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The transition to low‐carbon energy and energy independence of a country play an important role in the sustainable development of its energy sector. Another important issue of sustainable energy development is the cost competitiveness in the generation process; with new renewable energy technologies, a sustainable energy transition to carbon‐neutral society is possible. In this article, we present a view of sustainable energy transformation based on a case study of Malta. We have created a simulation of a Maltese electricity system with projected growth and dominance of photovoltaic energy in the electricity market. The study results suggest that a system with a high penetration of photovoltaics has significant advantage over a conventional system using fossil fuels. In particular, in the simulated Maltese system, the total annual cost of energy was reduced threefold, the CO2 emissions were reduced by 40%, and the energy independence of Malta increased by 60%. In the end, the article gives a recommendation for further research into the Maltese energy system. [ABSTRACT FROM AUTHOR]

A global surge in socio‐economic activities is putting a massive burden on ecological balance, which has become one of the major challenges worldwide. Yet, it is complicated for national and international authorities to find eco‐friendly and interlinked socio‐economic developments due to a lack of empirical evidence. In this era of digitalization, digital financial inclusion has an ability to create a balance among economy, ecology, and society by conserving natural resources. Meanwhile, it minimizes ecological burden by promoting sustainable energy transition at all societal levels, which is the main agenda of the United Nations (UN) Climate Change 28th Conference of Parties (UN‐COP28). Focusing on these intentions, this research aims to explore the dynamic influence of digital financial inclusion (DFI), sustainable energy transition (SET), and governance (GOV) on global ecological footprints (EFT) by taking a sample of 121 nations within a timeframe of 2003–2022. This study utilizes a two‐step system generalized method of moments (GMM) and Driscoll–Kraay (D–K) regression as prime and robust empirical techniques, respectively. The outcomes reveal that DFI significantly reduces EFT worldwide and upper‐middle‐income samples; however, it significantly enhances EFT in high‐income nations. While DFI has a negative and insignificant connection with EFT in lower‐middle and low‐income countries. Moreover, SET significantly declines EFT in all categories, and mixed outcomes are found for the linkage between GOV and EFT. Some vital policy implications for ecological sustainability are also provided in this research work. [ABSTRACT FROM AUTHOR]

This study looks at China’s supportive market and regulatory frameworks for a sustainable energy transition. It examines how public and commercial sectors help shift to cleaner, more sustainable energy. We use both methods to evaluate the effectiveness of policies, legislation, and incentives in boosting green energy adoption. This inquiry also examines how governments and businesses collaborate to meet China’s ambitious energy transformation objectives. Climate change and China’s air pollution need a shift away from coal-based energy generation. The historical study shows two policy mix temporal variations: rules and instruments configurations and regulatory intensity and concentration. The strategy combination has moved from authority-based instrumentation to the current response, resulting in a lot of instrumentation and several device kinds. The Chinese government is experimenting with new rules to minimize carbon dioxide emissions while enforcing air pollution reduction and renewable energy assistance initiatives. This study explores the complicated relationship between policy frameworks and market dynamics to understand better how government-crafted strategic plans may align with market processes and capitalize on private-sector innovation and investment. Through case studies and theoretical models, it outlines each industry’s mutually beneficial role in supporting sustainable energy. New legislative tools, calibrated ones, and policies that replace and sequence all evolutionary traits are needed. The study shows that China has used a complex set of regulatory mechanisms to reduce coal-based power sector pollution and encourage renewable energy technology. [ABSTRACT FROM AUTHOR]

The global shift from conventional energy sources to sustainable alternatives has garnered significant attention, driven by the promise of economic benefits and environmental sustainability. The current study rigorously investigated the economic advantages and sustainability achieved from the transition of households in Mauritania from liquefied petroleum gas (LPG) to biogas utilization. The study constitutes a robust case study that centers on assessing the multifaceted impacts of this transition on household finances and overall quality of life in Mauritania. This case focuses on biogas technology adoption and its role as a competitor of LPG in Mauritania. The energy poverty portfolio of the nation has been explored and livestock waste generation and biogas production potential have been estimated at 2451 million cubic meters annually. Biogas production can fulfill 50% of the energy requirement for cooking purposes within the country. The community scale fixed-dome-type biogas digesters have been recommended for Mauritania by considering a community of 100 families. The calculated payback period for the community project is 74 months, and after the payback period, continuous monthly benefits of USD 1750 will be started. Livestock manure is directly utilized for farming practices in Mauritania, which produces 10.7 Gg of methane emissions per year. Biogas production is a clean and economically viable option for Mauritania, which can also be beneficial for reducing the methane emissions footprints of the livestock sector. This case study will prove as a vital project for other African nations if successfully implemented. Multiple recommendations for the policy-makers of Mauritania have also been formulated, like tariffs on biogas production facilities and swift financing schemes, which can further strengthen the biogas production on a national scale. International funders should also take part in coping with the energy demand of Mauritania and its mission to mitigate climate change rather than utilizing LPG on a national scale. Biogas production and utilization are much cheaper compared with the fluctuating prices of LPG and ensure health when cooking. [ABSTRACT FROM AUTHOR]

This study combines an investigation of Kish Island's transition to sustainable energy and transportation with a focus on the integration of hydrogen port infrastructure, employing nonlinear optimization to chart the path forward. It emphasizes the pivotal role of such infrastructure in transitioning from traditional vehicles and gas-fired power, evaluating scenarios like a 30% reduction in fossil fuels and the implementation of carbon taxes to encourage a shift to electric and hydrogen-powered vehicles. Forecasts suggest an increase in electric vehicle adoption to 46% by 2023, with a goal of complete electrification by 2042, thereby transforming the energy landscape and reducing emissions. Key to this transition is a 25% government subsidy on hydrogen vehicles to enhance market competitiveness, alongside the strategic embedding of hydrogen infrastructure within sustainable tourism zones. This approach creates a synergistic model of energy, transport, and environmental stewardship, aiming to elevate regional prosperity and sustainability. The study extends its innovative perspective to include the exploration of methanol production, the development of carbon markets, and the advancement of Carbon Capture and Storage (CCS) technology, positioning the hydrogen port as a crucial element in Kish Island's sustainable development strategy. • Study pioneers sustainable hydrogen in ports. • Novel model optimizes low-carbon transport. • Integrates green hydrogen in tourism hubs. • Enhances port's green energy transition. • Promotes economic growth through tourism. [ABSTRACT FROM AUTHOR]

The Benin energy sector faces serious challenges, including an unfavorable energy mix with regular power shortages, erratic power outages, reliance on electricity imports, and dependence on traditional cooking stoves. This study has investigated strategies critical for Benin to employ to achieve 24.6 %, 44 %, and 100 % renewable energy (RE) integration targets in the final electricity mix in 2025, 2030, and 2050, respectively. This study used the EnergyPLAN model to develop different energy scenarios suitable for Benin to achieve its proposed RE penetration target. A combination of natural gas (NG) with solar photovoltaic (PV), wind energy, hydropower, and concentrated solar power (CSP) is used to develop three scenarios for RE integration namely the government targets scenario, 2 % RE per year scenario and 50 % RE in 2050 scenario. The results show that the government targets scenario is too ambitious because of the current trend and pace of developing the energy sector. Moreover, a combination of 563 MW of NG, 125 MW of PV, 200 MW of wind, 600 MW of hydropower, and 60 MW of CSP would achieve 50 % RE by 2050 under the 50 % RE scenario. This scenario would decrease CO2 emissions by 50 % with no CEEP generation. Furthermore, the total electricity generation from MSW in Benin is estimated to be 0.232, 0.3215, and 1.16 TWh/yr in 2025, 2030, and 2050, respectively. The study's findings could help decision-makers and stakeholders make informed decisions to promote the integration of RE resources in the Benin Republic.

The global shift from conventional energy sources to sustainable alternatives has garnered significant attention, driven by the promise of economic benefits and environmental sustainability. The current study rigorously investigated the economic advantages and sustainability achieved from the transition of households in Mauritania from liquefied petroleum gas (LPG) to biogas utilization. The study constitutes a robust case study that centers on assessing the multifaceted impacts of this transition on household finances and overall quality of life in Mauritania. This case focuses on biogas technology adoption and its role as a competitor of LPG in Mauritania. The energy poverty portfolio of the nation has been explored and livestock waste generation and biogas production potential have been estimated at 2451 million cubic meters annually. Biogas production can fulfill 50% of the energy requirement for cooking purposes within the country. The community scale fixed-dome-type biogas digesters have been recommended for Mauritania by considering a community of 100 families. The calculated payback period for the community project is 74 months, and after the payback period, continuous monthly benefits of USD 1750 will be started. Livestock manure is directly utilized for farming practices in Mauritania, which produces 10.7 Gg of methane emissions per year. Biogas production is a clean and economically viable option for Mauritania, which can also be beneficial for reducing the methane emissions footprints of the livestock sector. This case study will prove as a vital project for other African nations if successfully implemented. Multiple recommendations for the policy-makers of Mauritania have also been formulated, like tariffs on biogas production facilities and swift financing schemes, which can further strengthen the biogas production on a national scale. International funders should also take part in coping with the energy demand of Mauritania and its mission to mitigate climate change rather than utilizing LPG on a national scale. Biogas production and utilization are much cheaper compared with the fluctuating prices of LPG and ensure health when cooking.

Currently, more than 90% of the electricity produced in the Kingdom of Saudi Arabia originates from fossil fuels. Under the Vision 2030 initiative, the Kingdom aims to derive 50% of its energy from renewable sources by 2030. This study presents a comprehensive evaluation and ranking of renewable energy technologies for a selection of cities across the country using an integrated methodology that combines the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The focus is on four renewable sources, namely Photovoltaic (PV), Concentrated Solar Power (CSP), Wind Energy, and Fuel Cell, each with a capacity of 10 MW. The performance of these renewable sources is assessed in five different cities of Ar'Ar, Ha'il, Riyadh, Najran, and Al Baha. The evaluation considers multiple criteria that encompass climate, environment, and social aspects, providing a holistic assessment of the alternatives. The AHP method is employed to determine the relative weights of the criteria, ensuring consistency in the pairwise comparisons. The TOPSIS method is then applied to rank the alternatives based on their performance scores. The results highlight the preferences and relative performance of the different renewable energy technologies across the considered cities. Fuel Cell technology emerges as the most favorable option in all the cities with a score higher than 0.68, demonstrating superior capacity factor (92.4%), minimal environmental impact, and reliable power generation but with a negative net present value (NPV) of − 12.22 M$. Wind Energy and CSP technologies followed in ranking, indicating their competitiveness and suitability as renewable energy options by producing in excess of 25,000 MWh/year. PV technology demonstrates competitiveness across all cities with the lowest levelized cost of electricity (LCOE) (4.33 C/kWh) and quickest payback period (12.4 years). The findings of this study provide valuable insights for decision-makers and stakeholders involved in the selection of appropriate renewable energy technologies. The rankings serve as a valuable tool in informing decision-making processes and facilitating the transition to sustainable energy systems. [ABSTRACT FROM AUTHOR]

This paper explores the vital role of green energy technologies in mitigating carbon emissions and advancing sustainable energy transition. It emphasizes the significance of green energy in reducing the carbon footprint, delves into the environmental consequences of carbon emissions, and analyzes the mechanisms through which green energy contributes to carbon reduction. This paper discusses technological advancements across various renewable energy sources, including solar, wind, hydroelectric, biomass, geothermal, tidal, wave, nuclear, osmotic, and salinity-powered energy generation. It also examines emerging green energy technologies, identifies barriers to adoption, offers an Indonesian perspective, and provides recommendations for a greener energy future. Overall, this paper offers a comprehensive exploration of green energy's transformative potential in combatting climate change and promoting sustainable development. [ABSTRACT FROM AUTHOR]

Facilitating a sustainable transition process, whether on a global or local scale, entails crafting an energy mix tailored to meet the specific needs of users. The objective is to pinpoint the most effective future strategy that optimizes both socio-economic benefits and sustainability. To tackle these challenges, a plethora of modeling tools now exists to evaluate various scenarios prior to implementation. However, it is worth noting that modeling tools are primarily geared towards economic optimization, exemplified by the open-source energy modeling system, OSeMOSYS. This paper proposes an optimization methodology encompassing economic, energetic, and environmental sustainability, introducing the most widely referenced estimator as an economic additional cost using the weight sum and monetization methodology. The ramifications of integrating these different estimators in terms of energy matrix design, costs, and emissions are thoroughly evaluated. Furthermore, the optimal selection criteria are delineated based on users’ anticipated objectives. To ensure the reproducibility of the study, we present an exercise utilizing data from Atlantis framework, which shares characteristics of both developing and developed nations. The main results indicate that implementing sustainability, despite not causing significant variations in overall costs (¡0.5%), leads to a 35% decrease in emissions. However, there is a 14.5% increase in investment costs, while residual costs rise by 6%.

Understanding the spatial variation of factors driving interest in bioenergy is important for designing effective energy policies. Although previous authors have broadly explored the determinants of biomass supply intentions in the field of bioenergy, the potential spatial variation of these factors has received limited consideration from bioenergy research. We performed a structural equation modeling based on the theory of planned behavior to investigate the impact of spatial disparities on factors determining people's intentions to supply forestry residues for clean energy. Our data were generated through a survey of 247 participants randomly sampled from two contrasting geographic regions (north and south) of the Republic of Benin. We found that spatial disparities altered the effects of attitude and knowledge of renewable energy while income and perceived behavioral control exhibited consistent positive effects across geographical regions. Our findings imply that ignoring spatial disparities when analyzing bioenergy acceptance can lead to distorted inferences. These findings can be used as a baseline information by policymakers to develop region-specific actions for achieving local transition toward clean energy in the Republic of Benin. [ABSTRACT FROM AUTHOR]

Understanding the spatial variation of factors driving interest in bioenergy is important for designing effective energy policies. Although previous authors have broadly explored the determinants of biomass supply intentions in the field of bioenergy, the potential spatial variation of these factors has received limited consideration from bioenergy research. We performed a structural equation modeling based on the theory of planned behavior to investigate the impact of spatial disparities on factors determining people’s intentions to supply forestry residues for clean energy. Our data were generated through a survey of 247 participants randomly sampled from two contrasting geographic regions (north and south) of the Republic of Benin. We found that spatial disparities altered the effects of attitude and knowledge of renewable energy while income and perceived behavioral control exhibited consistent positive effects across geographical regions. Our findings imply that ignoring spatial disparities when analyzing bioenergy acceptance can lead to distorted inferences. These findings can be used as a baseline information by policymakers to develop region-specific actions for achieving local transition toward clean energy in the Republic of Benin.

This study analyzes public perception towards the energy transition and decarbonization in Chile, and how these preferences change with political ideology, as well as distance between power plant installations and people’s homes. Due to a lack of scientific research on civil society preferences for energy production in Chile, we used a convenience sample and conducted a survey among future decision makers (current university students) to identify which factors impact their acceptance or rejection of energy sources. In addition, we asked them about their vision for the future energy mix. In total, 164 valid questionnaires were collected. Results show that the level of acceptance and preference changes with political ideology, with social liberals being more willing to change their lifestyle and increase their willingness to pay for a faster inclusion of clean technologies in the energy mix. Higher levels of education increase this willingness to pay. The level of acceptance decreases up to 56% for solar and wind when the installation is located within a radius less than 5 km from the population’s homes. The level of rejection is 97% for hydroelectricity and 99% for non-renewable power plants if they are located at distances lower than 5 km. The decentralization of energy policy decisions and the consideration of local society would be relevant for an energy transition towards renewable sources.

Sustainable energy (SE) transition and environmental quality have become a predominant part of integral policy worldwide. Besides, economic development policies at global level are being reformulated to make sure that energy supplies are reliable and have the tendency to protect environment. Although, economies are participating in activities which can help to fulfill overarching goals but developing economies specifically face challenges due to high dependency on coal consumption. The article, thereby, intends to explore the role of green financial innovation, eco-financing, carbon taxes, and economic openness on the SE transition in Vietnam. The study also checks the role of inflation and industrialization on the SE transition as control variables. The article also used Dynamic Auto-regressive Distributed Lags (DARDL) to test the connection among the variables. The outcome indicated that green financial innovation, eco-financing, carbon taxes, economic openness, inflation, and industrialization have a positive and significant linkage with the SE transition in Vietnam. These outcomes provide guidelines to policymakers in establishing new policies regarding SE transition. [ABSTRACT FROM AUTHOR]

Rural areas are essential to moving towards the necessary sustainable energy transition and climate change mitigation through renewable energy (RE) technologies. However, RE planning and decision-making in rural locations have not been developed to date with a focus on the local level and accompanied by a careful and thorough assessment of the simultaneous availability of alternative RE sources in a specific territory. Quite differently, RE investments in rural locations have been primarily driven by the interests of large power utilities to exploit a particular RE source, with benefits escaping from the rural economies to end up in the income statements of those large corporations. There is a need to approach RE planning at the municipal scale considering the availability of alternative RE sources. This study suggests the development of a rural RE potential index that could help in the identification of appropriate locations for the implementation of hybrid renewable energy systems (HRESs). The construction of a composite indicator to measure rural RE potential is exemplified through a case study that deals with ten indicators in the context of Galician rural municipalities, involving different RE potentials and some technical or regulatory constraints. Equal weighting and Principal Component Analysis are considered alternative methods for the index construction. Municipalities are the relevant local decision level where energy policy should be focused in order to diversify both the RE mix and the investor base. The proposed index could be the basis for future analyses aimed at optimizing the design and implementation of HRESs in rural environments at a local-regional-national scale.

With the increasing urgency for sustainable development and energy transition, decision-makers face complex challenges in evaluating and prioritizing viable alternatives. Traditional decision-making techniques often struggle to capture the inherent uncertainty and imprecision associated with the latest sustainable energy transition issues. This paper presents a research framework based on fuzzy set theory and the technique for order of preference by similarity to ideal solution (TOPSIS) method to address these complexities and uncertainties. Our proposed approach offers a comprehensive evaluation and ranking of alternatives for sustainable energy transition. To demonstrate the effectiveness and applicability of this system, we employ a case study in the Kingdom of Saudi Arabia (KSA). As a global leader in fossil fuel production and export, particularly oil, the KSA has recognized the need to address climate change and diversify its energy sector. By leveraging the fuzzy TOPSIS-based framework, we provide decision-makers with a powerful tool to navigate the challenges and uncertainties involved in the energy transition process. This research yields promising results, demonstrating the superior capabilities of the proposed fuzzy TOPSIS-based framework compared to traditional decision-making techniques. The case study in the KSA highlights how our approach effectively captures and addresses the uncertainties and complexities involved in sustainable energy transition decision making. Through comprehensive evaluations and rankings, decision-makers gain valuable insights into alternative solutions, facilitating informed and strategic decision-making processes. Our research contributes to sustainable energy transitions by introducing a robust decision-making framework that integrates fuzzy set theory and the TOPSIS method. Based on the fuzzy TOPSIS-based evaluation, the research findings indicate that solar energy (EA1) ranked as the most favourable alternative among the evaluated options for the sustainable energy transition in the KSA. Using our framework, stakeholders in the KSA and similar contexts can make informed decisions to accelerate their energy transition efforts and achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

• Calculation of product circularity and global warming indicators. • Evaluation of end-of-life management solutions to slow and close resource loops. • Chemical recycling has the greater circularity and low-impact potential. • Thermal recycling has the lower circularity and higher carbon footprint. • Higher circularity does not always lead to carbon savings. It is estimated that 570 Mt of blade waste, whose management is complex and expensive, will be generated by 2030 in the European Union alone. Accordingly, alternative blade waste management techniques are being investigated to optimize material recovery. This study evaluates the correlation between the circular economy performance and the carbon footprint of seven end-of-life management solutions for wind turbine blades: repurposing, grinding, solvolysis, pyrolysis, co-processing in cement kilns, incineration with energy recovery and landfilling. The circular economy performance is analyzed through the calculation of the product circularity indicator, while the carbon footprint is determined through life cycle assessment, using the global warming indicator and considering the management of three blades from cradle-to-gate as functional unit. As the performance of solvolysis and pyrolysis recycling is expected to change in the future, a sensitivity analysis is also carried out to evaluate the variability of the results by changing their process efficiency and the quality of the recovered materials. The results indicate that blade recycling through solvolysis is the most circular (0.47–0.77) and low-carbon (225–503 CO 2 eq.) solution overall. Blade repurposing, grinding and cement co-processing have a similar circularity (0.52–0.55) and a global warming impact ranging from 499 t CO 2 eq. to 615 t CO 2 eq. Although the circularity of pyrolysis is 59% (0.35) to 118% (0.48) greater than the circularity of incineration and landfilling (0.22), its carbon footprint can range from 566 t CO 2 eq. to 744 t CO 2 eq, which could be up to 19% higher than the carbon footprint of these linear EoL management alternatives (623 t CO 2). Based on these findings, proposals for sustainable industrial innovation and methodological recommendations for the development of integrated circularity and sustainability studies are proposed. [ABSTRACT FROM AUTHOR]

Poland, with its objective of switching from a fossil‐fuel base to renewable sources of energy, is a textbook example of an energy transition economy. In this review, the challenges and opportunities for local resilience were identified, followed by an in‐depth analysis of Low Carbon Economy Plans (LCEP) in the 10 largest cities of Poland. The methodology included a bibliometric analysis of the peer‐reviewed studies published from 2010 to 2022, along with K‐means clustering (empirical analysis) of the selected Polish cities. The challenges and opportunities were classified into social (S), economic (E), institutional (I), political (P), technological (T) and environmental (EN) dimensions. Institutional and political dimensions were identified as having a relatively neglected niche in low‐carbon transition research, necessitating an empirical analysis of LCEP at the city scale. Exploiting the knowledge base of traditional sustainable activities, understanding the power relations between the politics, stakeholders and industry elements, and knowledge‐based governance were found vital for creating relevant policies. Three modes of development, multi‐activity goals (MG), energy transition goals (EG), and transport goals (TG) were identified for increasing local resilience. The results illustrate the need to understand low‐carbon policies and their impacts on both energy transitions and local resilience. [ABSTRACT FROM AUTHOR]

To mitigate global climate change, drastic transformations of the energy system are needed. Whereas the public is asked to adapt its energy demand patterns, their perspective is often neglected. In this study, we incorporated a more human-centered dimension into energy research by examining how social characteristics determine the composition of individuals' preferred energy mix. Previous studies have been mainly limited to the exploration of preferences for one energy system in isolation. Hence, little is known about how various energy sources are combined into various energy mixes. Furthermore, empirical research regarding the heterogeneity of energy preferences often lacks an intersectional approach. Against this background, we used Belgian data from the European Social Survey (N = 1766) to examine the diversity of preferred energy mixes among individuals and how this relates to social characteristics. Specifically, a segmentation analysis was conducted to cluster Belgian respondents into intersectional, meaningful groups related to their preferred energy mixes. The results of the segmentation analysis underpin the existence of vulnerable and privileged groups in the establishment of a green transition. This study highlights the importance of focusing on energy mixes from an intersectional stance, as it provides an excellent tool to uncover the power dynamics underlying an energy transition. [ABSTRACT FROM AUTHOR]

The energy crisis is the foremost concern for the developing world, predominantly in European countries. The global energy demand will increase significantly by 2050, while natural resources dramatically decrease every day. However, net-zero emissions targets, climate emergency calls (1.5 °C global warming limit), smart environmental transformations, and energy transition efforts bring hope for fundamental changes in climate action globally. One of the best and most cost-effective strategies to achieve reduced energy consumption is encouraging energy conservation actions, which should begin at the household level and further spread to the community level. Therefore, this study aims to point out the critical role and growing importance of the ‘human’ dimension of smart cities via a behavior-based approach. The main purpose of the study is to measure the effect of feedback and intervention mechanisms on the energy conservation behavior of 100 volunteers who live in Kadikoy, Istanbul, over eight months through a behavioral questionnaire. The findings indicate that the feedback and intervention mechanisms affect volunteers’ energy conservation behaviors in the following behavioral groups: intention (t(99) = −2.75, p = 0.00), attitude (behavioral beliefs and outcome evaluations) (t(99) = 2.29, p = 0.02), subjective norms (t(99) = −4.07, p = 0.00), and perceived behavioral control (control beliefs and influence behavior) (t(99) = 3.60, p = 0.00). Moreover, among the four variable groups, participants’ intention, subjective norms, and perceived behavioral control scores are relatively high in favor of actual energy conservation behavior. Hence, the findings of the study will provide valuable insights for the local government in terms of empowering citizen participation and data-driven feedback loops, from the bottom-up energy transition perspective, via smart technologies in smart cities.

Energy is a pivotal element for overall development. Therefore, affordable and clean energy for all (Sustainable Development Goal 7) is one of the important elements. Despite a suitable approach, Kyrgyzstan lags behind to achieve its Sustainable Development Goals by 2030. Improving access to energy can significantly impact the progress of many other sustainable development targets. However, access to reliable, sustainable, and adequate energy is a crucial task in rural Kyrgyzstan. Taking into consideration the energy situation and the importance of the availability of energy services, the overarching aim of the presented article is to map the potential of improving rural energy services to foster overall sustainable development goals. The article presents the most relevant information about rural energy usage behaviour based on three primary pillars: energy demand, energy carrier, and energy sources. In addition, the presented research article synthesises the key driving factors which have a direct or indirect impact on the energy services in rural areas. The summarised data displays a deep insight into a variety of complex and dynamic household energy consumption patterns. The article provides a potential solution nexus to foster improved energy services in rural Kyrgyzstan and therefore to foster the overall sustainable development in Kyrgyzstan. The findings of the article help to formulate a strategy to design rural energy services for policy makers and stockholders.

Rural areas are essential to moving towards the necessary sustainable energy transition and climate change mitigation through renewable energy (RE) technologies. However, RE planning and decision-making in rural locations have not been developed to date with a focus on the local level and accompanied by a careful and thorough assessment of the simultaneous availability of alternative RE sources in a specific territory. Quite differently, RE investments in rural locations have been primarily driven by the interests of large power utilities to exploit a particular RE source, with benefits escaping from the rural economies to end up in the income statements of those large corporations. There is a need to approach RE planning at the municipal scale considering the availability of alternative RE sources. This study suggests the development of a rural RE potential index that could help in the identification of appropriate locations for the implementation of hybrid renewable energy systems (HRESs). The construction of a composite indicator to measure rural RE potential is exemplified through a case study that deals with ten indicators in the context of Galician rural municipalities, involving different RE potentials and some technical or regulatory constraints. Equal weighting and Principal Component Analysis are considered alternative methods for the index construction. Municipalities are the relevant local decision level where energy policy should be focused in order to diversify both the RE mix and the investor base. The proposed index could be the basis for future analyses aimed at optimizing the design and implementation of HRESs in rural environments at a local-regional-national scale. [ABSTRACT FROM AUTHOR]

The energy mix in Nepal is currently dominated by the traditional and inefficient use of biomass (66.54%) and fossil fuels (27.24%), and energy poverty remains extremely high. This paper reviews relevant literature to provide an overview of the current renewable energy status and energy mix in Nepal, and to discuss prospects for the country to achieve a sustainable energy transition. Nepal‐specific papers from peer‐reviewed sources and other agency and academic reports were included insofar as these discussed renewable energy and provided recommendations for policy‐making on sustainable energy and related development goals. Despite the rapidly falling cost of solar photovoltaic, the share of modern renewable energy in Nepal is currently less than 3%. On this basis, and given the country's sustainable energy goals, we conclude that favorable and aggressive policies and strategies are needed to support adoption of clean energy in Nepal, comprised of a high share of solar generation equipped with battery storage, and balanced with storage such as off‐river pumped hydropower technology. [ABSTRACT FROM AUTHOR]

Abstract Background As the countries of the Western Balkans (WB) have committed to sustainable development, the process of regulatory and economic adjustment is underway. As part of the aforementioned fact, the WB countries have commenced exploitation of energy from renewable sources, among which hydropower is the most important. The main objective of the study is to analyse the status of renewable energy transition in the WB region, focusing on the construction and exploitation of small hydropower plants (SHPPs), as well as a proposal for an original model for decision making in this field, based on a multidimensional decision-making space. Namely, in most cases, there is resistance to the construction of SHPPs in the WB territory, as well as divided opinion among investors, companies, environmental movements, academia, and citizens on this issue. This shows that the entire decision-making process has to be reviewed and re-designed. Results The results of the study show that the construction of SHPPs caused damage to environmentally protected areas, living conditions of local communities, touristic and agricultural potential. All of the foregoing matters have led to mass protests by citizens and a high degree of mistrust so that the future of SHPPs in the WB is extremely uncertain. The assessment of the acceptability of existing SHPPs through the proposed model showed that 74% of SHPPs cannot be considered acceptable from the aspect of the location where they were built, and from the aspect of the impact on the quality of life of the local population. Accordingly, this paper provides suggestions for much-needed improvements. Conclusions The construction of SHPPs is causing numerous controversies, opposition, and resistance. To find the right solution, and contribute to sustainable energy and economic development, it is necessary to develop a fully transparent and objective policy system in this field, and to use contemporary models for decision making with emphasis on the involvement local communities in the decision-making process.

• Proposing a deep learning model based on AAE to predict PV. • Developing ICA to adjust the parameters of the AAE. • Stability analyses for the optimal training of prediction model. This research proposes a navigation method that explores how to accelerate urban energy transformation through legal means from the perspective of energy law, in order to improve the accuracy of photovoltaic output power prediction in sustainable energy transformation. Firstly, a deep learning model based on adversarial autoencoder (AAE) architecture was introduced to predict photovoltaic output power according to clean environment policies. Secondly, in order to effectively fine tune the parameters of AAE, a heuristic optimization method based on the Imperial Competition Algorithm was proposed to optimize the AAE configuration to adapt to the unique characteristics of photovoltaic systems, thereby improving prediction accuracy. In addition, the study analyzed the challenges and opportunities faced by current urban energy transformation, and then proposed sustainable ways to accelerate urban energy transformation from the aspects of formulating transformation plans, promoting technological innovation, promoting green transportation, promoting building energy conservation, and developing circular economy. The synergistic effect of deep learning and heuristic optimization, combined with strict stability and sensitivity assessment, puts this research at the forefront of advancing photovoltaic output power prediction methods, which is of great significance for optimizing renewable energy utilization and grid integration. [ABSTRACT FROM AUTHOR]

Our study investigates the relatively unexplored relationships between socio-economic factors and perceptions of climate change and their influence on household energy preferences in developing contexts, taking the case of Nepal. We aim to achieve two objectives: to create a robust model identifying key socio-economic and climate perception variables affecting household energy behaviour; and to compare the respective impacts of these factors. Applying a mixed-method approach, we surveyed 323 households across 49 districts and three physiographic regions (high hills, mid hills and Terai plains) of Nepal. We fixed the explanatory and response variables through literature review and evaluated three ordinal logistic regression models: one focused solely on socio-economic factors, the second only on climate perception and the third a composite model integrating both. Data statistics showed that 47 % of the respondents preferred no change to their existing energy status, 23 % opted to rely completely on grid-electricity, 14 % favoured switching to renewables, while 16 % preferred an optimal combination of grid-electricity and renewables for their household use. The Composite-model was found to be the best fit model for our dataset. The identified key socio-economic factors include urbanization, education levels, and the availability of energy alternatives indicating a wide disparity in the energy access and use across the different socio-economic categories of Nepal. Likewise, magnitude and timing of summer and winter rainfall, changes in the household energy demands and community level subsidies were found to be the significant climate change perception variables. Hence, our findings highlight the need for better access to modern energy and financial incentives, mostly to the rural remote areas, and community-awareness initiatives throughout the country supported by comprehensive energy policies for sustainable renewable energy transition at the household level as well as in mitigation of the impacts of climate change. By enhancing this policy-science-society interface, our research contributes valuable insights for developing effective strategies to promote renewable energy adoption in similar developing contexts. • People's energy preferences are impacted by multiple factors. • Composite model outperformed its counterparts. • Socio-economic and climate change perception parameters need to be dealt holistically. • A significant contribution to the policy-science-society interface. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive approach to optimizing renewable energy allocation in urban environments. Our methodology integrates statistical economic modeling and decision-making techniques to address the complex challenges associated with renewable energy management. By employing stochastic programming and robust optimization, we optimize renewable energy allocation to minimize operational costs, reduce emissions, and enhance system reliability. Our analysis demonstrates significant reductions in operational costs (15.2%) and emissions (20.5% for NOx and 18.9% for CO2) compared to baseline scenarios. Moreover, our approach improves system reliability by reducing load shedding (25.1%) and enhancing overall system reliability (12.3%). These findings underscore the effectiveness of our proposed strategy in fostering economic, environmental, and operational sustainability in urban energy environments. • VNS optimizes urban renewable energy efficiently. • Statistical modeling guides data-driven decision-making for urban systems. • Novel cost effective and emissions reductions framework for urban systems. [ABSTRACT FROM AUTHOR]

Abstract Background The paper aims at gaining insight into the implementation of the process of sustainable energy transition in the countries of Central Asia: Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. Information and scientific studies on the situation in these countries is scarce. On the other hand, these are resource-rich countries, some are exporters, and all are energy transit countries. The main aim of the paper was realized by applying the energy policies and regulatory framework analysis, defining priorities and monitoring selected indicators prescribed by the International Energy Agency. Methods The following methods were used in the quantitative analysis: measurement of data intercorrelation; Pearson test of correlation; principal component analysis (with rotation method: Oblimin with Kaiser normalization); Kaiser–Meyer–Olkin measure of sampling adequacy, Bartlett’s test of sphericity and t-test. The period covered by the quantitative analysis: 1990–2018, provided that the available data for 2019 or 2020 were used in certain cases. Results Sustainable energy transition is, at the analysis of policies and data, at a low level. There is no adequate regulatory framework in these countries. The energy transition takes place exclusively within the framework of providing enough energy, without regard to sustainability, while even energy exporting countries are not making efforts to achieve a sustainable energy transition. Conclusions There are no indications that the energy transition in the countries of Central Asia will take place according to the standards of the European Union or global bodies. On the other hand, having in mind the natural resources of the mentioned countries and the specific geopolitical position, monitoring the changes is of special importance. The impact of changes on sustainability can be determined mainly ex post.

Energy is a pivotal element for overall development. Therefore, affordable and clean energy for all (Sustainable Development Goal 7) is one of the important elements. Despite a suitable approach, Kyrgyzstan lags behind to achieve its Sustainable Development Goals by 2030. Improving access to energy can significantly impact the progress of many other sustainable development targets. However, access to reliable, sustainable, and adequate energy is a crucial task in rural Kyrgyzstan. Taking into consideration the energy situation and the importance of the availability of energy services, the overarching aim of the presented article is to map the potential of improving rural energy services to foster overall sustainable development goals. The article presents the most relevant information about rural energy usage behaviour based on three primary pillars: energy demand, energy carrier, and energy sources. In addition, the presented research article synthesises the key driving factors which have a direct or indirect impact on the energy services in rural areas. The summarised data displays a deep insight into a variety of complex and dynamic household energy consumption patterns. The article provides a potential solution nexus to foster improved energy services in rural Kyrgyzstan and therefore to foster the overall sustainable development in Kyrgyzstan. The findings of the article help to formulate a strategy to design rural energy services for policy makers and stockholders. [ABSTRACT FROM AUTHOR]

Although the diffusion of policy innovations can promote sustainability, how this process can be accelerated remains unclear. I address this gap by conceptualizing policy transfer and policy diffusion using the multiple streams framework (MSF) and developing hypotheses to connect them. I apply this theorization to explain the limited spread of the energy conservation building code (ECBC) in India by combining a process trace of policy adoption in the embedded case of Andhra Pradesh with a dyadic event history analysis of state‐level diffusion during 2012‐18. The data for this study are collated from official statistics, elite interviews, news reports, policy documents, and secondary literature. The qualitative analysis shows that policy transfer to Andhra Pradesh occurred when external influence and prior adoption elsewhere were used by a policy entrepreneur to exploit a window of opportunity and couple problem, policy, and politics in the state; the dyadic analysis demonstrates that policy diffusion was influenced by the interaction among the structural characteristics of the problem, policy, and politics streams. I conclude with the implications for research on policy diffusion and the MSF as well as the relevance of the findings for promoting policy innovation for a sustainable energy transition. [ABSTRACT FROM AUTHOR]

Abstract Background Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended—SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods Research was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx—Microsoft Research’s Bayesian Network Authoring and Evaluation Tool. Results Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.

The COVID-19 pandemic brought tremendous pressure to the African continent's health sector, particularly in rural areas. Rural healthcare facilities experienced severe energy shortages due to the influx of Covid-19 patients, which strained their operating capacities. These facilities usually rely on diesel engines, and this unidirectional approach limited governments' vision in resolving the energy crisis. This paper aims to develop a hybrid energy system (HES) that combines alternate energy sources available at a rural healthcare centre in northern Nigeria and conduct a techno-economic analysis of the viability of such systems. The energy potential of available energy resources at the target location and comparison of various HES configurations were estimated with HOMER Pro software to determine the most feasible choices. These choices were analyzed for technical, financial, and environmental viability using RETScreen Expert. Due to an abundance of solar energy, low diesel cost, and sufficient wind energy potential, the results show PV – Diesel and Wind – Diesel system HES configurations as the only practical choices. Techno-economic analysis indicates that the PV – Diesel HES produces annual savings of $30,583 with a Net Present Value (NPV) of $390,949 compared to $15,174 and $193,980 for the Wind – Diesel configuration. Further analysis solidifies the PV-Diesel HES as the best choice with a payback period of 1.3 years, 75 tons of CO2 emission reduction, and annual savings of $30,583 compared to the initial diesel energy system.

The success of sustainable development heavily depends on successful energy transition toward renewable or carbon-free energy sources. This study attempted to analyze the impact of sustainable development and environmental initiatives on sustainable energy transition in selected OECD economies. For this purpose, the study generated the dataset of environment air and GHG emission, environmental-related technologies, development (gross domestic product, trade openness, and gross domestic spending on R&D) and sustainable environment (air and GHG emission and environmental-related technologies), and energy sources (renewable energy consumption, nonrenewable energy consumption, and sum of total energy consumption) of selected economies of OECD between 2000 and 2020. This study utilized dynamic panel GMM for regression analysis, and FMOLS and DOLS were applied as the robustness models. Empirical results indicated that sustainable development and a sustainable environment contribute positively to the energy transition process in OECD economies. However, these factors also negatively contribute to non-renewable energy consumption in OECD. Thus, the study’s outcomes confirmed the sustainable energy transition in OECD. Therefore, this study suggested that the success of Sustainable Development Goals depends on successful energy transition.

With the increasing urgency for sustainable development and energy transition, decision-makers face complex challenges in evaluating and prioritizing viable alternatives. Traditional decision-making techniques often struggle to capture the inherent uncertainty and imprecision associated with the latest sustainable energy transition issues. This paper presents a research framework based on fuzzy set theory and the technique for order of preference by similarity to ideal solution (TOPSIS) method to address these complexities and uncertainties. Our proposed approach offers a comprehensive evaluation and ranking of alternatives for sustainable energy transition. To demonstrate the effectiveness and applicability of this system, we employ a case study in the Kingdom of Saudi Arabia (KSA). As a global leader in fossil fuel production and export, particularly oil, the KSA has recognized the need to address climate change and diversify its energy sector. By leveraging the fuzzy TOPSIS-based framework, we provide decision-makers with a powerful tool to navigate the challenges and uncertainties involved in the energy transition process. This research yields promising results, demonstrating the superior capabilities of the proposed fuzzy TOPSIS-based framework compared to traditional decision-making techniques. The case study in the KSA highlights how our approach effectively captures and addresses the uncertainties and complexities involved in sustainable energy transition decision making. Through comprehensive evaluations and rankings, decision-makers gain valuable insights into alternative solutions, facilitating informed and strategic decision-making processes. Our research contributes to sustainable energy transitions by introducing a robust decision-making framework that integrates fuzzy set theory and the TOPSIS method. Based on the fuzzy TOPSIS-based evaluation, the research findings indicate that solar energy (EA1) ranked as the most favourable alternative among the evaluated options for the sustainable energy transition in the KSA. Using our framework, stakeholders in the KSA and similar contexts can make informed decisions to accelerate their energy transition efforts and achieve sustainable development goals.

Waste-to-Energy (WtE) has been considered as an option to eliminate Krabi’s problems of municipal solid waste (MSW) management. A survey on WtE potential as well as key drivers, barriers, and challenges to overcome the barriers was conducted in this study. The study found high WtE potential due to huge amount of many years accumulated MSW in couple with the increasing trend of new daily waste generation. Meanwhile, Krabi is an island having land limitation for landfill. The urgent need to eliminate the huge amount of MSW has become a key driver for WtE implementation. One more key driver of WtE is Krabi Goes Green roadmap with target to generate electricity from 100% renewable energy by the year 2026. Another key driver is disruptive effects of MSW management roadmap under Section 44 of Thailand's Constitution 2017. By the way, implementation of WtE is facing with public opposing due to concerning of dioxin and air pollutant emissions from solid waste combustion. How to ensure zero emission of dioxin and air pollutants is very challenging to achieve public trust and acceptance. High temperature combustion as well as installation of high efficiency end-of-pipe treatment together with real-time monitoring system was recommended by some interviewees of the present study. In addition, due to MSW management and WtE power plant investment must involve with many organizations; therefore, stakeholders' open mind consultation and policy integration among relevant governmental agencies are highly recommended.

• Novel GRU-LIME prediction method boosts accuracy. • GRU consistently beats traditional models for reliable predictions. • Renewable energy insights inform sustainable urban development. This study proposes a novel approach to sustainable energy transition in urban environments, focusing on the prediction and management of renewable energy outputs for low-carbon urban development. We introduce a new intelligent prediction model based on Gated Recurrent Unit (GRU) Networks to forecast the output power of both tidal and biomass units. The GRU model, known for its capability in capturing sequential dependencies, is employed to enhance the accuracy of renewable energy predictions in the context of urban sustainability. To address the interpretability challenges inherent in complex deep learning models, we leverage LIME (Local Interpretable Model-agnostic Explanations). By integrating LIME into our GRU-based prediction model, we enhance transparency and understandability. This approach facilitates the identification of key factors influencing predictions, providing stakeholders and decision-makers with valuable insights for effective sustainable energy management. The proposed hybrid model is applied to the digital model of real tidal and biomass sites in China, allowing for a statistical examination of renewable integration and energy management strategies. The results offer a comprehensive understanding of the dynamics between renewable energy sources and urban development, paving the way for informed decision-making in the pursuit of low-carbon and resilient cities. This research contributes to the broader discourse on sustainable urban development by offering a robust statistical framework for renewable energy integration and management in urban environments. [ABSTRACT FROM AUTHOR]

Facilitating a sustainable transition process, whether on a global or local scale, entails crafting an energy mix tailored to meet the specific needs of users. The objective is to pinpoint the most effective future strategy that optimizes both socio-economic benefits and sustainability. To tackle these challenges, a plethora of modeling tools now exists to evaluate various scenarios prior to implementation. However, it is worth noting that modeling tools are primarily geared towards economic optimization, exemplified by the open-source energy modeling system, OSeMOSYS. This paper proposes an optimization methodology encompassing economic, energetic, and environmental sustainability, introducing the most widely referenced estimator as an economic additional cost using the weight sum and monetization methodology. The ramifications of integrating these different estimators in terms of energy matrix design, costs, and emissions are thoroughly evaluated. Furthermore, the optimal selection criteria are delineated based on users' anticipated objectives. To ensure the reproducibility of the study, we present an exercise utilizing data from Atlantis framework, which shares characteristics of both developing and developed nations. The main results indicate that implementing sustainability, despite not causing significant variations in overall costs (¡0.5%), leads to a 35% decrease in emissions. However, there is a 14.5% increase in investment costs, while residual costs rise by 6%. • Novel Methodology Proposal Integrated on the OSeMOSYS Tool. • Multi-Criteria Optimization including sustainability estimators criteria. • Estimators for energy, economic, and environmental sustainability are integrated. • Impact on Decision-Making of a sustainable energy system. • The sustainable transition does not entail a notable increase in the total cost. [ABSTRACT FROM AUTHOR]