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A Literature Review on Renewable Energy Resource and Optimization

Vijay Prakash Sharma 1 , Devendra Kumar Somwanshi 2 , Kalpit Jain 2 and Raj Kumar Satankar 3

Published under licence by IOP Publishing Ltd IOP Conference Series: Earth and Environmental Science , Volume 1084 , Second International Conference on Sustainable Energy, Environment and Green Technologies (ICSEEGT 2022) 24/06/2022 - 25/06/2022 Jaipur, Rajasthan, India Citation Vijay Prakash Sharma et al 2022 IOP Conf. Ser.: Earth Environ. Sci. 1084 012002 DOI 10.1088/1755-1315/1084/1/012002

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1 Assistant Professor, Manipal University Jaipur, Jaipur, India

2 Assistant Professor, Poornima College of Engineering, Jaipur, India

3 Associate Professor, Poornima College of Engineering, Jaipur, India

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Step by step the energy request is broadening and in this way the necessities for a manageable source that won't hurt the climate are of prime significance. Several projections express that by 2050 the energy requesting will basically increase. In any case bigger part of the energy necessities is fulfilled by oil subordinates yet by the utilization of innocuous to the environment power designs could help in giving the energy requests. As we in general understand that feasible power is the energy which is either established by the environment or straightforwardly from the sun or from heat conveyed critical inside the earth. In this review paper the renewable energy s power and warmth, which is produced using sun based, wind, sea, hydropower, biomass, geothermal assets, bio engages and hydrogen and these resources are known as unlimited resources.

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Towards Sustainable Energy: A Systematic Review of Renewable Energy Sources, Technologies, and Public Opinions

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• Published: 02 November 2020

A systematic review of the costs and impacts of integrating variable renewables into power grids

• Philip J. Heptonstall   ORCID: orcid.org/0000-0001-8411-6673 1 &
• Robert J. K. Gross   ORCID: orcid.org/0000-0003-3810-6663 1  

Nature Energy volume  6 ,  pages 72–83 ( 2021 ) Cite this article

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• Energy economics
• Energy science and technology
• Engineering
• Solar energy
• Wind energy

The impact of variable renewable energy (VRE) sources on an electricity system depends on technological characteristics, demand, regulatory practices and renewable resources. The costs of integrating wind or solar power into electricity networks have been debated for decades yet remain controversial and often misunderstood. Here we undertake a systematic review of the international evidence on the cost and impact of integrating wind and solar to provide policymakers with evidence to inform strategic choices about which technologies to support. We find a wide range of costs across the literature that depend largely on the price and availability of flexible system operation. Costs are small at low penetrations of VRE and can even be negative. Data are scarce at high penetrations, but show that the range widens. Nonetheless, VRE sources can be a key part of a least-cost route to decarbonization.

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Data availability

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Heptonstall, P.J., Gross, R.J.K. A systematic review of the costs and impacts of integrating variable renewables into power grids. Nat Energy 6 , 72–83 (2021). https://doi.org/10.1038/s41560-020-00695-4

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Received : 03 April 2019

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DOI : https://doi.org/10.1038/s41560-020-00695-4

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What really influences the development of renewable energy? A systematic review and meta-analysis

Yadong wang.

School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China

Associated Data

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Promoting renewable energy (RE) is one key strategy to increase energy security and mitigate global warming. What really influences the development of RE has aroused public attention worldwide. Numerous studies have identified and evaluated the critical influence factors (CIFs) for renewable energy development (RED); however, there seems to be no consensus among the previous studies on these CIFs and their importance level or influence direction. Given that, this study, for the first time, conducts a systematic review and meta-analysis of the CIFs for RED. With evidence from 33,119 observations in 67 studies between 2010 and 2022, 44 CIFs distributed in political, economic, environmental, social, and technological (PEEST) dimensions were selected from an international perspective. Results demonstrate that (i) 27 CIFs with statistical significance and their rank list were identified through meta-analysis. Some of them were mentioned many times in previous studies, but their significance for RED was not very high. (ii) The top three driving factors in CIFs’ significance rank list were industrial infrastructure investment , R&D , and financial development , and the top three inhibiting factors were the fossil-based energy consumption structure , policy uncertainty , and population life. (iii) The publication year, country’s economy, and links of the RED value chain have a moderating effect on some CIFs’ influence mechanisms. This study not only contributes to the existing RED knowledge body but also provides references to policymakers and practitioners in formulating policies and good practices to promote renewable energy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11356-023-26286-w.

Introduction

With the development of global industrialization in recent years, a large number of traditional fossil energy have been developed and utilized, resulting in a shortage of energy resources, environmental deterioration, climate warming, and other prominent problems. The survival and sustainable development of mankind has been seriously threatened (Liu and Espinosa 2019 ). In December 2015, the Paris Agreement set the target average rise in global temperature at 2 °C or even 1.5 °C by the end of this century (IPCC 2014 ). Obviously, the way energy production and consumption that is based on traditional fossil energy are no longer sustainable. Accelerating the transformation of energy structure and expanding the deployment of renewable energy (RE) have become important means, for worldwide countries, to cope with climate change and develop a low-carbon economy (IEA 2020 ; REN21 2013 ). According to the yearbook of “Renewable Energy Statistics 2021” issued by the IRENA (IRENA 2021 ), the global installed renewable power capacity will reach 2799 GW in 2020, an increase of 10.3% compared with 2019; more than 260 GW of new renewable power capacity was installed, up nearly 50% from 2019, as shown in Fig.  1 . However, in the transition from traditional fossil energy to RE, there is still the problem of insufficient energy supply. For instance, in 2020, the global shortage of gas, oil, and coal will lead to a sharp rise in the price of fossil energy (IEA 2021 ). Coupled with the impact of COVID-19, many countries are suffering from “energy shortage” and “electricity shortage” (Hoang et al. 2021 ). The main reason is that the development and deployment of RE still fail to meet the current energy demand gap (Tvaronaviciene et al.  2020 ). Therefore, it is particularly important to figure out the drivers and restraints in renewable energy development (RED) on a global scale.

Installed renewable power capacity in 2020

To promote the sustainable development of RE, some existing studies have explored the influencing factors of RED from different perspectives. For example, Cadoret and Padovano ( 2016 ) and Zhao et al. ( 2021 ) both confirmed that the high quality of government regulation and administrative intervention contribute to the deployment of renewable energy; Zhang et al. ( 2021 ) and Vural ( 2021 ) both put forward the view that trade openness can promote the supply and demand of RE. But what’s even more remarkable is that some of the existing studies do not seem to reach a consensus. For example, in earlier studies, Marques et al. ( 2010 ) thought that the socioeconomic and political factors are mainly robust, but the CO 2 emission mitigation did not promote RED. However, using a longer time series (1990–2010) and a wider sample size of countries (including Brazil, Russia, India, China, and South Africa), Aguirre and Ibikunle ( 2014 ) indicated that CO 2 emission levels are significant indicators of renewables participation, which are contrary to Marques et al. ( 2010 ). Moreover, they pointed out that developing countries with lagging GDP tend to seek more fossil-based solutions and other cheap alternatives rather than renewables, but the study of Bamati and Raoofi ( 2020 ) demonstrated that GDP is the main driver of RE production in developing countries. In a word, there is no consensus among previous studies on the critical influence factors (CIFs) for RED and their importance level or even influence direction, which makes it difficult to theorize the research on RED in the realm of forecasting and policy.

Although some scholars have pointed out, through qualitative literature review, that these disagreements may be caused by different research designs or sampling differences, the real reasons still need to be further explored by a systematic review of relevant literature and verified by more convincing quantitative review methods. A few review papers conducted a systematic literature review for the influence factors of RED through qualitative or descriptive quantitative statistical methods, but they only summarized and investigated the frequency of influence factors (Sener et al. 2018 ; Bourcet 2020 ). Actually, it seems that the frequency is not able to reveal the importance of CIFs exactly (Hussein and Zayed 2021 ; Chen et al. 2022 ). Meta-analysis could overcome this shortcoming, which is deemed to be more reliable and transparent than a narrative review (Glass et al. 1981 ). Because it has two advantages: first, by using it, researchers can aggregate multiple research results on the same research topic and get stronger universal conclusions on a certain research field; second, it can explore the boundary conditions of the relationship between variables, test the moderating effect, and better interpret the relationship between variables (Certo et al. 2006 ; Cui et al. 2018 ). Therefore, this study, for the first time, provides a systematic review and meta-analysis of the CIFs for RED. To further provide a quantitative synthesis analysis of previous studies, a meta-analysis approach is adopted. The obtained results answer some of the unanswered queries identified as gaps in the literature, such as the critical roles of PEEST factors for RED and their respective levels of significance for RED.

Literature review

Definition of red.

The usage of RE has multiple benefits, as the energy produced from natural processes, including reducing greenhouse gas emissions (Gareiou et al. 2021 ), improving energy security (Ibrahiem and Hanafy 2021 ), promoting green and sustainable economic growth (Dogan et al. 2020 ), etc. The main types of RE include solar energy, wind energy, hydro energy, geothermal energy, and biomass energy (IEA 2016 ). It should be highlighted that the RE mentioned here is in a broad sense; in other words, it is a general term for energy forms such as solar energy, wind energy, and so on, without specifically discussing one of the special energy. The reason is that the research scope of limiting the analysis to a single type of RE is very narrow, which is inconsistent with the wide range required by a systematic literature review (Snyder 2019 ).

According to Porter’s value chain theory (Porter 1990 ), the R&D, production, sales, and transportation activities of an industry can be expressed by the value chain. Zhang and Yang ( 2020 ) extended this theory to the energy industry and put forward the concept of the value chain of the RE industry (REI), which includes technological innovation, project investment, production, transmission, and consumption of RE. Specifically, power generation is the main utilization form of RE (Wang et al. 2021a , b , c ); technological innovation can significantly reduce the utilization cost of RE such as power generation (Lin and Chen 2019 ); investment is an important force to promote the development of REI (Bai et al. 2021 ); at the same time, the growth of RE consumption can reduce the country’s dependence on traditional fossil energy and imported energy (Zhang et al. 2021 ). All of these activities can actively promote the orderly expansion of REI. Therefore, in this study, we define RED as a four-in-one value chain including the links of “innovation-investment-production-consumption.” The conceptual framework of RED is shown in Fig.  2 .

Conceptual framework of RED

Influence factor of RED

The benefits of RED have motivated many researchers to study “What drives the development of renewable energy?” The seminal paper of Sadorsky ( 2009a , b ) discussed the impact of GDP per capita, CO 2 emissions, and oil prices on the RED. Then, flourishing literature has emerged to discuss the factors that prompt or inhibit RED from various perspectives (Salim and Rafiq 2012 ; Darmani et al. 2014 ; Xu et al. 2019 ). The factors affecting RED in previous studies can be summarized into these categories: economic, financial, environmental, political, social, technological, and so on (Sener et al. 2018 ). Among them, economic factors such as GDP per capita (Vulal 2021; Churchill et al. 2021 ) and GDP (Uzar 2020a ; Sweidan 2021a ) and environmental factors such as CO 2 emissions (Zheng et al. 2021 ; Assi et al. 2021 ) are the most concerned and studied frequently. Other factors include financial development (Lin et al. 2016 ), trade openness (Churchill et al. 2021 ), energy price (Li and Leung 2021 ), R&D (Khezri et al. 2021 ), government regulation (Gan and Smith 2021), population (Radpour et al. 2021 ), urbanization (Wang et al. 2018 ), etc.

Existing literature available on the drivers or inhibitors explaining the diversity of RED provides an evaluation of the importance level of CIFs. However, there is little consensus among the previous studies. The disagreement between them is regarding the influence degree even the influence direction of CIFs, as shown in Table ​ Table1. 1 . This table provides an example of three CIFs, and some studies consider them as significant or driving factors for the RED, while other studies estimated them as non-significant or inhibiting factors. Taking GDP per capita as an example, its role is mixed. In the studies of Chen ( 2018 ), Oluoch et al. ( 2021 ), and Churchill et al. ( 2021 ), GDP per capita significantly promoted RE’s production and consumption, while Assi et al. ( 2021 ) believed that the impact of GDP per capita on RE consumption is not statistically significant. Also, Aguirre and Ibikunle ( 2014 ) and Hao and Shao ( 2021 ) reported its negative impact, they hold that developed countries with higher GDP per capita usually have a mature energy structure dominated by fossil energy, which makes their energy transformation to RE face a greater challenge.

Disagreement between previous studies on the CIFs for RED

Although these inconsistent views may be attributed to the differences in research specifications, sampling variation, or data availability, an international review of the CIFs required for RED and a generalized understanding of the importance of these CIFs are both warranted and imperative. The systematic identification of CIFs is not only important to understand the research gaps and avoid the duplication of future research, but also can help the policy designer of the countries in different economies to propose more targeted RED promotion strategies.

Review studies of CIFs for RED

To the best of our knowledge, four review papers discussed the CIFs for RED. Specifically, Bourcet ( 2020 ) reviewed the literature that emerged in the late 2000s to study the quantitative determinants of RED at a country level. Their main contribution is that they used a variety of frameworks to measure RE deployment and revealed the consensus and non-consensus about the empirical determinants of RE deployment. Apfel et al. ( 2021 ) made a systematic literature review of renewable energy in the Global South from the technological focus, political perspective, socio-cultural context, economic, and social aspects. They concluded that the current analytic perspectives are predominantly techno-economic, with a conspicuous lack of thought given to business potentials and energy infrastructure. Njoh ( 2021 ) identified and analyzed environmental and institutional factors affecting renewable energy initiatives on the demand and supply sides in Ethiopia. Additionally, Sheikh et al. ( 2016 ) and Jenniches ( 2018 ) conducted a similar systematic literature review, but they only focused on the political and social impact of RE development and its relationship with energy growth.

However, these review studies still have some limitations. For example, Apfel et al. ( 2021 ) only focused on the research agenda about RE in the developing countries of Africa, Asia, and South America, and Njoh ( 2021 ) only discussed the PESTECH factors of RED’s consumption and production. The former was limited to the national sample, and the latter omitted the focus on innovation or investment of RED. Although Sener et al. ( 2018 ) and Bourcet ( 2020 ) provided a rich analytical framework for identifying the determinants of RED from qualitative or quantitative research. The limitation was still existing because they only summarized and investigated the frequency of factors implemented in previous studies, which cannot recover the importance of CIFS exactly. Moreover, Bourcet ( 2020 ) also mentioned that meta-analysis could be the next step to go further in the analysis of the reviewed papers’ results.

Given these limitations, this study discusses the CIFs for RED based on the PEEST framework through a systematic review and meta-analysis, which can provide more reliable evaluation results and the importance ranking of CIFs. The meta-analysis assumes a different approach to estimating a model with the individual studies participating as individual observations with a respective weight, and the obtained results can be rigorous with reliable predictions (Menegaki et al. 2021 ).

Research methodology

Meta-analysis is a quantitative research methodology that provides comprehensive synthesis by integrating several independent empirical studies which are comparable under the same criteria. Meta-analysis is often combined with a systematic review, which could guarantee the completeness of the literature selection (Oxman and Guyatt 1993 ; Liberati et al. 2009 ). The system review result is only presented in the form of narrative comments and lacks quantitative analysis (Grant and Booth 2009 ). However, meta-analysis is a quantitative technology, which takes previous studies as a sample to extract data, synthesize several individual studies, and provide a more accurate effect size (ES). In general, a systematic review is the basis of the effectiveness of meta-analysis (Borenstein et al. 2021 ). Accordingly, in this study, we integrated a systematic review and meta-analysis to maximize the advantages of these two methods. The research framework and procedures are shown in Fig.  3 .

The framework of the systematic review and meta-analysis

Data collection and selection criteria

Search strategies.

At least two search databases are required to achieve accurate retrieval of studies (Zhu and Liu 2020 ). In this study, the researchers chose to search for relevant studies in Chinese databases (CNKI, VIP, and WanFang) and English databases (Science Direct, Springer, and Web of Science). 1 Then, two search strategies are proposed, i.e., keyword-based search and snowballing research. For the keyword-based search strategy, the representative keywords included “renewable energy,” “renewable energy development,” “renewable energy power generation,” “renewable energy innovation,” “renewable energy technology,” “renewable energy investment,” “renewable energy consumption” and combined with the keywords of “influencing factor,” “driving factor,” “influence,” “promote,” and “inhibit.” The snowballing research was conducted after the keyword search to avoid omitting the relevant studies, including backward snowballing and forward snowballing. Meanwhile, the publication year was set between 2005 to 2022. To avoid the risk of publication bias, there are no restrictions on the article types, countries, or publishers.

Inclusion and exclusion criteria

The inclusion and exclusion criteria were set as the benchmark of literature selection. The inclusion criteria are (1) the study object is RED and its influencing factors; (2) the study is quantitative empirical research; (3) the study is conducted from the country or region level; (4) the study reports the correlation coefficient or statistical values that can be converted to ES such as regression coefficient, t value, and z value. The exclusion criteria are (1) the study analyzed the influencing factors of a single type of RE; (2) the qualitative study and review study of case analysis, interview, and SWOT analysis; (3) the study is conducted from the micro level (such as family and individual); (4) the study is not available to the full text; and (5) duplicate studies or studies with same sample data.

Literature selection

The process of literature selection following the new PRISMA statement is shown in Fig.  4 (Page et al. 2021 ). Firstly, through a keywords-based search, the initial records were obtained from Chinese and English databases. By using Endnote software and manual identification, the duplicated and non-conforming records were removed. 2 Then, the title and abstract were reviewed in detail for achieving the preliminary screening. At this stage, the authors have completed the screening of studies that need to be included in the evaluation. Next, through the examination of the full text, some studies that unqualified inclusion criteria were excluded, such as the lack of reports on the statistical values that can be transformed into ES. Fifty-five studies meeting the criteria were obtained in the keywords-based search process. Afterward, 25 studies were identified through the snowballing search, and then, 7 studies remained after the screening process. Finally, 62 studies were included in the literature database for meta-analysis, including 55 studies from keywords-based search and 7 studies from snowballing search. The literature retrieval was completed in October 2021. 3

PRISMA flow diagram for literature selection (adapted based on the PRISMA 2020 flow diagram [ http://www.prisma-statement.org/ ]) (notes: * refers to the papers that were published in a non-English language or gray literature; for example, committee publications and industry flyers. ** refers to the studies that were out of scope after the review of the title and abstract, that is, not relating to renewable energy development and its influence factors. Examples include publications relating specifically to the effect of renewable energy on economic or carbon emissions)

Data coding

After the literature selection, it is necessary to extract the required data and encode it. The data extracted from previous studies contained the statistics values that can transform into ES (i.e., the correlation coefficient). Referring to the coding steps of previous studies (Cui et al. 2018 ; Ma et al. 2021 ), the following points need to be explained: (1) each study only participates in coding once. If the study contains multiple independent research samples, the coding process can be repeated; (2) the CIF that appeared in at least two studies will be data coded; (3) when one CIF appeared in two studies with opposite meanings, only one meaning was taken; (4) to make the data comparable, the CIFs with highly similar meanings but different names are coded together. After the data coding procedures, 4 a total of 67 studies are coded, and their specific information is shown in Table ​ Table2 2 .

Basic information of the literature included in meta-analysis

Study ID is written as follows: the last name of the first author + year + optional key information (article type, J indicates journal article, T indicates graduation thesis) (sampling country, the meaning of the abbreviation is shown in the column of “sampling country”) (Links of RED value chain, IV indicates innovation, IT indicates investment, P indicates production, C indicates consumption)

Procedures of meta-analysis

In this study, standard meta-analysis procedures are followed. As shown in Fig.  3 , the first step in performing the meta-analysis is to decide on the effect size based on the available type of data and the purpose of the analysis. Then, the heterogeneity analysis is followed. The purpose of the heterogeneity analysis is to test whether there is heterogeneity among the selected studies, and then, the appropriate statistical model can be chosen. When heterogeneity is high, the random effect model (REM) should be selected; otherwise, the fixed effect model (FEM) should be selected. After the statistical model selection, the subgroup analysis should be conducted. The purpose of subgroup analysis is to divide studies into subgroups according to specific criteria and discuss the possible impact of this grouping on meta-analysis results. The classification criteria of subgroups can be any factor that researchers believe may have an impact on the results, such as publication year and country. Then, the sensitivity analysis is needed, aiming to examine the robustness of results and discuss the impact of other elements on the results. Finally, a common problem in meta-analysis is “publication bias.” Publication bias analysis is needed to verify the reliability of data before meta-analysis. There are two common approaches, i.e., qualitative and quantitative methods. The specific methodology of the above six procedures of meta-analysis is shown in Appendix A.

CIF identification and data extracted

After literature selection and data coding, 62 studies meeting the criteria were finally included in the meta-analysis, among which 3 studies involved multiple independent samples, so a total of 67 independent studies were included in the literature database finally. Table ​ Table2 2 shows their specific information.

Subsequently, after a careful full-text review of each study, 44 CIFs were identified, 5 as shown in Table ​ Table3. 3 . Following the cross-dimension classification of RED influencing factors first proposed by IEA ( 2015 ) and combined with the actual meaning of these identified CIFs, 44 CIFs were divided into five categories, i.e., PEEST. The measure and frequency of CIFs that appeared in the studies were also illustrated in Table ​ Table3 3 .

Critical influence factors for renewable energy development

Only the representative indicators are listed in the column of “measure”; “frequency” means the occurrence of each CIF in the literature database

Numerical example

A numerical example of CIF15 “GDP per capita” on meta-analysis procedures was provided in this subsection, and the remaining 43 CIFs repeated these procedures. Table ​ Table4 4 shows the sample data of CIF 15, which were identified to the software function of Meta-Analysis in Stata 16.0. The results contained the statistical result of meta-analysis, heterogeneity report, subgroup analysis, sensitivity analysis, and publication bias.

Identified statistical data of CIF15 for meta-analysis

Study ID is written as follows: the last name of the first author + year + optional key information (article type, J indicates journal article, T indicates graduation thesis) (sampling country, CHN means China, OECD means the organization for economic co-operation and development countries; DI means developing countries; DD means developed countries; BR means the Belt and Road countries; SSA means Sub-Saharan Africa; ASEAN means the Association of Southeast Asian Nations countries, APC indicates Asia-Pacific countries; W indicates the global countries; LA indicates Latin American countries) (Links of the RED value chain, IV indicates innovation, IT indicates investment, P indicates production, C indicates consumption)

Heterogeneity analysis shows that P -value was 0.000 and I 2 = 96.8 % , indicating that high heterogeneity existed in CIF 15. As a result, REM was adopted for reducing the high heterogeneity. The forest plot provided visualized meta-analysis results, as shown in Fig.  5 . 6 The ES of a study was depicted as a point estimate that was bounded by its confidence interval (95% in this study). As shown in Fig.  6 , the SES of CIF 15 is 0.12, indicating that GDP per capita has a positive effect on RED.

Meta-analysis result and forest plot of CIF 15 (note: ES means the effect size, 95%CI indicates the lower and upper limits of the 95% confidence interval of ES, and % Weight refers to the weight of ES; the meaning of study ID is the same as that in Table ​ Table4 4 )

Sensitivity analysis of CIF15

The results of the subgroup analysis were shown in Table ​ Table5. 5 . Twenty-five studies involving CIF 15 were grouped according to three criteria of publication year, country’s economy, and LREDVC. The test results for subgroup differences showed that, among these groups, the moderating effect of the country’s economy is the only influential criterion because there is a significant difference ( P < 0.05 ) in the importance level of CIF 15 among different subgroups.

Subgroup analysis of CIF15

k refers to the number of studies

Sensitivity analysis and publication bias analysis were performed finally. Figure  6 presents the forest plot of sensitivity analysis. If one study located in the Y-axis was removed, then reacquired ES, and lower and upper confidence intervals were shown in the right line. As can be seen from Fig.  6 , after the studies were removed item by item, the variation of SES was small, indicating that the sensitivity of CIF 15’s sample data was low and the meta-analysis results were robust and reliable. Figure  7 shows the funnel plot of CIF 15 for the publication bias test. It shows symmetrical distribution after conducting Tweedie’s Trim and Fill. In addition, the Failsafen of CIF15 is 4802, which is much much higher than the threshold value of 135 (i.e., 5 ∗ 25 + 10 ). Therefore, it is proved that the publication bias is too slight to affect the result.

Funnel plot of standard error by the effect size for CIF 15

Meta-analysis results

Following the analysis procedure of CIF15, the remaining 43 CIFs have conducted a meta-analysis in turn. Table  B1  in Appendix B summarizes the meta-analysis results of each CIF as well as the test results of heterogeneity and publication bias. Next, the results shown in Table B1 will be discussed in detail.

Statistical results of meta-analysis

Column 4 of Table B1  shows SES and its 95% confidence interval, and column 5 reports the Z value and P value of the two-tailed test. In addition, columns 2 and 3 show the number of studies k and total sample size n for each CIF, respectively. Through meta-analysis, 27 CIFs in PEEST dimensions with statistical significance ( P < 0.05 ) were obtained respectively.

• The role of political factors

As shown in Fig.  8 , seven significant CIFs were identified in the political dimension. Specifically, CIF4 “energy security” and CIF12 “policy uncertainty” have significant negative impacts on RED. CIF1 “market-oriented regulation,” CIF6 “regulatory quality,” CIF8 “Kyoto protocol,” CIF9 “administration-oriented regulation,” and CIF13 “geopolitical risk” have significant positive effects on RED. Among them, the most influential factor is CIF12 ( ES = - 0.317 ), and the least influential factor is CIF 9 ( ES = 0.061 ).

• (2) The role of economic factors

Meta-analysis results of significant political factors (notes: CIF 1 indicates “market-oriented regulation,” CIF4 indicates “energy security,” CIF6 indicates “regulatory quality,” CIF8 indicates “Kyoto protocol,” CIF9 indicates “administration-oriented regulation,” and CIF13 indicates “geopolitical risk”)

For the economic factors, five significant CIFs were obtained. As shown in Fig.  9 , they are CIF15 “GDP per capita,” CIF16 “oil price,” CIF17 “financial development,” CIF18 “GDP,” and CIF19 “trade openness.” All of them have a positive promoting effect on RED, and CIF17 has the strongest promoting effect.

Meta-analysis results of significant economic factors (notes: CIF15 indicates “GDP per capita,” CIF16 indicates “oil price,” CIF17 indicates “financial development,” CIF18 indicates “GDP,” and CIF19 indicates “trade openness”)

• (3) The role of environmental factors

Among the environmental factors, three significant CIFs were identified, as shown in Fig. ​ Fig.10. 10 . Three CIFs are CIF24 “natural endowments,” CIF27 “environmental regulation,” and CIF28 “carbon dioxide emissions intensity” respectively. CIF24 and CIF 27 affect RED positively, while CIF28 has a significant inhibitory effect on RED.

Meta-analysis results of significant environmental factors (notes: CIF24 indicates “natural endowments,” CIF27 indicates “environmental regulation,” and CIF28 indicates “carbon dioxide emissions intensity”)

• (4) The role of social factors

As shown in Fig.  11 , six significant CIFs were identified in the social dimension. Specifically, CIF30 “urbanization,” CIF31 “education degree,” and CIF34 “social acceptance” have significant positive effects on RED, while CIF33 “fossil-based energy consumption structure” inhibits RED.

• (5) The role of technological factors

Meta-analysis results of significant social factors (notes: CIF30 indicates “urbanization,” CIF31 indicates “education degree,” CIF33 indicates “fossil-based energy consumption structure,” CIF34 indicates “social acceptance,” CIF 35 indicates “income inequality,” and CIF 37 indicates “population life”)

Six CIFs have a statistically significant effect on RED in technological factors, as shown in Fig.  12 . They are CIF38 “R&D,” CIF39 “industrial infrastructure investment,” CIF40 “fossil-based energy consumption structure,” CIF41 “technology and change,” CIF42 “knowledge storage,” and CIF43 “installed renewable power capacity . ” Except for CIF40 has a significant negative effect, the other five CIFs have significant positive effects on RED.

Meta-analysis results of significant technological factors (notes: CIF38 indicates “R&D,” CIF39 indicates “industrial infrastructure investment,” CIF40 indicates “fossil-based energy consumption structure,” CIF41 indicates “technology and change,” CIF42 indicates “knowledge storage,” and CIF43 indicates “installed renewable power capacity”)

Heterogeneity analysis and public bias

The heterogeneity test results are shown in column 6 of Table B1 . The Q value reflects the degree of heterogeneity of each effect size, and I 2 represents the proportion of heterogeneity in a total variation of ES. Take CIF4 as an example, the Q value is 106.51 ( P < 0.001 ), showing that there was heterogeneity among different independent ESs; I 2 is 95.3%, showing that 95.3% of the observed variation was caused by the true differences in ESs, and 4.7% was caused by the random differences. Through the heterogeneity test of all CIFs, it can be concluded that except for the ESs of CIF6, CIF9, CIF13, CIF28, CIF37, CIF43, and CIF44 have no significant heterogeneity, the remaining CIFs exist varying degrees of heterogeneity. Therefore, as shown in the model selection in column 7 of Table B1 , the FEM is adopted to calculate the SESs of these seven CIFs, while the REM is adopted for other remaining CIFs. The test results of publication bias are shown in column 8 of Table B1 . When the Failsafen is greater than the threshold value of 5 k + 10 , it can be judged that there is no publication bias. It can be found that except for some CIFs with insignificant ES, there is no publication bias in the other remaining CIFs.

Subgroup analysis

Table B2  in Appendix B summarizes the subgroup analysis results of 44 CIFs based on the three criteria mentioned in section 3.5.4. If the P - v a l u e < 0.05 , indicating that the criteria significantly reduced the heterogeneity between subgroups.

As for the subgroup of the publication year, there were 38 CIFs suitable for the subgroup analysis, and 8 CIFs showed significant subgroup differences. This indicates that there are cognitive differences in the effect of these 8 CIFs on RED between the old studies and recent studies. In particular, CIF7 “corruption control” and CIF14 “political stability” even differ in the direction of influence. While the old studies suggested that both corruption control and political stability promote RED, the recent studies suggested the opposite. According to the study of Hakimi and Hamidi ( 2020 ), the impact of corruption and political instability depends largely on trade openness, and trade liberalization reduces corruption’s impression of environmental rules and mechanisms. Hence, it can be guessed that the sample selection of the new study is more recent, and the complex fluctuations of the international trade situation under the COVID-19 in the past 2 years have interfered with the driving mechanism of the two political factors CIF7 and CIF14 (Hoang et al. 2021 ; Liu et al. 2021 ).

In the subgroup of the country’s economy, there were 12 CIFs showed significant subgroup differences, indicating that the type of country’s economy plays a moderating role in the effect mechanism of these 12 CIFs. Taking CIF15 “GDP per capita” with the highest frequency as an example, in the sample studies of developing and developed countries, the higher the GDP per capita level is, the more favorable it is to RED. Moreover, its effect is stronger in developed countries. However, in the sample studies worldwide, the GDP per capita level has a slight negative impact on RED. Therefore, it can be concluded that there is no consensus about the effect of GDP per capita both in samples of developing and developed countries and in samples at a global scale (Bourcet 2020 ). The explanation for this given by Cadoret and Padovano ( 2016 ) was that, when economic activity increases, the greater energy consumption that the increased production requires is not immediately met by RE, but by other more elastic energy sources like fossil-based energies. In other words, when GDP per capita reaches a certain threshold, it will harm RED.

To determine the influence of LREDVC, the studies were classified into four subgroups. There are 15 CIFs showed significant subgroup differences, indicating that the influence mechanism of some factors may differ greatly in different LREDVC. Take CIF23 “CO 2 emissions” as an example, it has a positive impact on production, that is, the higher the CO 2 emission level is, the more conducive it is to the growth of RE power generation. However, it has a negative impact on the innovation, investment, and consumption of RE. Marques et al. ( 2010 ) proposed that greater amounts of CO 2 mean more incentive toward renewable power generation. In contrast, Bai et al. ( 2020 ) hold that mature traditional energy market and development technologies in countries with high CO 2 emissions, coupled with the inherent consumption habits of energy users, restrict the promotion and deployment of RE. These conflicting mechanisms might explain why different conclusions are documented in the different LREDVC.

Sensitivity analysis

In the sensitivity analysis, removing one study will change the SES to varying degrees. The smaller the change degree of SES, the more robust the results. Therefore, it makes sense to explore the results of sensitivity analyses only if we find a reason to remove studies whose results differ significantly from other studies. In this study, the change rate of 50% was set as a benchmark, we screened out the studies with a change rate of more than 50% and the occurrence frequency of more than one time, and tried to find out the reasons why these studies greatly affected the robustness of meta-analysis results. These included CIFs and selected studies were illustrated in Fig.  13 . 7

Major effect size changes of 16 CIFs through sensitivity analysis

As shown in Fig.  13 , the study ID of Ibrahiem and Hanafy ( 2021 ) (J)(NAC)(C) appeared 5 times, which is the most frequent one in the figure. After reviewing this study, we find that it is unique in many aspects. The first is that the sampling country of this study was Egypt, Morocco, and Tunisia, these three countries have great differences in both economic development level and deployment of renewable energy compared with the high occurrence frequency of China and some OECD countries. The second is that the research data was annual data from 1971 to 2014 and was with a large time window span and coarse data particles. Therefore, this study may have different observations on CIFs for RED.

Discussions and recommendations

Further discussions on top cifs.

Figures  14 and ​ and15 15 show the CIFs ranking based on the frequency-importance and the significance-importance, respectively. It can be seen that the CIFs ranking based on frequency-importance is very different from the CIFs ranking based on significance-importance. For example, although CIF23 “CO 2 emissions” was mentioned many times in previous research, its significance for RED did not appear. Moreover, CIF 33, CIF 12, and CIF 37, as hindering factors, had a significant impact on RED statistically, but they received little attention from researchers. And only CIF17 was in both top lists, implying that CIF17 “financial development” appeared in previous studies frequently and had high significance for RED. Specifically, finance enhancement especially green finance significantly contributes to renewable energy technologies. For example, energy storage technology and hydrogen technology need to be improved with mass finance input. Therefore, policies must consider green finance enhancement for encouraging renewable energy investment. Overall, these differences numerically demonstrate that the frequency of occurrence of any factor in the literature does not necessarily reflect its importance level.

CIFs ranking based on the frequency-importance (note: only CIFs whose frequency is at least 5 is displayed here)

CIFs ranking based on the significance-importance (notes: the red bar chart represents the negative impact and the green bar chart represents the positive impact. The length of the bar chart represents the degree of influence, and the longer the bar, the greater the degree of influence)

According to the ranking analysis, two meaningful findings can be concluded, as follows:

• First, the factors concerned mostly are distributed in economic and environmental dimensions, and most of them are promoting factors, while the inhibiting factors, which also have a significant effect on RED, seem to receive little attention. Since the Industrial Revolution, the relationship between the economy, environment, and energy has been the focus of scholars’ attention (Menegaki et al. 2021 ), which also explains the high frequency of using economic and environmental variables. In contrast, research on some of the obstacles in the social dimension is scarce, even though these factors are inevitable for countries to take into account to achieve sustainable RED. Therefore, future research should focus more on addressing these potential social barriers.
• Second, if the literature review was only conducted through qualitative methods, some key information would be omitted, leading to inaccurate conclusions, which had no benefit to RED promotion in practice and even given the wrong signal to future research. The different CIFs ranking results demonstrated that meta-analysis plays a vital role in capturing the quantitative messages conveyed by previous studies (Hussein and Zayed 2021 ; Chen et al. 2022 ).

Moderating effects of three criteria

The potential moderating effects of three criteria in terms of publication year, country’s economy, and LREDVC that the dependent variable belongs to were examined in this study (the empirical results are shown in Table B2 ), which is also a significant contribution to the existed qualitative literature review studies, as follows:

• First, the time-varying effects of political and social factors on the influence mechanism of RED deserve attention. The influence mechanism of 8 CIFs was moderated significantly by “publication year,” and these 8 CIFs mainly distributed in political and social dimensions. In the subgroup of old studies, both CIF 7 “corruption control” and CIF14 “political stability” play a positive role, but in the subgroup of recent studies, they are seen as more of a hindrance. Taking CIF30 “urbanization” as an example, the influence of CIF30 was relatively weak in old studies (ES = 0.038), while the ES of new studies (ES = 0.206) showed that the influence of CIF30 was significantly improved. These inconsistent results imply that relevant policymakers need to optimize RED’s regulatory strategies according to the changing political situation and historical course of social development. For example, recent studies have confirmed that the impact of social acceptance on RED appeared to be less important, which raises the question of whether incentives for public acceptance of RE need to be adjusted in time to ensure the proper allocation of resources.
• Second, the coarse-grained mixed country sampling may obscure research results. This finding is consistent with the view of Ahmad et al. ( 2020 ) and Menegaki et al. ( 2021 ) that energy use is generally closely related to a country’s level of development. Specifically, our results show significant heterogeneity in the impact of 12 CIFs on RED across developing, developed, and global scales. It is worth noting that the signing of CIF8 “Kyoto protocol” can promote RED in developed countries, but it plays an opposite role in developing countries, as does the CIF 10 “administrative intervention.” Interestingly, the two most concerning economic and environmental variables, i.e., CIF 15 “GDP per capita” and CIF23 “CO 2 emissions,” also differ widely in countries at different levels of development. GDP per capita is the driving force and CO2 emissions are the restraining force in both developing and developed countries, which is consistent with most research results. However, global samples show that CO 2 emissions contribute to RED while GDP per capita inhibits it, indicating that it is necessary to distinguish the sampling method when referring to the empirical results.
• Third, it is crucial, when discussing the influence factors, to standardize the dependent variables used to explain the dynamics of RED. According to the dependent variables used in previous studies, the RED can be represented by the four LREDVC, i.e. innovation, investment, production, and consumption. 8 The systematic combining of the selected dependent variable of RED means a well-represented framework of CIFs and more accurate meta-analysis results. As shown in Fig.  15 , critical roles on the four links are presented and their influence level and direction are obtained. It conveys a signal that a certain influencing factor may have different effects on different value chain links of RE. As the subgroup difference test results showed, 14 CIFs were significantly moderated by dependent variable selection (see Table B2 ). For example, CIF23 is a strong hindrance factor in innovation, investment, and consumption links, but a driving factor in production links. This also explains why the comprehensive impact of this factor on RED is not significant.

Recommendations for future research and policy design

Based on the empirical results and further discussions, some recommendations for future research and policy design can be proposed as follows.

• Recommendations for future research. (i) The frequency of occurrence of any factor in the literature does not necessarily reflect its importance level. The jury of some CIFs is still out, so the over-reliance on factors that are studied frequently in empirical research, such as economic and environmental factors, may result in the omission of key information; (ii) Future research should address some potential barriers for a systematic examination of RED (as shown in Fig.  15 ), rather than duplicating some consensus-forming drivers such as R&D and GDP per capita. Moreover, the current research on CIFs of renewable energy policy is also weak. (iii) The temporal and spatial effects of some factors should be concerned in further studies, in particular, some of the political factors that have changed dramatically recently and the social factors with potential accumulative effects, such as geopolitical risk, population, and urbanization. (iv) The measurement method of RED in current studies has not been unified, which needs to be improved in future studies. Bourcet ( 2020 ) also holds the same view.
• Recommendations for policy design. (i) Inspired by the importance ranking list of critical factors, the government could shift direct subsidies, which have a modest impact on the renewable energy sector, into more important aspects such as infrastructure construction and R&D input. At the same time, the financial policy resources such as bank credit should be appropriately tilted toward the renewable energy industry. (ii) Policies for RE development in developing and developed countries should be varied. For instance, developing countries are more sensitive to carbon market pricing than developed countries, and government administrative intervention may play opposite roles in developed and developing countries. Therefore, developing countries with relatively backward RE development should be very cautious in learning successful experiences from developed countries with advanced RE development, and should not blindly copy it; otherwise, it will produce negative effects. (iii) Some fine-grained policies, promoting the RE’s technology innovation, attracting investment, power generation, and active consumption (Fig.  15 provides some key hints), should be specifically put forward and a package of RED policies adding value to the RE industrial chain could be formed accordingly. (iv) Last but not least, some dynamic policies should be considered with the spatial–temporal evolution. For example, the varied urbanization processes mean different demands for RE, and social public acceptance also plays a different role as well in countries at different stages and levels of development.

The innovation and contribution of this paper

The main contributions of this study can be concluded threefold. First, 44 CIFs for RED distributed in PEEST dimensions are identified through an international systematic review, providing a more reliable framework for future empirical research. Second, the importance level and influence direction of 44CIFs, for the first time, are quantitatively evaluated through the meta-analytically synthesis of the previous studies. The large sample size in meta-analysis guaranteed more accurate results than the independent empirical study. Third, the key factors affecting RE’s innovation, investment, production, and consumption are further identified, combining four different RED links allowed us to increase the level of representation of the factors affecting RE deployment decisions. Overall, this systematic and quantitative literature review of CIFs for RED is significant, both for public policy recommendations and for structuring future research.

Conclusions

For constructing a global energy structure with a high proportion of renewables, it is crucial to figure out what really influences the development of renewable energy. This study, for the first time, contributes to the existing RED knowledge by identifying the CIFs in PEEST dimensions with a quantitative approach of meta-analysis. The main conclusions are as follows:

• The frequency of occurrence of any factor in the literature does not necessarily reflect its importance level. A more reliable and transparent ranking list of CIFs for RED is summarized in this study. The results show that the top three promoting factors are “industrial infrastructure investment,” “R&D,” and “financial development.” And the top three obstructive factors are “fossil-based energy consumption structure,” “policy uncertainty,” and “population life.”
• The heterogeneity in the significance level of CIFs caused by multiple moderators is empirically uncovered by the subgroup analysis. Spatial-temporal heterogeneity of the influencing factors and the definition of the dependent variable deserve attention when conducting empirical research. Based on a systematic review of previous empirical studies about the critical factors affecting RED, the obtained meta-analysis results uncover multiple gaps in the current theoretical knowledge.
• This study could serve as a stepping stone for future research to complete the theory development of CIF’s importance level identification for RED. Meanwhile, the valuable findings have practical implications for policy design for RED.

Despite the encouraging results, this study has several limitations. First, the literature selection cannot be exhaustive. In the future, various databases or search engines, such as Google Scholar, can be used to expand the knowledge of the existing study on CIFs for RED. Second, in the subgroup analysis, there is great heterogeneity among some ESs, indicating that there are other potential moderating variables not discussed in this paper. It is expected that the follow-up research can effectively solve this problem and explore more valuable conclusions. Third, there may be correlations between some CIFs or bidirectional causality between some CIFs and RED. This issue was not considered in this study. Hence, further research could switch the attention to unlocking the “black box” of these complex influence mechanisms.

Below is the link to the electronic supplementary material.

Abbreviations

Author contribution.

Yadong Wang: conceptualization, methodology, software, formal analysis, writing—original draft; Delu Wang: writing—review and editing, supervision, project administration, funding acquisition; Lan Yu: resources, software, methodology; Jinqi Mao: visualization, investigation, validation.

This work was supported by the National Natural Science Foundation of China (No.72074210); the National Social Science Fund Later Funding Project of China (No. 20FGLB049); and the Chinese Scholarship Council (No. 202206420051).

Data availability

Declarations.

We declare that we do not have human participants, human data, or human tissue involved in the study.

Not applicable.

The authors declare no competing interests.

1 CNKI, VIP, and WanFang are authoritative databases in China, covering almost Chinese academic articles on all subjects. More and more academic articles prefer to search literature in Science Direct and Springer because they are highly recognized by researchers worldwide in tracking the newest knowledge in various research fields. Besides, the lists of indexed content in Web of Science, Science Direct, and Springer are clear. Therefore, this study chose to search for relevant studies in Chinese databases (CNKI, VIP, and WanFang) and English databases (Science Direct, Springer, and Web of Science).

2 Initial searches yielded 15,149 records, and 14,124 records remained after removing the duplicated and non-conforming records.

3 Evidence-based science requires two researchers (Yadong Wang and Lan Yu) to screen the literature back-to-back and blind. A compilation of two researchers’ selection results was strictly checked one by one, and the consistency reached 92%. Then, a third researcher (Jinqi Mao) determined the inconsistent selection results. Finally, Prof. Delu Wang checked the whole literature database for the authority.

4 To ensure the reliability of the coding results, two researchers (Yadong Wang and Lan Yu) coded the selected literature independently in the coding stage, and then, a third (independent) researcher (Jinqi Mao) checked and compared the coding results of the two groups. For inconsistently coded information, a consensus was reached through backtracking and discussion.

5 CIFs with frequency equal to 1 were not included in the statistical analysis due to the applicable conditions for meta-analysis.

6 The square in Fig.  6 represents the ES of the study, and the confidence intervals can be used to measure the accuracy. The narrower the confidence interval, the higher the accuracy. The last one was a diamond, which represents SES.

7 In Fig.  13 , the red diamonds represent the original SES in the meta-analysis, and the dots in other colors represent the changed SES after deleting one study that it represented.

8 Out of 67 studies, 27 focused on the technology innovation of RE, 16 on renewable energy production, 13 on renewable energy investment, and the remaining 11 studies discussed the renewable consumption.

Publisher's note

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• Open access
• Published: 23 February 2021

A critical review of the integration of renewable energy sources with various technologies

• Erdiwansyah   ORCID: orcid.org/0000-0001-8887-8755 1 , 2 ,
• Mahidin 3 ,
• H. Husin 3 ,
• Nasaruddin 4 ,
• M. Zaki 3 &
• Muhibbuddin 5  

Protection and Control of Modern Power Systems volume  6 , Article number:  3 ( 2021 ) Cite this article

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Wind power, solar power and water power are technologies that can be used as the main sources of renewable energy so that the target of decarbonisation in the energy sector can be achieved. However, when compared with conventional power plants, they have a significant difference. The share of renewable energy has made a difference and posed various challenges, especially in the power generation system. The reliability of the power system can achieve the decarbonization target but this objective often collides with several challenges and failures, such that they make achievement of the target very vulnerable, Even so, the challenges and technological solutions are still very rarely discussed in the literature. This study carried out specific investigations on various technological solutions and challenges, especially in the power system domain. The results of the review of the solution matrix and the interrelated technological challenges are the most important parts to be developed in the future. Developing a matrix with various renewable technology solutions can help solve RE challenges. The potential of the developed technological solutions is expected to be able to help and prioritize them especially cost-effective energy. In addition, technology solutions that are identified in groups can help reduce certain challenges. The categories developed in this study are used to assist in determining the specific needs and increasing transparency of the renewable energy integration process in the future.

1 Introduction

Decentralization in the electricity sector is a major step in the spread of renewable energy sources that can reduce dependence on fossil fuels [ 56 ]. Global growth of photovoltaics (PV) and wind power in recent years has been 4% and 7%, respectively. The average increase over the past 5 years reached 27% PV and 13% wind [ 37 , 80 , 109 , 116 ]. Variable renewable energy (VRE) has differences, in various ways, from conventional generation. There are six main characteristics of VRE generator output, such as: the main resource has variable, small and modular VRE generators, which are different from conventional generators and are non-synchronous and an unpredictable type of VRE, although there may be low costs in the short-term [ 5 , 50 , 59 ]. These characteristics can create various challenges to the existing power system. In this case, power system performance characteristics can be affected because of some predefined challenges, e.g. the capacity for transmission line loss or inadequate generation. In addition, the inability of portfolio generation available for matching the demand for power to the needs at any time [ 11 , 31 , 39 , 40 , 63 , 88 , 113 , 129 ].

Existing energy technologies can be used to overcome these challenges. In this case, modification technology and renewable technology can reduce some of the effects, such as the expansion of transmission networks and centralized or distributed storage devices. Integration of VREs connected to power systems requires technological solutions to achieve the decarbonization target. However, the application of a technology can cause complications caused by three main factors. First, technology choices include the implicit or explicit application of the costs, and the maturity and technological preferences of policymakers as well as companies [ 46 , 90 , 95 , 115 ]. Second, the decision on a specific solution technology is not via a single entity but rather several actors, such as utilities, system operators and regulators [ 57 , 66 , 94 , 124 ]. Finally, designated technologies vary by region including the VRE share of generator portfolios or individual power configurations for interconnected island systems [ 21 , 69 , 82 ].

From the opinions of several practitioners and researchers on energy transition, we can say that there is not enough transparency on the scope of the technologies to overcome these challenges [ 53 , 60 , 75 ]. The individual analysis offered by some proposes specific technologies, e.g. voltage management solutions for networks distributed through VRE penetration [ 70 , 77 , 98 , 131 ]. However, there are several technologies presented in this paper that have the potential to overcome broader challenges such as battery storage. In addition, scenarios for investigating the deployment of specific technologies to increase storage and transmission capacity have also been discussed [ 33 , 49 , 101 ]. However, from several studies, the substitution effects of different technology solutions are very rarely considered. Other studies focus only on some aggregate challenges, especially the challenges of flexibility [ 10 , 74 , 81 , 84 , 110 , 118 ]. However, challenges are defined at an aggregate level such that they do not necessarily lead to a particular solution technology. While some technology solutions and individual challenges might be known, some of the available literature does not provide a transparent picture. It is very important that decision-makers and researchers alike are aware of these factors when considering energy transition. When so informed, they will be better able to determine the road map and strategy on technology for the development of power system plants.

Renewable energy technology is widely covered in the literature and clearly various challenges still exist. The review carried out in this study aims to map the challenges of VRE by describing what technology solutions are appropriate to overcome these challenges. The approach taken in this paper is the analysis of data from the literature used to compile and map the list of technology solutions and challenges based on their interrelations, and to identify any lack of consistency and classify challenges to VRE. This approach aims to distinguish the observed symptoms, e.g. performance characteristics that change. Furthermore, this analysis is complemented with information from several experts to strengthen and ensure more accurate results. The findings on challenges and their linkages to technology solutions are also discussed. The relevant implications for policymakers and companies are presented in the next section. The main contribution of this review is to provide up-to-date information and useful knowledge in the deployment of RET so that energy access across the country can be improved. The systemic approach within an RE framework for information on important components of the RE ecosystem is a feature of this article.

The outline of this paper is as follows. Part one is an overview. Part two describes the materials and methods used. Part three gives the results and discusses the review and analysis regarding RET. Part three presents the findings and solutions of RET in detail. The final part is the conclusion.

2 Materials and methodology

2.1 collecting challenges and technology solutions.

Analysis of the challenges and technological solutions contained in this study were collected from literature published in journals, conferences and from some institutions in the English language. The samples analysed in this paper were mostly collected from internationally recognized journals and sources from established publishers such as Elsevier (Science Direct), Springer, Wiley, etc. [ 13 , 38 , 117 ] and from various online websites published by several official government and private institutions and research institutions. The journals analysed and reviewed in this paper contained 132 articles deemed relevant to technological challenges and solutions, especially for renewable energy.

The literature review conducted in this paper is divided into several categories to map various technological challenges and solutions comprehensively. The first category reviewed related to challenges and technological solutions from a systemic viewpoint, looking at the differences between systematic studies that focus specifically on technological solutions and challenges as well as other foci relating to VRE in an integrated manner in certain areas such as islands or villages. Reviews relating to market share issues or regulations are set in perspective from a technological or operational solution integrated directly with VRE. The final category analysed is the basis for extracting technological solutions and challenges. Studies relating to perspective technology and operations are used to eliminate ambiguity for the identification of challenges. This is due to dependence on fundamental technical phenomena. Various sequential effects in increasing the yield of VRE penetration have been reported in several studies [ 35 , 71 , 97 , 120 ]. This is done because it does not have the marginal cost that is important to the challenges of integrating renewable energy. However, the ambiguity of challenge that is defined on the economic perspective has a lower spot price so that it is following the wishes of the community in perspective. To define various technical challenges including generation, it is inadequate to adjust ambiguity because it has potential effects that are not desired by stakeholders. For example, the selection of problems, in particular, is not an institutional or organizational challenge. As such, it is very easy to overlook storage from a technical point of view. Organizations or institutions that have changed are in fact steps for technical reconfiguration. In addition, it can increase more than one market share for technology solutions to power systems.

Integration of challenges and technological solutions collected and analysed from a variety of literature is a function as well as interview input for further research processes. This challenge is not tangible, in this case, the description and the words conveyed have differences. First, the challenges are collected in a long form, then iteratively collected and repeated. The technological solutions collected are determined with two requirements, first; independently this technology must be able to mitigate one another and automatically the challenges are integrated directly into VRE. Such requirements are very necessary to prevent the grouping of sub-technologies used as technological solutions. One example of sub-technology is Smart Meter, which is very possible to respond to requests as needed. However, it cannot independently reduce challenges that are integrated directly with VRE. Therefore, it is important to classify responses to requests for technological solutions, however, not for Smart Meters. As for the second category, it is done to define technology solutions based on their respective functions as explained by [ 16 , 76 , 93 ]. Thus, the exclusion of technological solutions can gradually be helped by the differences between one another. Given the example of the request-response, the main function of this technology is to reduce power at certain times and devices. However, response requests are operated on different devices, for example, electric heaters and heat pumps so that different technological solutions cannot serve similar functions. This study develops the challenges and technological solutions based on the various literature reviewed. The identification of all interrelated technological solutions is described with specific challenges.

The list of challenges as explained earlier will be refined with literature and reviews relating to challenges according to their level and challenges related to overall causality (Table 1 ). The relationship between the challenges and the technological solutions analysed shows that the two are mutually exclusive. Therefore, the analysis methodology applied in this study aims to find out the causes, management tools and the standard tools. Besides, the purpose of applying this method is to identify the main causes of certain problems and events as the root causes [ 14 , 36 , 112 ]. Categories with failure modes on micro-networks that can be used to find various errors and resolutions are found in the method [ 34 , 48 , 52 ]. The method is applied to identify the increasing symptoms of penetration of VRE collected from various literature. The symptoms analysed represent various effects that have adverse effects on performance characteristics for the power system. The identification of challenges found in the literature is then mapped based on the symptoms of each specific VRE characteristic that is the root of the problem.

3 Result and discussion

3.1 defiance.

There are eight categories of problems in increasing VRE penetration found in some of the literature as shown in Table 2 . Furthermore, the problems that have been identified were divided into four main categories as requirements for basic performance for power systems. The dominant performance requirement for end consumers is one of sufficient power quality. This power quality consists of a continuous and uninterruptible power supply with a steady-state of voltage and current. In addition, if there is an instant matching, it is better to stay awake and safe. The basic category of VRE can be responsible for power quality challenges that include the modularity of the VRE generator and the fact of dissonance. Furthermore, the flow was categorized as transmission and distributed power efficiency. Multiple stream categories were the cause of the challenge compared to the other categories. Modularity, location constraints and VRE were the biggest part of the flow of challenges. The frequency of controls and challenges was categorized as stability to the power system to restore the system after a blackout. The cause of the stability of this challenge was due to the modularity of the VRE generator and the synchronization of the generator. The relationship between the challenges with the balance of supply and demand for active power in the short and long term of the system was categorized into power balance. This included a wider coordination system of speed capacity in the power system to the generator and ramp to a minimum. The main cause of the challenges was the uncertainty and variability of VRE. The main problem from the results of the analysis has given a bottom-up challenge category that was consistent by adjusting the problems contained in the power system to increase VRE penetration. A detailed review of the interrelated challenges between VRE characteristics and challenges is the basis of the review in this paper.

The results of the analysis of the main problems contained in an electricity network problem that includes a mismatch of demand and electricity supply are shown in Fig.  1 . Schematic description of the analysed problem was categorized into five chains, i.e. the causal effects of different VRE characteristics. Further analysis was carried out to ascertain the level of detail of each so that the problem can be resolved as quickly as possible before the selection of challenges interrelation analysis. Demand and supply that do not have in common certainly have a variety of different reasons besides increasing VRE penetration. For example, delivery limitation from nuclear power plants and coal is one of the reasons because the power system is less flexible [ 74 ]. However, the main focus of this paper discusses the challenges and integrated technological solutions and causes of the connection to the increased VRE penetration. The main problems analysed are eight causes caused by the increased VRE penetration as summarized in Fig. 1 . A list of the challenges that has been summarized includes descriptions and categories of each as well as the symptoms observed and references as shown in Table  3 . Twenty six challenges have been identified as a whole and most of them are challenges related to power system stability and power flow.

Analysing the root cause to balance challenges

3.2 Technologies of Solutions

Categorical and technological solutions and challenges are generally not specifically available in the literature. This is because most categories are implicit and have differences in the focus of each research. The study of power systems are flexible such as technology that can consume and produce power actively [ 25 , 97 ]. Meanwhile, research on electricity networks tends to focus on technology for power distribution and transmission only ([ 99 , 100 ]. Technology solutions that are comprehensively registered are not included in the technology identification as reported in the study [ 63 ]. Categorization of technology solutions is determined such as transformation in the energy sector and conclusions with a higher level. Research on top-line classification using two characteristics assigned to technological solutions has been reported by [ 54 ]. Transformations in the energy sector that lead to distributed or centralized systems are characteristics as reflected in the literature [ 19 , 22 , 26 ]. Therefore, the difference between distributed and centralized technology solutions can be used at a higher or lower level of system challenge. Technology with one side of generation and transmitted technology that is distributed with the other side can be categorized into the second as reported in several kinds of literature. Technology flexibility can be classified as technological solutions such as technology that contributes to system flexibility producing or consuming active power or better known as grid technology that is also classified as a technological solution. The characteristics of technological solutions can be divided into four groups through two assignments. The group which is categorized as two assignments includes a description, e.g. potential applications and solutions for each technology solution as shown in Table  4 . Twenty one technology solutions have been identified; 10 of which are distributed technology solutions, while the remaining 11 technological solutions are centralized. Besides, 21 technological solutions are also distinguished from the flexibility and grid technology systems. Whereas, there are 8 flexibility technologies and 13 grid technologies.

Grid technology is considered more attractive than flexibility technology because grid technology can serve both centralized and distributed systems. An estimation solution in a grid distribution system can estimate or measure a particular grid area. While responding to requests to serve multiple applications can be done with technology flexibility. Centrally distributed and distributed technology systems are very similar when they were first seen. However, more closely, the design between the two shows the difference. Where the ability to serve the application is distinguished from the operator and the owner himself. This difference is illustrated in the case of a stored and distributed system. On the other hand, storage with a distributed system is generally a battery unit installed at the household level with a closed state. Optimized independent consumption of these units is generally found in households, e.g. end consumers or stand-alone. While centralized storage systems such as water pump storage units or batteries are connected. The purpose of this application is for a short period during peak periods or to maintain the system’s power stability. Whereas centralized distributed storage is generally found in the operator or utility system.

3.3 Interrelationships between solutions to challenges

After completing the identification of technological solutions and challenges for integrated VRE, an analysis was carried to overcome the challenges as shown in Table  5 . Challenges contained in the scope of solutions can ignore the number of technological solutions so that defined challenges can be addressed. Successful solution spaces are identified as illustrated in Table  6 . Where the potential solutions contained in technological solutions that refer to several challenges can be addressed as quickly as possible. Because the space and potential of qualitative solutions are numerical comparisons and very limited to be used. Observation matrices made from the perspective of solutions such as high potential solutions and overall challenges are technological flexibility. VRE generators and distributed conventional generators that have a high level of potential solutions are included in the flexibility technology group, for example, large conventional generators with low potential solutions and conventional generation. Furthermore, distributed technological solutions tend to be higher compared to centralized systems. However, distributed grid technology has special exceptions especially for limiter or harmonic filter devices. Finally, the unique value that grid technology has on specific challenges include direct current control systems that have high voltage (HVDC) and power flow that can accurately solve problems such as long transmission distances. However, these challenges can generally be addressed by utilizing flexible technology.

Contributions made by the solution technology to solve the challenges are described in Tables  5 and 6 . Challenges that are local and site-specific have a narrower scope because the solution can only be done by the distributed solution technology, modified distributed VRE generators or additional technology solutions, e.g. harmonic filter. The whole technology group can solve various flow challenges, except technology-centred flexibility that has limitations in solving flow problems. The difference in solution space is included in the category of flow challenges starting from a narrow space to a wider space. The challenge of stability can be solved by a system technology solution by controlling at the system level centrally. Thus, the challenges of flow and distributed technology networks cannot solve challenges to stability, unless the system level can be aggregated. Stability categories such as challenges have wider solution space; however, systems in control interactions cannot be improved. To be able to balance, challenges can only be done by flexibility technology so that existing challenges can be tailored to the needs and active power consumption, excerpt for the increase in the more important VRE estimates. In general, the challenges in the balance category have a wider solution space than the availability of generations in the long run.

Three insights are very important in integrating VRE and decarbonization for the energy sector. The first process discusses two insights for overcoming integrated VRE challenges, e.g. a different power system. The last insight illustrates the results of research that can improve policymaking in the energy sector transition. Solution space for different challenges is the first point, while earlier observations are made for several types of technology that can solve specific challenges. However, the intuitive analysis of the results of expert interviews shows that business people and policymakers are not very familiar with the technological solutions that can be used to solve certain challenges. It is very clear that this technology falls into different categories. However, the development of different solution technologies can reduce the economic viability of a single technology and diminish market potential. Contributions in the decline in market price levels have a relationship with the things mentioned above. This is the same as the balancing power market in Germany. In this case, storage institutional frameworks, increasing VRE forecasts, changing demand responses simultaneously can significantly reduce market prices [ 43 , 51 , 87 ].

An illustration of the balance and challenges of stability can be used further as an example. The results of the interviews with experts clearly show that each different technology category can function as technology e.g. request responses available only focus on a centralized solution. Therefore, large scale and conventional generation are competitive technologies. However, the distribution of technological flexibility is not focused on analysing the more competitive technological landscape. This can be said as a prominent relationship to the potential influence of grid technology on technology flexibility, e.g. VRE estimates that increase significantly. This is because the size of the market is reduced to the demand response and storage technology. Technology like this, in general, can be used as a counterweight to a certain size of the market by looking at the quality of market participants. Lack of knowledge of technology and its groups is the main reason since competitive technology can be used for decision-making information for processes in a smoother energy transition.

The distribution of solution technology portfolios in each region for VRE integration contained in the literature seems to be very generic. Thus, the guidance given to companies and policymakers always fails to develop business policies and strategies. For future decision making, it can be assisted through an interrelation matrix such as preparing proposals and technology roadmaps both nationally and internationally. This aims to be able to decarbonize the energy sector. Interrelation material functions to match each category as well as some of the history of each country. Every quality challenge has occurred regionally for high distributed VRE penetration so that the spread of flexibility is needed especially distributed technology networks. Countries with a high penetration of VRE generators are southern England, southern and northern Italy and southern Germany [ 109 ]. Although the availability of data spread flexibility is not available for distributed technology networks in certain regions, projects such as the RD&D smart grid are technologies with very high priority for policymakers and companies in these countries [ 24 , 28 , 78 ]. The challenge of flow for the transmission rate reached by countries such as Germany, in general, requires a technology system with a centralized network. Such systems, such as transmission networks or amplifications, must be expanded, active power control and HVDC transmission systems. Germany is currently preparing several large projects that can be utilized by using technology. This is done after the assessment phase in determining the design and size of the complex installation has been completed.

Countries such as Ireland and Spain have done similar things, both of which have faced stability challenges. On the other hand, the transmission operator system is set as the centralized controller of the VRE generator. It aims to the needs of VRE generators to support network stability [ 3 , 102 , 108 ]. Besides, the investigation was carried out to ease the limitation of the stability criteria. Finally, solving the challenge of balance can only be done through technology flexibility. California, for example, is a country that have difficulty of being able to maintain power balance when the sun changes night so that the VRE generation has decreased significantly [ 32 ]. To encourage investment in storage with more flexible generators and environmentally friendly renewable energy, the State of California has introduced several new products [ 2 , 29 , 30 ]. Thus, interrelation matrix can be concluded that its function can be carried out by business people and those who make policies in identifying solutions technology groups. Finally, the challenges that are prevalent in certain areas can be reduced and the formulation of steps and policy strategies in supporting the dissemination of technology can be easily carried out.

Frequent debates between actors to prioritize technological solutions in VRE and irrigation management in the energy sector have often been carried out. Priority for technology solutions in integrating VRE with costs and ease of implementation is reported by several researchers ([ 21 , 35 , 99 , 100 ]. This perspective has short-term benefits, also, the potential solutions that are perpetuated from this perspective are differences in facing challenges. Technology solutions are prioritized based on their respective solutions so that technology flexibility can be used as a solution to the challenges of VRE. This is as stated by experts in supporting the potential of technological flexibility ([ 99 , 100 , 126 ]). The results of the analysis can support the call for decision-makers adjusted to market rules or the placement of newly applied policies. Remuneration schemes for reactive power are introduced in the regional market. However, technology ratings are determined solely based on their respective potential and do not take into account other technological solutions that contribute to solving challenges. Besides, the solution space is different among all challenges. To consider these factors, the ranking of technologies can be adjusted to their potential in solving challenges. The preference for the deployment of this flexibility technology is specifically found in distributed and centralized VRE. Protection strategies with appropriate equipment can solve specific challenges, and higher interests can be achieved by the following perspectives. Response to requests both small and large is part of the technology solution. In addition, there are large generators with lower priority because of the limitations of the potential for more unique solutions. Relevantly to distinguish VRE integration, there are two examples large, small demand response spreads and large flexible conventional generators. Cost savings from existing solutions can be realized in the short term. However, it is not enough to only deal with the scope of the existing challenges or potential. The aspects discussed can be assumed to confirm the benefits of the results of the analysis for policymakers as a whole.

The results of the analysis carried out have important limitations to be considered when interpreting the final results. A review of specific research on existing challenges can improve VRE penetration. However, additional challenges which are not listed in this study can also face challenges such as the electric power system. At the same time, analysis of challenges was also found in power systems with lower VRE penetration. Specifically, the analysis conducted in this study is a challenge that is directly related to technology solutions. This analysis does not measure one technology solution that can solve only certain challenges. In addition, the future developments beyond the scope of this analysis can be reduced, e.g. the emergence of new solution technologies that can change frequency stability criteria or more robust end-user equipment such as variable frequency drives. Furthermore, the specific costs of the solution technology, the urgency of the challenges or the feasibility of implementing the solution technology are not considered. This is due to environmental constraints such as high land, social areas such as the public for receiving the final transmission line. This quantification is adapted to specific contexts with differences in power system characteristics. Furthermore, high levels of uncertainty are more vulnerable when considered such as revenue and costs than differences in applications and technology solutions. This need is needed for the need to think in grouping portfolios or technologies that focus on the completion of integrated VRE.

4 Conclusion

Specifically, the review in this research is to study the integration of VRE systems that are connected with modern power systems and technology to overcome challenges. Besides, the need for power system technology in increasing VRE market share with complex integration is also discussed. The collection of challenges undertaken in this study was drawn from a variety of literature relating to technology solutions in integrating VRE. The challenges developed can consistently integrate VRE which is the root problem of this analysis. The results of this analysis are supplemented by data from interviews of experts who have helped in investigations related to technology solutions and their challenges.

The results of the analysis with some insights outlined in the study can be summarized as follows

VRE integrated with challenges can affect the characteristics of the power system.

Technology solutions that vary with the number of challenges can be significantly overcome. In general, technology flexibility has a higher solution potential than the use of grid technology.

The identified technological solution facilities are intended to be able to overcome challenges in several categories.

Identification of challenges from various practice literature can be arranged and collected based on the root of the problem to produce each of the more exclusive challenge categories.

Categories and collections of technology solutions are used to test challenges that can be overcome by a single technology.

The size of potential solutions becomes very important for companies or policymakers in promoting certain technologies and their respective solutions.

Some of the descriptions presented in this review are a starting point for future research related to this topic. The relationship between technology solutions and challenges is one of the new fields of research. This is done with an estimated cost compared to the use of different solution technologies and can be introduced comparatively to the environment as a whole. Life Cycle Assessment (LCA) can be used to measure costs integrated with VRE because the installed capacity with future projections is available [ 41 , 107 , 114 , 125 ]. This system can significantly improve recommendations on policies issued. Overall, the development of individual solutions technology that is integrated with VRE is an issue that has a high price for the transition in the energy sector in a sustainable manner. In this case, a further investigation between the characteristics of different power systems and geographies is on one side of the technology solutions and challenges with different sides.

5 Nomenclature

VRE Variable Renewable energy

HVDC High-Voltage Direct Current

RE Renewable Energy

LCA Life Cycle Assessment

RET Renewable Energy Technology

PV Photovoltaics

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Acknowledgements

This research supported by PNBP Universitas Syiah Kuala, Research Institutions and Community Service.

About the authors

Erdiwansyah: Born in Desa Meunafa Kec. Salang, Kab. Simeulue Aceh Province at 14 March 1984. Erdiwansyah is a lecturer at the Faculty of Engineering, University Serambi Mekkah, and Banda Aceh, Indonesia since 2014 until now. In 2020 this was registered as a PhD of Engineering Student at Universitas Syiah Kuala. The Master’s degree was pursued at the Department of Electrical Engineering at Universitas Syiah Kuala, Banda Aceh, Indonesia, completed in 2016. Furthermore, the bachelor’s degree was obtained in August 2012 from the Faculty of Engineering Department, Universitas Serambi Mekkah Banda Aceh. Currently, besides studying, he also helps research professors at Universitas Syiah Kuala, Banda Aceh.

Mahidin: Born in T. Gajah Kec. Tnh. Jambo Aye at 3 April 1970, the eldest one out of 6 siblings. Finished the elementary school in SDN Lhokbeuringen T. Gajah at 1982, Junior High School at SMPN 1 and Senior High School at SMAN 1 Panton Labu, Kec. Tnh. Jambo Aye, North Aceh, in 1985 and 1988, respectively. Moreover, undergraduate degree was earn at August 1994 from Department of Chemical Engineering, Syiah Kuala University. Magister degree was pursued at Department of Chemical Engineering, ITB in October 1999, and received Doctor of Engineering in Resource and Energy Science from Graduate School of Science and Technology, Kobe University in September 2003. He was awarded a professor in chemical engineering in 2018. Fields of research are treatment and utilization of energy resources, especially renewable energy resources and mix of energy (energy diversification).

Husni Husin Ph. D, is a Professor of Chemical Reaction Engineering at Syiah Kuala University. She joined Chemical Engineering Department since December 1994; Born: 1965, Samalanga, Aceh, Indonesia; Education: Syiah Kuala University (1990); Institute Technology Bandung (2000); National Taiwan University Science and Technology (NTUST) Taiwan (2011); The title of her dissertation is “Fabrication of La-doped NaTaO3 via H2O2 Assisted Sol-gel Route and Their Photocatalytic Activity for Hydrogen Production”; Her research interests are: Nanomaterial for Clean Energy production (Photocatalytic, Solar cell, Biodiesel, Biofuel, Fuel Cell), Heterogeneous Catalyst and Application, Adsorbent and Application;

Nasaruddin received the B.Eng. degree in Electrical Engineering from Sepuluh Nopember Institute of Technology, Surabaya, Indonesia in 1997. Then he received M. Eng and D. Eng in Physical Electronics and Informatics, Graduate School of Engineering, Osaka City University, Japan, in 2006 and 2009, respectively. He is a lecturer at Electrical Engineering Department, Syiah Kuala University. He was head of master of Electrical Engineering Programme; graduate school of Syiah Kuala University. Currently, he is head of Electrical and Computer Engineering Department, Faculty of Engineering, Syiah Kuala University. He has published several papers in international journals and accredited national journals. His research interests include digital communications, information theory, optical communications and ICT applications for disaster. He is a member of IEEE and IAES.

Dr. Ir. Muhammad Zaki, M. Sc is a lecturer and researcher in Chemical Engineering Department, Faculty of Engineering, Unsyiah since 1992. Received a Bachelor degree (Ir) in Chemical Engineering Department of Unsyiah, then continued S2 (M.Sc) and S3 (Dr.) at Universiti Kebangsaan Malaysia in Chemical and Process Engineering Department.

Muhibbuddin I completed my Ph. D in Technical and Vocational in Mechanical Engineering from The State University of Padang, Indonesia, in 2016 under the supervision of Prof. Dr. Nizwardi Jalinus and finished Master of Engineering degree in Mechanical Engineering Joint Programme between Gadjah Mada University and Bandung Technology Institute, in 2012. Since 2007 worked as Traineer Machining at Sandvik Light Industrial Park PT. Freeport Indonesia Tembagapura Papua Indonesia and resigned in 2008 for graduating as civil servant. Since college, I have been interested in Energy Conversion Machines especially water turbines, windmills and applied engineering. Besides studying, I am also active in Laboratory and Micro Hydro Power Plants Development Centers and research final project Bachelor; “Design and Manufacture of Transmission System a Portable Propeller Water Turbine 4 kW Capacity for Micro Hydro Power Plants”. The Master of Engineering focuses on the research; “Study of Utilization of Bamboo Parts as Blades of Pelton Water Turbine for Enhancing Rural Energy Technology to Support the Energy Independent Village Program”. Doctoral Research; “The development of Cooperative Project-Based Learning (CPBL) models for Energy Conversion Machines in Technical Vocational Education and Training in Mechanical Engineering”. I served as Head of Devision Human Resources Teacher and Education Personnel (Echelon III) Southwest Aceh Regency Education and Culture Office from 2018 to 2019. Since October 1, 2019 until now I am joined as a lecturer in Mechanical and Industrial Engineering, Faculty of Engineering, Syiah Kuala University, Banda Aceh.

The funding of this research is the grand research of the professor with the contract number of (32/UN11.2.1/PT.01.03/PNBP/2020).

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Doctoral Program, School of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia

Erdiwansyah

Faculty of Engineering, Universitas Serambi Mekkah, Banda Aceh, 23245, Indonesia

Department of Chemical Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia

Mahidin, H. Husin & M. Zaki

Department of Electrical and Computer Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia

Department of Mechanical and Industrial Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia

Muhibbuddin

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1. Erdiwansyah: The first author acts as the author of all article content and data collection such as literature searches and other data that support this research. 2. Mahidin: The second author acts as the draft writer of the article and also as a review for the refinement of the article before it is sent to this journal. 3. H. Husin: The third author acts as a controller of the writing done by the first author. In addition, the third author is also tasked with analyzing the literature data collected and written by the first author. 4. Nasaruddin: The fourth author acts as a drafter and design of articles written by the first author. In addition, the fourth author is also a policy maker for this article and serves as the final review and editing of this journal. 5. M. Zaki: The fourth author acts as a contributor to research funding in addition to funding from the grand research. The fourth author also acts as analysis and refinement of the final article. 6. Muhibbuddin: This sixth author acts as a fund contributor for checking language and words and sentences for English language experts. The sixth author has also helped to revise the end of the journal jointly with all the authors in this article. The author(s) read and approved the final manuscript.

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Erdiwansyah, Mahidin, Husin, H. et al. A critical review of the integration of renewable energy sources with various technologies. Prot Control Mod Power Syst 6 , 3 (2021). https://doi.org/10.1186/s41601-021-00181-3

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Received : 13 July 2020

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Published : 23 February 2021

DOI : https://doi.org/10.1186/s41601-021-00181-3

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ORIGINAL RESEARCH article

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Unearthing Potential: Exploring the Frontier of Underground Hydrogen Storage

D R A F T Development and calibration of a bio-geo-reactive transport model for UHS Provisionally Accepted

• 1 Clausthal University of Technology, Germany

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The increased share of renewable energy sources will lead to large fluctuations in energy availability and increases energy storage's significance. Large-scale hydrogen storage in the subsurface may become a vital element of a future sustainable energy system because stored hydrogen becomes an energy carrier available on demand. Large hydrogen amounts can be stored in porous formations such as former gas fields or gas storages, while caverns can contribute with high deliverability. However, the storage of hydrogen induces unique processes in fluid-fluid and rock-fluid interactions (for example, bio-and geochemical reactions), which may affect the efficiency of the storage.In the present study, a mathematical model describing the two-phase multicomponent flow in porous media, including bio-and geochemical reactions, is developed to predict these hydrogen-related processes. The proposed model extends an existing model in the open source simulator DuMu x describing the bio-reactive transport process considering methanation and sulfate-reduction by geochemical reactions. Significant attention is placed on the reduction from pyrite-to-pyrrhotite coming with the generation of harmful hydrogen sulfide. This reaction is calibrated by developing a kinetic model in DuMu x that mimics the observations of reactor experiments from literature. The developed and calibrated model is afterwards used for simulation runs on field scale to assess the impact on Underground Hydrogen Storage (UHS) operations.The developed kinetic model describes the reduction from pyrite-to-pyrrhotite in agreement with the observations in the literature, whereby particular focus was placed on the hydrogen sulfide production rate. The consecutive implementation of the transport model in DuMu x on field scale, including the bio-and geochemical reactions, shows the potential permanent hydrogen losses caused by reactions and temporary ones induced by gas-gas mixing with the initial and cushion gas.

Keywords: Underground hydrogen storage, Underground energy storage, Reservoir Simulation, DuMu x, Bio-Geo-Reactive Transport, mathematical modeling, Porous media

Received: 12 Feb 2024; Accepted: 15 Apr 2024.

Copyright: © 2024 Hogeweg, Hagemann, Bobrov and Ganzer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Sebastian Hogeweg, Clausthal University of Technology, Clausthal-Zellerfeld, Germany

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Addressing the Environmental Kuznets Curve in the West African Countries: Exploring the Roles of FDI, Corruption, and Renewable Energy

• Published: 15 April 2024

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• Lobna Abid 1 , 3 ,
• Sana Kacem 1 , 4 &
• Haifa Saadaoui 2  

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Environmental degradation and economic growth are two intricately related issues whose impact is in constant increase within a global context marked by climate risks and corruption, notably in certain African countries. This research work examines the impacts of economic growth, corruption, renewable energy, and foreign direct investment on carbon dioxide emissions for a set of West African economies between 1990 and 2020. The current paper uses the PMG-ARDL panel method in order to assess the relationships between the various variables invested. The results are indicative of the long-term effects of variables. These findings demonstrate that GDP per capita has a positive and significant effect on CO2 emissions, and that the Kuznet curve is not validated in this case. Moreover, FDI confirms the pollution heaven hypothesis as it reduces environmental quality in the long run. In contrast, renewable energy consumption and control corruption in West African countries constitute significant factors in the fight for environmental quality. The causality outcomes reveal that there exist one way of unidirectional link between CO2 to both income and corruption, and a one direction causality from FDI to CO2 emissions. Meanwhile, the link between renewable energy and CO2 emissions is neutral. In this respect, this research offers outstanding findings to help maintain influential procedures for environmental sustainability within the West African framework.

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Abid, L., Kacem, S. & Saadaoui, H. Addressing the Environmental Kuznets Curve in the West African Countries: Exploring the Roles of FDI, Corruption, and Renewable Energy. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-01858-4

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A review on the passivation engineering in improving the photocatalytic hydrogen evolution performance.

Photocatalytic hydrogen evolution (PHE) is a promising way to the energy renewable and eco-friendly development of future society, but the low activity and durability of photocatalysts seriously restrict the development of this technology. Passivation engineering may provide a feasible idea to solve these problems, by which a relatively stable and mild environment can be formed to guarantee the high separation and utilization of photogenerated charge carriers. Recently, passivation engineering has been more and more adopted in improving the activity and durability of photocatalysts, so a comprehensive review will help researchers understand and use this technology to construct high-performance photocatalytic system. Herein, the basic concept and the roles of passivation technique in PHE are firstly discussed. Subsequently, this review introduces the commonly utilized synthesis methods followed by the characterization means in the passivation engineering. After then, we review the categories and mechanism of passivation engineering in PHE. Lastly, the challenges and perspectives of passivation engineering for future practical applications are discussed. We hope that this review can provide some useful guidance and excite the interest over passivation engineering in constructing high-performance photocatalysts.

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European Solar Charter

The European Solar Charter, signed on 15 April 2024, sets out a series of voluntary actions to be undertaken to support the EU photovoltaic sector.

Solar energy, in particular photovoltaics (PV), is currently the fastest growing renewable energy source in the EU. Last year, 56 GW of solar PV were installed in the EU, two thirds of it on rooftops, empowering consumers and protecting them from high electricity prices and reducing land use. The installations in 2022 and 2023 saved the equivalent of 15 billion cubic meters of Russian gas imports in total, mitigating the risk of disruption of gas supplies to the Union. In addition, the sector provides around 650 000 jobs, 90% of these on the deployment side, and is projected to increase until around 1 000 000 by 2030.

Achieving the 2030 EU target of at least 42.5% renewable energy by 2030, with an ambition to reach 45%, will require further acceleration in the deployment of renewable energy, including solar energy.

The bulk of the demand for solar modules in Europe is covered by imports from a single supplier, China, a concentration that creates short-term risks for the resilience of the value chain and long-term risks for price stability for solar panels due to dependencies on suppliers outside of Europe. Access to affordable solar modules from a diversity of sources as well as a resilient, sustainable and competitive European solar value chain are therefore necessary to achieve a deployment rate in line with the above targets while enhancing security of supply and mitigating the risk of supply chain disruptions.

However, the European solar module manufacturers have faced recently a particular challenge due to the combination of import dependency and a sharp drop in the prices of imported panels. In 2023, the solar photovoltaic sector in the EU and globally saw the prices of the panels plummet from circa 0.20 €/W to less than 0.12 €/W. This unsustainable situation is weakening the viability of existing European production and jeopardises planned investments for new manufacturing plants announced over the last 2 years. As a consequence, some European companies have either reduced their operations, announced that they would prioritise production in other international markets, in particular the U.S., or even announced their closure.

Over the last years, the EU has taken initiatives to strengthen its support to the European solar PV manufacturing sector, which includes several globally competitive companies in several steps of the value chain.

The European Solar PV Industry Alliance (ESIA), launched in December 2022 to reinforce the cooperation within industry, set itself the target of 30 GW of production capacity along the value chain, an objective considered achievable by 2030. The ESIA pipeline includes more than 20 projects, including several at multi-GW scale. The Net-Zero Industry Act (NZIA), on which a political agreement was reached in February, aims to ensure that the Union’s overall strategic net-zero technologies manufacturing capacity, including solar PV, approaches or reaches at least 40% of the annual deployment needs by 2030. The act includes concrete measures, such as accelerated permitting or market access facilitation through the use of non-price criteria in public procurement, renewable energy auctions and other support schemes.

However, further urgent action is needed in the short term to address the crisis in the European manufacturing industry.

All relevant stakeholders – the Commission, the Member States and the companies active along the European solar PV value chain - should ensure that the green transition and the European industrial objectives go hand in hand, accelerating the deployment of renewables while at the same time enhancing the EU’s security of supply by supporting the competitiveness of the sector and the jobs it creates in the EU.

To this end, the European Solar Charter sets out immediate actions to be taken by the Commission, EU Member States and the representatives of the solar PV value chain, in particular wholesale, distribution and manufacturing parts, to be implemented ensuring full compliance with EU competition law and state aid rules.

Actions by EU countries and industry

The undersigning Member States and solar industry representatives, respectively COMMIT to implementing as a matter of priority the following actions:

• In the framework of renewable energy auctions or other relevant support schemes, rapid early implementation of the relevant NZIA provisions through the application of, in addition to price criteria, ambitious non-price criteria, including resilience, sustainability, responsible business conduct, ‘ability to deliver”, innovation and cybersecurity criteria.
• In the framework of public procurement of solar energy products: rapid early implementation of the relevant provisions in the NZIA and in the Energy Performance of Buildings Directive through the application of, in addition to price criteria, ambitious resilience, sustainability, social, ‘ability to deliver”, innovation or cybersecurity criteria; ensure the relevant provisions in the Foreign Subsidies Regulation are fully implemented.
• The promotion of innovative forms of solar energy deployment, such as agri-PV, floating solar, infrastructure-integrated PV, vehicle-integrated PV or building-integrated PV with a specific focus on innovative business models such as turnkey projects for PV integration in buildings, including through the removal of possible regulatory and permitting barriers as well as the adaptation of existing public support schemes or the creation of specific public support schemes.
• Create favourable framework conditions for manufacturing facilities of PV products and for additional investments, with a view to supporting the achievement of the manufacturing benchmark in the NZIA, including through rapid early implementation of relevant NZIA provisions on permitting and net-zero acceleration areas, improved availability of manufacturing skills and engagement across the value chain to improve the availability of recycled materials.
• A joint commitment across the EU solar PV value chain to continuous innovation, technological excellence, responsible business conduct, cybersecurity, sustainability, diversification of supply chains, social integration.
• Consider using all available EU funding opportunities as well as flexibilities under the State aid Temporary Crisis and Transition Framework (TCTF) to provide support for new investments in the solar energy supply chain.
• Engage in the Member States Task Force under the European Solar Industry Alliance to exchange best practices on the application of non-price criteria, provide support to the industry and to strategic projects, and on the promotion of innovative forms of solar energy deployment
• Include therefore in the portfolios of the relevant market players, such as wholesalers, distributors and installers and in view of improving the competitiveness of the Union and diversification of supplies, solar PV products commensurate to the EU’s manufacturing capacity meeting high resilience, sustainability and responsible business conduct criteria. This includes custom-made and innovative solar PV products as well as products for innovative forms of deployment (such as building-integrated PV, agri- 3 PV, floating solar, infrastructure-integrated PV or vehicle-integrated PV), provide specific visibility to key qualities and origin of these products and gradually increase their volume.
• Maintain and, where possible, expand the current production capacity, in line with expected growing demand for their products, based on the public and private commitments adopted in this Charter.
• In the case of solar PV products offtakers, incorporate resilience, sustainability, responsible business conduct, ‘ability to deliver”, innovation and cybersecurity considerations in their strategies, including through cooperation with manufacturers.

Actions by the Commission

The European Commission INTENDS to:

• Further facilitate access to EU funding for solar PV manufacturing projects under the Recovery and Resilience Facility, structural funds, the Innovation Fund, the Modernisation Fund, and Horizon Europe, including through the Strategic Technologies European Platform (STEP). The Innovation Fund has selected solar PV manufacturing projects for a total of €400 million and made €1.4 billion available in its 2023 call for clean tech manufacturing, including solar PV.
• Work with the European Investment Bank to reinforce its support to investments in the solar manufacturing value chain, including through InvestEU.
• Support Member Statesin the inclusion of transparent, non-discriminatory and objective non-price criteria in renewable energy auctions, in public procurement as well as the promotion of innovative forms of solar energy deployment, including through recommendations, guidance, and the structured dialogue in the appropriate fora, including the Community of Public Buyers for Sustainable Solar PV for public procurement.
• Explore, in cooperation with Member States through the Joint European Forum the possibility of an Important Project of Common European Interest (IPCEI) to support innovations and their first industrial deployment in the solar PV manufacturing value chain.
• Continue providing support to the European Solar PV Industry Alliance in view of the achievement of its objectives, and directly engage with Member State authorities in the dedicated taskforce to share best practices on demand-side measures and support to the sector and to strategic projects.
• Continue to cooperate with third countries to enhance the resilience and diversification of supply chains via existing and future partnerships, dialogues and trade agreements and fora.
• In collaboration with Member States and social partners, facilitate the expansion of skills availability for the EU solar sector, including for manufacturing, through inter alia the Solar Academy and the Renewable Energy Skills Partnership.
• Propose forward-looking Ecodesign and Energy Labelling regulations for solar PV products to establish, on the basis of a robust methodology, appropriate environmental and energy performance standards for the sector.
• Promote the acceleration of deployment by supporting Member States in the swift implementation of the revised Renewable Energy Directive and by implementing the Grids Action Plan.
• Assess all evidence of alleged unfair practices put forward by the industry or from other independent sources.

Monitoring and review

All signatories COMMIT to monitor future developments in the sector and contribute to a fair and competitive international environment in the solar sector.

One year following the signature of the Charter, the Commission will review the implementation of the adopted commitments.

Related links

• European Solar PV Industry Alliance (ESIA)
• Net-Zero Industry Act (NZIA)

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