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A current challenge in energy system modelling is integrating high temporal and spatial resolution with a detailed representation of technologies and sector coupling within a single model. This paper presents a pioneering sectoral optimisation approach for transformation pathways in the German federal states. Spatial resolution in the energy system model REMod is increased and the model is extended from a single-node to a multi-node model for Germany by integrating energy exchanges between regions into a simulation-based optimisation. The approach highlights the challenge of adjusting energy distribution to address the mismatch between high final energy demand in some states and the potential for renewable energy resources in others. The extended model was compared with the results of the single-node model with the same boundary conditions. The comparison showed that increasing the spatial resolution did not significantly affect the overall cost of energy system transformation. However, the composition of the energy system changes, leading to approximately 6% more renewable capacity being installed in a scenario with ten regions. The results for the German federal states indicate a concentration of onshore wind development in the northern federal states with higher full load hours, especially in Lower Saxony/Bremen with 36 GW and Schleswig-Holstein/Hamburg/Mecklenburg-Vorpommern with 38 GW in 2045. The expansion of photovoltaic capacity in densely populated states such as North Rhine-Westphalia (73 GW), Bavaria (71 GW), and Baden-Württemberg (54 GW) reflects the need to meet growing electricity demand. The solar photovoltaic to wind power ratio varies between the federal states and influences the choice of flexibility options, including power-to-x technologies or gas and hydrogen turbines. By 2045, Germany's primary energy supply will shift to states with abundant renewable resources. Spatial flexibility is essential to balance electricity demand and solar and wind potential, mainly through state interconnections. • Sector-coupled energy system model with high temporal and spatial resolution developed. • Simulation-based optimisation as alternative to linear optimisation techniques. • Transformation path on federal states level for Germany modelled. • Transmission grid expansion is needed to transmit renewable energy from Northern to Southern Germany. [ABSTRACT FROM AUTHOR]

Measuring the limitations of transitioning to 100% renewable energy systems partly equates with the capability of quantifying associated net-energy production. To foresee future possibilities, an advanced systemwide energy-return-on-investment (EROI) model was constructed. Driven by the thorough consideration of the existing weaknesses of EROI, the model integrates the concept of energy statistics, life cycle assessment techniques and energy system modelling in order to overcome the underlying primary energy quality issues, boundary condition problems and energy system design related uncertainties that compromises comparability of EROI during the energy transition. This model was applied to the Israeli power system that presents a unique opportunity to examine the vulnerability of depending on limited resources and the connection of EROI to system design. This study demonstrates the dependency of EROI on the energy transition path, system design requirements expressed via interactive linkages of curtailment, variable renewable energy penetration and storage system design, and resource diversity. Achieving a very high variable renewable energy penetration by 2050 with solar photovoltaics carries a risk of falling below an EROI value of 10, such vulnerability can be largely minimised by well-conducted manoeuvring of the system design and resource diversification. Despite the large uncertainty of this study, the need for a multicriteria designing technique is out of the question. • An advanced systemwide EROI model suitable for studying transitions is presented. • EROI trend depends on transition paths and system design differences. • EROI bottoms out for system designed without curtailment. • Very high solar photovoltaics penetration of up to 100% carries sustainability risk. • Multicriteria system design and resource diversification can circumvent the risk. [ABSTRACT FROM AUTHOR]

The separation of heavy water (D 2 O) from light water (H 2 O) is an energy-intensive process. Heavy water is primarily used in nuclear reactors but has vast applications in medical and biological investigations. This paper comprehensively investigates suitable thermodynamic conditions for separating heavy water from light water using gas hydrates. Gas hydrates, which are crystalline structures made up of water and gas molecules, have drawn much interest because of their usage to separate gas mixtures. In this work, however, using high-pressure Differential Scanning Calorimetry, different thermodynamic phase boundaries of hydrate formation from the liquid mixture of D 2 O and H 2 O were explored for preferential separation of D 2 O as solid hydrates. Utilizing a laboratory scale, high-pressure reactor differences in the kinetics of hydrate growth using heavy water and light water were also investigated, thus clearly showing that the hydrate formation and dissociation process could be utilized for separating the two water isotopes. In this work, hydrates were formed at 278.15 K using methane & natural gas to understand the thermodynamic phase behavior of these hydrates. Since kinetics and morphology of hydrate formation are also crucial for a scale-up, comparing two different types of hydrate former will help understand the behavior better. The results of this study contribute to the fundamental understanding of thermal behavior and the kinetics of hydrate formation of light and heavy water. The comparative analysis of DSC thermograms provides valuable insights into the effects of isotopic substitution on the phase transitions of water. • A novel hydrate-based separation process for separating a highly energy-intensive mixture of H 2 O-D 2 O. • Thermodynamic insight on Heavy water and Light water solidification (phase change) using in-situ High-Pressure DSC. • Demonstration of lab-scale hydrate formation, thermodynamics & kinetics using an H 2 O-D 2 O mixture. [ABSTRACT FROM AUTHOR]

To meet the nationally determined contributions proposed by the countries that signed the Paris Agreement, investments must be made in renewable generation technologies such as solar and wind. However, due to their high variability, these technologies pose challenges in terms of meeting demand or generating excess electricity. For this reason, energy system models are designed to capture this variability by considering flexibility technologies. Nevertheless, it is important to note that some energy system models lack integration with other sectors. Therefore, integrated assessment models have been employed to evaluate mitigation strategies, as they endogenously consider the linkages between energy and non-energy sectors. In addition, due to their complexity, these models do not account for the variability of renewable resources. Hence, this research aims to address this issue. This work represents the first attempt to evaluate how the introduction of hourly resolution affects the outcomes of integrated assessment models, specifically focusing on the Global Change Analysis Model (GCAM). We employ a soft-linking approach between the GCAM and the Highway to Renewable Energy Systems model (H2RES, an hourly level energy system model) to accomplish this. The proposed approach is tested using Chile's Nationally Determined Contributions under different hydrological profiles in the power sector. The results show that it is possible to use the capacity obtained from the Global Change Analysis Model and implement it on an hourly scale. However, the feasibility of implementation depends on high levels of flexibility technologies, such as battery energy storage. When given the choice of investments in renewable sources and flexible technologies, the optimal dispatch of the H2RES model show small differences than those obtained by GCAM-Chile. H2RES differs from GCAM-Chile in approximately 5% for wind and 3% for solar electricity generation in the year 2050. However, feasible integration of significant renewable sources is obtained with relatively high Critical Excess Electricity Production levels, reaching 20% in 2050. This excess electricity is attributed to the necessity for flexible technologies to manage the intermittency of renewables sources when hourly profiles of such sources are considered. • Assessment of the importance of the hourly variability for carbon neutrality pathways. • Feasible integration of large renewable resources with high critical excess electricity production levels. • Large deployment of energy storage for integration of variable renewable energy. • Solar Photovoltaic, preferably over wind energy to compensate for dry – hydrology. [ABSTRACT FROM AUTHOR]

With increasing focus on equitable and just energy transition, it is critical to understand the trade-offs of different decarbonization outcomes across economic, environmental, and social sustainability criteria. In this analysis, we use a multi-criteria decision analysis to quantify sustainability outcomes across 32 decarbonization outcomes in 2050 in the U.S. The economic sustainability criteria we use are system cost, national average retail rate, and electricity system employment. The environmental sustainability criteria we use are life cycle greenhouse gas emissions, life cycle water depletion, life cycle land transformation, and air pollution fatalities. The social sustainability (distributional impacts) criteria we use are retail rate equality across states, electricity employment equality across low-income households, and air pollution disparities across census tracts. We evaluate performance across these criteria under eleven different stakeholder preference scenarios. We find that decarbonization policies with indefinitely extended tax credits have the highest sustainability score under equal criteria weighting, with greater investments in renewable energy technologies, and result in better environmental, system cost, job, and air pollution disparities compared to mid-case scenarios, that only include current policies and CO 2 reduction targets. We also see that our multi-criteria decision analysis identifies decarbonization outcomes that would not have been identified as optimal under a single objective, which highlights the importance of trade-off analyses to understand decarbonization outcomes more holistically. • Trade-off analysis across sustainability criteria for decarbonization outcomes. • Include distributional equality as social sustainability criteria. • Multi-criteria decision analysis across eleven stakeholder preference scenarios. • Indefinite tax credit extensions score highest in sustainability. [ABSTRACT FROM AUTHOR]

More and more territories are looking at alternatives to diesel for their public transport to decarbonise their energy mix. Electricity and hydrogen, among the most popular alternatives, are analysed in this article on the basis of various technical, economic and environmental criteria. The consumption of these vehicles is first estimated and the feasibility of their implementation validated in terms of range and recharging time. The economic criterion then evaluated is the total cost of ownership (TCO) of the vehicle fleet, and the environmental criterion is the global warming potential (GWP) of a vehicle, taking into account the life cycle of the main technologies that compose it as well as the vehicle's operating phase. Here, coaches are analysed for the case study of Reunion Island. If the technical feasibility concludes that it is impossible to use a fleet entirely composed of electric vehicles, a fleet composed only of hydrogen vehicles would involve high TCO and GWP. A balance must be struck and improvements in vehicle consumption can be made to reduce the overall impact. [Display omitted] • GWP depends mainly on operation phase, the least on the transport of the technologies. • With marked relief, range and recharging time are a limit of battery coaches. • A battery and fuel cell coach mix results in an economic and environmental optimum. • Improvements in eco-driving and vehicle weight reduce costs and environmental impact. [ABSTRACT FROM AUTHOR]

Technological factors have significant impacts on the geopolitics of energy transition and climate governance, yet little scholarly attention has been given to international technological competition. This paper constructs a global photovoltaic technological competition network based on patents from 1970 to 2018 to capture the international competitive dynamics at multiple scales. The results reveal a continuous expansion of the global photovoltaic technological competition network. The network has an ideal core-periphery structure, while the competition between peripheral countries has been intensifying. Competition at the regional level is strongly related to Europe due to the high innovation capacity and foreign patenting rate of European countries. The elevating position of East Asia and the rest of the world since 1990 reflects the shifting landscape of global photovoltaic production. The United States and Japan have alternatively dominated the global photovoltaic technological competition, while Germany's influence is declining. Two catching-up players, South Korea and China, have significantly improved their status. The vast majority of developing countries, especially those that rely heavily on fossil fuels, are lagging far behind and exposed to the risk of "carbon lock-in". • A global photovoltaic technological competition network is constructed using complex network theory. • Photovoltaic patenting has formed a pattern of global competition with increasing intensity. • Competition at the regional level is strongly related to Europe. • National competitiveness is geographically uneven and temporally dynamic. • Photovoltaic technological competition may lead to intensifying geopolitical tensions. [ABSTRACT FROM AUTHOR]

Individual households, responsible for 25% of total energy consumption in Europe, are crucial actors in the energy transition. Although various policies and energy choices are available for such actors (e.g., individual solar photovoltaic or community energy systems), they are usually restricted to municipal governance, and public opinion towards national energy policy is not strongly presented. This study explores and describes the influence of the availability of alternative energy choices on different levels of governance to facilitate households' energy transition. An agent-based model is conceptualised through multi-level governance, the institutional analysis and development framework and the social value theory. To also address the ongoing energy crisis, the study focuses on the Dutch thermal energy transition and the thermal energy communities as a collective action for generating, distributing, and consuming renewable thermal energy and, therefore, three layers of energy choice alternatives are provided for households: national level (i.e., sources of natural gas), municipal/ community level (i.e., collective renewable energy technologies), and individual level. The results delineated the importance of the availability of alternative energy choices in the suggested multi-level governance collective action system. Such systems consumed only 12% natural gas, while they covered their thermal demand by increasing the capacity of collective thermal energy systems (83% on average) and adopting more individual thermal energy systems (heat pump, approximately 85%). Although the performances on voluntary blackouts/ discomfort (2.7% on average) and CO 2 emissions (85% reduction approximately) were also positive, this was reflected in a significant price increase. • Agent-based modelling and simulation is used to study thermal energy transition. • Multi-level governance is used as a theoretical backbone in an agent-based model. • The importance of the availability of alternative energy choices is demonstrated. • The availability of several natural gas sources leads to more sustainable outcomes. • The establishment of thermal energy communities is vital for the energy transition. [ABSTRACT FROM AUTHOR]

Electricity management systems are experiencing significant challenges due to the increased penetration of distributed energy resources. Electricity flows in distribution networks are transforming from unidirectional to bi-directional form. Consumers are transitioning to prosumers with different characteristics, where they take more active roles in electricity generation and consumption. Aggregators are vital financial intermediary agents in the power system transitions, as they could aggregate energy profiles of prosumers. The market competition between aggregators and interactions between prosumers and aggregators are complex and dynamic, which requires a holistic framework to model the market competition. This paper proposes an intelligent aggregation framework with edge computing, enabling decentralized competition for multiple aggregators and prosumers, which can be solved with a graph-based consensus algorithm. This study mathematically proves the proposed algorithm's convergence guarantee and convergence rate. In addition, the proposed framework is applied to an open-source dataset to demonstrate its applicability. Lastly, a benchmark analysis is conducted to show that the proposed algorithm has better communication complexity than the benchmark algorithms. • A dynamic market competition model for prosumer aggregation. • The solution state for the market to reach equilibrium is unique. • A graph-based algorithm for the market model with edge computing. • A proposed algorithm with a linear convergence rate. [ABSTRACT FROM AUTHOR]

Despite having multidimensional positive externalities of renewable energy (RE) in theory, the literature on RE's economic and environmental determinants is still very nascent. We have addressed this research gap by considering a balanced panel of 38 OECD nations attempting a phase-by-phase energy transition. We have used data spanning from 2000 to 2020 and deployed the novel method of moments quantile regression (MMQR) approach. Our results unveil that economic complexity reduces the consumption of renewable energy among the OECD nations, indicating that as the export becomes diversified, energy consumption at the production level becomes more dependent on non-renewable sources. This further suggests that OECD nations are yet to meet their renewable energy generation threshold. Moreover, energy efficiency fosters the consumption of renewable energy, substantiating that energy efficiency and renewable energy share complementary co-movement among the OECD nations. Furthermore, we unravel that environmental technology and natural resource rent have heterogeneous effects on renewable energy consumption in OECD. For instance, environmental technology only boosts RE consumption at the higher quantiles (70th to 95th), whereas revenue from natural resource rent curbs RE consumption. Our conclusions hold after a series of robustness checks. Overall, we propose that OECD nations should only export those products with absolute comparative advantage to reduce excessive dependence on fossils. Additionally, investment in renewable energy technology development should be escalated to ensure energy efficiency in the long-term. • The impacts of economic complexity (ECI), environmental technology (ENT), natural resource rent (NRT) and energy efficiency (EFX) on green energy use explored. • We use novel non-parametric method of moments quantile regression approach for OECD countries. • The ECI curbs the consumption of renewable energy while EFX is a boon for it. • ENT and NRT have heterogenous effects on RE consumption. • We also note different causal relationships to rectify the results' robustness. [ABSTRACT FROM AUTHOR]

Hydrogen Direct Reduction of Iron (HDRI) combined with renewable electricity is an attractive option for low-carbon steel production. In this paper, we present a novel and computationally efficient techno-economic power-to-x-plant optimization model which is then applied to an HDRI plant located in Finland. Plant dimensioning was carried out in several current and future power market and regulatory scenarios. We predict a production cost of 373 €/t for hot briquetted iron, and 351 €/t for a future scenario of 2025–2030. When the recently introduced EU rules for renewable fuels of non-biological origin are applied, the production costs increased by 30–46 €/t. The rules also have a significant increasing effect on the required hydrogen storage. The flexibility of the direct reduction shaft emerged as an important parameter affecting the required hydrogen storage as well as total production cost. The results of this paper hold significance for the optimal design of future low-carbon steel plants. • Computationally efficient optimization model for Power-to-X operations and dimensions. • Hydrogen Direct Reduction Ironmaking (HDRI) plant using wholesales and wind power. • Significant amounts of intermittent wind power can be absorbed by the HDRI plant. • HDRI/HBI production costs analyzed for EU regulatory scenarios on green hydrogen. • Emission reductions over 96% compared to CO 2 emissions of fossil steelmaking. [ABSTRACT FROM AUTHOR]

Power systems with a high level of renewable energy penetration face challenges due to the inherent properties of some renewable energy sources, such as their variability and uncertainty. These systems require reliable technologies capable of handling large ramps and flexibility needs. Concentrating Solar Power (CSP) has been identified as one solution, which has been researched and implemented in several countries. This paper presents a novel analysis and evaluation of the impacts of choosing an inadequate representation of CSP technology in power system planning tools. The current state of CSP in power system expansion planning in the literature is examined, providing a classification for the modeling of investment and operation of CSP plants. Based on a proposed analysis framework, different models and configurations for CSP plants are evaluated and applied to a 5-bus test system. One of the key findings is that the selected model highly impacts the computational effort (150% more processing time), the quality of the planning decision (14% more overall costs), and the total emissions (up to 52% more emissions). A storage-based model proves to be the most suitable option, considering the operation and investment costs, as well as computational burden. The selected model achieves a 1% error compared to the results obtained with a reference model, while also requiring 40% less computation effort. The proposed framework can be applied to other power system structures by choosing the best suited CSP modeling. • Analysis and evaluation of CSP modeling alternatives in power system planning. • State-of-the-art of CSP models for power system planning are reviewed and classified. • Selection of CSP project candidates impacts overall costs and optimal generation mix. • The modeling of CSP affects investment decisions, system costs, and emissions. • A storage-based model offers a good trade-off between accuracy and complexity. [ABSTRACT FROM AUTHOR]

Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure. [Display omitted] • The role of artificial intelligence in the energy transition process is studied. • Stage differences in the role of AI are analyzed. • The nonlinear relationship between AI and energy transition is investigated. • Provide insights into the factors affecting the relationship between AI and energy transition. • This research helps the government to advance the energy structure transition. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [ABSTRACT FROM AUTHOR]

Navigating the transition toward a zero-emission and just future amidst multiple crises requires a nuanced understanding of potential hindrances to investments and energy transitions. As current approaches hardly consider the big picture of interacting crises, this study offers a framework to analyze the dynamics and risk channels between 1) the climate crisis, 2) financial (in)stability, 3) the geopolitical energy crisis, and 4) the energy transitions. Our framework reveals that the dynamics depends on the specific emergency policy. Hence, we apply the framework to a German Case study. Our findings reveal that fossil energy security policies and insufficient macroprudential policies can threaten the energy transition and financial stability exacerbating negative feedback loops. The discussion highlights that short-term emergency policies outweighing long-term climate goals fail to secure financial stability, reduce transition risks, or accelerate the energy transition. In conclusion, crises can catalyse the transition if short-term emergency policies are harmonized with long-term climate goals advocating for a coherent policy framework. [Display omitted] • Conceptual framework to identify compounding risks' role in energy transition. • Versatile tool that aids hypothesis evaluation, empirical analysis, and policy assessment. • Transmission channels from climate and geopolitical crises to financial stability identified. • Aligning policies with Paris Agreement vital for zero-emission transition, averting systemic risks. • Fossil energy security policies impede energy transitions and financial stability. [ABSTRACT FROM AUTHOR]

As global concern shifts from developed countries—many of which have made significant strides towards carbon neutrality—to developing nations, an urgent need arises: how can the latter effectively borrow and adapt strategies that have proven successful in the former? This review thoroughly explores the successes and challenges encountered by developed countries in terms of emission accounting, mitigation strategies, and transitioning to renewable energy sources. We then explore how these strategies can be feasibly integrated into the economic, social, and political contexts of developing countries. Furthermore, this paper highlights the importance of customizing these strategies to the unique challenges and opportunities of developing nations, rather than simply replicating efforts. Through a comparative analysis, we present a roadmap to carbon neutrality that acknowledges the distinct contexts of these developing countries while drawing inspiration from global successes. This approach underscores the necessity of a collaborative, global effort in addressing climate change, recognizing the interconnectedness of all nations in this endeavor. It also sets the stage for future research and policy development that are both locally informed and globally conscious. [Display omitted] • Comprehensive analysis of emission accounting successes in developed countries. • Exploration of the unique challenges and opportunities in developing nations. • Emphasis on tailoring, not duplicating, carbon neutrality strategies. • Proposing a cohesive, global approach grounded in local context and solutions. [ABSTRACT FROM AUTHOR]

Transitioning to sustainable energy is a global imperative for countries to develop policies to achieve Sustainable Development Goals (SDGs), particularly SDG 7 and 13. Given the possible association between digital inclusion (DIGI) and the energy transition (EGTN), we examined the impact of DIGI on the EGTN while controlling for environmental taxes (ENTX) in the top-5 greenest economies in the world using quarterly data from 2001 to 2021. We examined the association at short-, medium-, and long-term frequencies using comprehensive approaches such as the Method of Moments Quantile Regression (MMQR) for panel analysis and Wavelet techniques, i.e., wavelet coherence, multiple wavelet, and partial wavelet for country-specific assessment. According to the MMQR results, DIGI has a significant and positive effect on EGTN, with a coefficient value ranging from 10.95 to 5.980 while moving from lower (0.25) to higher (0.95) quantiles. Similarly, ENTX has a positive and significant effect on EGTN, with a coefficient value ranging from 1.770 to 3.132 as the quantiles increase. In addition, the results of wavelet coherence expose a strong and positive connectedness between DIGI and EGTN in each sample country. Furthermore, multiple wavelet results for each country demonstrated that ENTX significantly strengthens the interaction between DIGI and EGTN. Our findings result in developing SDGs-oriented policy guidelines, specifically the policy strategy for addressing SDG-7 and SDG-13. The study endorses that the sample countries take initiatives to accelerate the EGTN process by improving digital inclusion and implementing an effective environmental taxation system. • We evaluated the role of digital inclusion on energy transition. • The study also considers the role of environmental taxes. • The study employed panel data from 2001 to 2020 for the greenest economies. • Digital inclusion and environmental taxes promote energy transition. • The panel results are validated by the wavelet analysis. [ABSTRACT FROM AUTHOR]

Digital transformation has been regarded as a primary styrategy to promote transitions in diverse fields, but industry pioneers believe that the existing barriers may hamper the speed of digital transformation. Hence, this paper presents a synthetical decision model integrating the weighted Heronian mean aggregation (WHMA) operator, the Level-Based Weight Assessment (LBWA) model, the CRITIC (criteria importance through intercriteria correlation) method, and the Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI) model with Fermatean cubic fuzzy sets to evaluate the barriers to digital transformation implementation in energy transitions with unknown weights of experts and criteria. In this framework, an extended WHMA operator with the deviation-based method is established to fuse experts' preference information. The LBWA model and CRITIC method with FCF setting are combined to derive the weights of barriers. Next, these methods are incorporated into the RAFSI model to analyze these barriers. A numerical example of evaluating barriers to digital transformation implementation in the power sector displays the application of the RAFSI model-based decision method. The result reveals that a 3 "Equipment manufacturer" (0.7063) has the highest barrier level, and a 4 "Consumers of smart power electronic" (0.4391) have the lowest barrier level. After that, sensitivity and comparative explorations are applied to examine the feasibility and reliability of the synthetical model. The results show that the proposed model can provide a more practical and stable evaluation result for supporting the decision of stakeholders associated with ET. • This study identifies a structure of barriers to the implication of the digital economy in achieving energy transition. • A synthetical decision model integrating the weighted Heronian mean aggregation operator is presented. • The RAFSI model with FCF is proposed to evaluate the barriers of digital transformation implementation in energy transition. [ABSTRACT FROM AUTHOR]

Decarbonizing the building sector is key to meet the EU climate goals by 2050. Although the recent policies recognized the importance of on-site solar energy production in the energy transition, there are only a few modelling studies analyzing how much the gap between the technically possible and policy-driven power generation of rooftop photovoltaic (PV) panels can be reduced. This study, therefore, uses geospatial techniques and the high-resolution Building Integrated Solar Energy (BISE) supply model to estimate the main spatial and temporal characteristics of the rooftop PV energy production potential. To support decision-making, important implications of the Solar Rooftop Initiative action plan of the European Commission on the future dimension of the PV electricity supply are also assessed in the context of the achievable potential. The modelling results indicate that the current rooftop PV technical potential could be about 2.7 PWh, being in similar extent with the EU power consumption. The largest country-level PV potentials can be found in Germany, France, Italy and Poland, with an increase of 30% by 2060. Our findings also underline that by following the latest policies, major improvement could be achieved in the EU's rooftop solar energy production by around 2040, depending greatly on the structure and energy efficiency niveau of the future building stock. [Display omitted] • Germany, Italy and France have the highest technical potential of rooftop PV. • Increase of around 25% in the technical potential was modelled until 2050. • Current rooftop PV technical potential could satisfy all power need in the EU. • Latest EU policies could mean huge step forward to a decarbonized building sector. [ABSTRACT FROM AUTHOR]

As global efforts intensify to mitigate climate change through Net-Zero by 2050, the transition from fossil fuels to renewable energy sources is of utmost importance. Within this context, geothermal power generation is an underestimated yet rapidly developing field with immense potential. A notable opportunity arises from repurposing abandoned oil and gas wells (AOGWs) as alternative sources for geothermal power production. This study employs multi-criteria decision analysis (MCDA) to examine the techno-sustainability of four geothermal power systems: i) a business-as-usual geothermal power plant (GEO bau), ii) repurpose two completely AOGWs for geothermal power generation (R-GEO double), iii) repurpose a single completely AOGW (R-GEO single), iv) repurpose semi-AOGWs (i.e., wells still in operation but with high water cut, R-GEO semi). We assessed 30 criteria across technical, environmental, economic, and social dimensions via the analytical hierarchy process. The study identifies R-GEO semi as the most techno-sustainable option due to its superior performance across environmental, economic, and social dimensions. However, GEO bau closely follows R-GEO semi , securing its position as the second-best option, marked by its outstanding technical proficiency and robust environmental and social performance. Conversely, R-GEO double and R-GEO single show limited techno-sustainability competitiveness. When sensitivity analyses are applied to the weighting factors, R-GEO semi demonstrates resilience and remains as the best option in most cases. However, GEO bau could outperform R-GEO semi when the value of technical criteria is increased (weightings >0.255) or when the weightings for environmental or economic aspects decrease (weightings <0.236 and < 0.244 respectively). R-GEO double and R-GEO single only overtake GEO bau when the economic aspect reaches a weighting of 0.659 or more. Despite R-GEO semi being the most promising option, it faces challenges due to limited power generation capacity and the availability of wells approaching their end-of-lives. The findings underline the necessity for broader stakeholder input, inclusion of more technical and social criteria, and data-driven decision-making processes. • First multi-criteria decision analysis of repurposing abandoned wells for geothermal power. • Repurposed semi-abandoned oil & gas wells are the most techno-sustainable option. • Technical criteria can tilt performance favour towards non-repurposed systems. • Drilling activity should be minimised to boost the deployment of repurposed systems. • Repurposed systems excel when economic criteria are prioritised. [ABSTRACT FROM AUTHOR]

As the global community shifts towards a clean energy paradigm, the understanding of energy security has witnessed significant evolution. Historical interpretations centered on the supply reliability and pricing stability. Contemporarily, terms such as "disruption", "risk", "threat", and "vulnerability" have become central in shaping our perspective on energy security. This is particularly in light of external shocks including geopolitical conflicts, wars, acts of terrorism, extreme climatic occurrences, and other unpredictable challenges. In the face of these external pressures, conventional indicator-based methodologies exhibit inherent challenges in adequately quantifying national energy security. This study introduces a variance-based weighting approach within the classical composite indicator framework and characterize the influence of such external shocks into the weights of individual energy security indicators. As a result, this approach can provide a holistic, intuitive, and communicable tool in the integration of external shock factors into the assessment of energy security performance, all while staying true to the fundamental essence of energy security. Through a re-examination of the energy security risk in major energy-consuming countries from the 2020 GEI, this paper underscores the effectiveness and applicability of our approach. • Novel variance-based weighting method introduced. • Enables inclusion of external factors in energy security performance. • Bridge subjective and objective weighting in composite indicators. • Reassesses energy security risk in major consumers using 2020 GEI. [ABSTRACT FROM AUTHOR]

Achieving carbon neutrality is probably one of the most important challenges of the 21st century for our societies. Part of the solution to this challenge is to leverage renewable energies. However, these energy sources are often located far away from places that need the energy, and their availability is intermittent, which makes them challenging to work with. In this paper, we build upon the concept of Remote Renewable Energy Hubs (RREHs), which are hubs located at remote places with abundant renewable energy sources whose purpose is to produce carbon-neutral synthetic fuels. More precisely, we model and study the Energy Supply Chain (ESC) that would be required to provide a constant source of carbon-neutral synthetic methane, also called e-NG (electric Natural Gas) or e-methane (electric methane), in Belgium from an RREH located in Morocco. To be carbon neutral, a synthetic fuel has to be produced from existing carbon dioxide (CO 2) that needs to be captured using either Direct Air Capture (DAC) or Post Combustion Carbon Capture (PCCC). In this work, we detail the impact of three different carbon sourcing configurations on the price of the e-methane delivered in Belgium. Our results show that sourcing CO 2 through a combination of DAC and PCCC is more cost-effective, resulting in a cost of 146 €/MWh for e-methane delivered in Belgium, as opposed to relying solely on DAC, which leads to a cost of 158 €/MWh. Moreover, these scenarios are compared to a scenario where CO 2 is captured in Morocco from a CO 2 emitting asset that allow to deliver e-methane for a cost of 136 €/MWh. • Model energy supply chain from Morocco to Belgium for electric methane; • Explore three CO2 sources for electric methane synthesis; • Analyse the pros and cons of each CO2 source on price and energy efficiency. [ABSTRACT FROM AUTHOR]

There is growing interest in energy sufficiency (ES); however, it remains conceptually debated and contested. This study presents a novel approach to measuring ES using unique microdata on the energy consumption of Japanese households. This approach determines lower and upper thresholds regarding domestic energy consumption for each household type and then identifies whether people really meet an adequate level of domestic energy services, with their diverse energy needs considered. The result illustrates that most people in Japan live in ES, despite about one-tenth being in energy poverty (EP) and one-twentieth in energy extravagance (EE). In addition, this study empirically clarifies the characteristics of people in ES, as well as those in EP and EE. People in ES and EE generally belong to higher income groups, live in larger houses, and are less committed to energy-saving behaviours; the opposite applies to people in EP. As a policy implication, this study suggests more progressive energy tariffs and carbon pricing, as well as improvement in access to renewable energy for the EP population, to engender an inclusive low-carbon energy transition and allow everyone to achieve ES. • First evaluation of people's 'energy sufficiency' (ES) using Japanese microdata. • Identified households in energy poverty, energy sufficiency and energy extravagance. • One tenth of people are in energy poverty and one twentieth in energy extravagance. • The prevalence of energy sufficiency is much related to income and housing size. • More progressive energy tariffs are suggested to allow everyone to achieve ES. [ABSTRACT FROM AUTHOR]

A prevailing hurdle to the rollout of renewable energy is resistance on local levels. Aiming to address this issue, the German government introduced a classification for regional green electricity in 2019. A recent survey indicates that consumers appreciate this classification but also raises concerns of lacking transparency and credibility of its current communication. This study analyzes whether visual labels for regional green electricity can address this issue. Drawing on Signaling Theory, this paper studies how the label affects consumer attitudes and behavior and how familiarizing experiment participants with the label moderates its effects. We test the model by means of a multi-method lab experiment comprising eye-tracking and survey data. We find positive effects of the label with both objective (visual attention, time to decision) and subjective (stated trust) measures. Further, giving participants a briefing on the labels prior to the experiment moderates the labels' effects on visual attention and trust. These findings suggest that a regional green electricity label could provide a potent tool for policymakers to accelerate the transition towards a carbon neutral energy sector. [Display omitted] • German legislation introduced a classification for regional green electricity but consumer communication is being criticized. • This multi-method study evaluates how a visual label could address this issue, building on eye-tracking and survey data. • Findings suggest that labels are potent as they effectively alter consumer attitudes and behavior. • Building the label's brand is important as familiarity with the label is a critical success factor for such an initiative. [ABSTRACT FROM AUTHOR]

Zero‑carbon electricity is a pre-requisite for decarbonisation of the wider economy and many scenarios envisage rapid expansion of renewables. IEA estimates a need to double the annual rate of investment to 2030. A rapid transition to low carbon electricity creates a risk to investors because projects being financed now will generate their revenue in a zero‑carbon electricity system for which there is no track record of price formation. Although the cost of renewable power has fallen greatly, future revenues from renewables are still affected by market price risks that are often outside the control of generators. If risks are difficult to quantify, they may be mis-priced, leading to inefficient premiums being added to the cost of capital, which could increase the overall cost of the transition. In this context many countries around the world provide support for low carbon energy, such as the UK Contracts for Difference. In this paper we investigate exposure to price risk caused by uncertainty over the mix of technologies used to achieve decarbonisation, which we term 'transition risk', and how this varies under different technology mixes, and for different policy regimes. We show that exposing investors to transition risk could increase the cost of delivering the renewables needed for a zero‑carbon electricity system by around 25% or £7bn/year compared to policy options that reduce exposure to wholesale market price risk. The paper concludes that as long as transition risks remain high, de-risking policy mechanisms can help to minimise the overall cost of achieving net-zero. • We characterise the current stage of the low-carbon transition as a 'build phase', requiring large volumes of investment • Uncertainty over the final physical state of the decarbonised system causes significant financial risk to investors • 'Contracts for difference' (CfDs) help to manage this 'transition risk' and reduce the cost of capital for projects • Exposing projects fully to transition risk could increase costs by a third, and raise the cost of transition by £7bn per year [ABSTRACT FROM AUTHOR]

Germany is under increasing pressure to rapidly decarbonize its electricity system, while ensuring a secure and affordable electricity supply. In this context, energy storage systems (ESSs) can play a crucial role in enabling a high share of variable renewable electricity generation. To investigate the complex interplay of ESSs in the electricity system, bottom-up energy system optimization models have been utilized to create strategies for the decarbonization of electricity systems at minimum cost. Previous studies have used models to investigate the role of storage technologies in decarbonizing electricity systems. However, in most of them, key aspects pertaining to the optimal storage technology mix (what), the daily and seasonal operation of storage technologies (what), the timing of the investment (when), and their optimal placement (where) are omitted. In this work, we present MANGOelec, a model for the long-term optimal design of electricity systems that allows us to study all the what-where-when dimensions for ESSs. We apply the MANGOelec model to the German electricity system considering the horizon until 2050, as well as various scenarios to investigate the effects of several external factors like building rates of renewable generation technologies or grid expansion limitations on the optimal transformation pathways. The study results indicate that a mix of short- and long-term storage is needed, independent of external factors. For instance, battery storage potentials are close to fully exploited across all regions and the technology is solely used for daily operation. Hydrogen storage, on the other hand, is primarily installed in a small set of regions and operated exclusively as a seasonal storage option. Here, the results indicate that the demand for hydrogen storage capacity is substantial, reaching 2.7–5.9 TWh of hydrogen-based storage capacity in 2050 depending on the scenario. The results also suggest that independent of the storage technology chosen, their deployment commences after 2030 and is completed by 2045. In conclusion, the study shows that already existing ESSs provide sufficient flexibility at first but need to be expanded substantially after 2030 to enable a cost-optimal transition of the German electricity system. Moreover, it illustrates the need for ESSs in order to achieve the decarbonization goals of the German electricity system, which can provide valuable insights to energy planners and policy makers. • Role of energy storage systems in the German electricity system is investigated. • Modeling of daily and seasonal storage investments and operation in 2021–2050. • Quantification of regional and temporal patterns in energy storage installations. • High hydrogen-based seasonal storage demand in selected federal states is shown. [ABSTRACT FROM AUTHOR]

One of the main tools to achieve the promise of carbon neutrality is the energy transition. Reducing dependence on traditional energy and promoting the use of renewable energy drives changes in the energy sector and contributes to the energy transition. The building sector is strongly linked to energy consumption and retrofitting the building sector with natural gas energy is a positive energy efficiency strategy. This research aimed to determine the factors influencing social housing tenants in the Netherlands to participate in retrofits and to identify the differences among participants in their preferences. Using a stated choice experiment and discrete choice model, 380 effective social housing tenants in the Netherlands participated. The estimated Mixed Logit Model (MLM) reveals the preferences of social housing residents, and the Latent Class Model (LCM) indicates differences between latent groups. The results show that social housing residents are attracted by saving total housing costs, enhancing living comfort, providing a new bathroom, kitchen and toilet of individual houses and improving the neighbourhood environment. Meanwhile, they are resistant to the interference generated during the renovation process. These findings can be used to guide government and housing organisations in developing retrofit programs that align with the needs and preferences of social housing tenants. • Increasing social housing retrofit contributes to the energy transition. • Determine attributes in promoting tenants' interest in energy-efficiency renovations. • Captured the preference heterogeneity by a mixed logit model. • Observe heterogeneous preferences among latent class membership respondents. • Gain and hedonic motives exert key roles in attracting tenants' willingness to participate. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A high-resolution spatio-temporal energy demand simulation model is introduced. • Geographic demand variation is introduced by mapping of technology diffusion. • Implications on load profiles are analysed for large-scale uptake of heat pumps. • Demand side management potential for water and space heating is simulated. Abstract Localisation of energy technologies and policies is increasing the need for high-resolution spatial and temporal energy demand simulation modelling, which goes beyond annual and national scale. Increasing the temporal resolution is crucial for demand side management modelling or for the simulation of load profile changes due to the installation of new technologies such as heat pumps. Increasing the spatial resolution enables regional energy planning and capturing the spatial dynamics of drivers of energy demand. Yet regional and local energy grids are interconnected with national and continental networks, so to capture multi-scale effects, high resolution is required everywhere. A high-resolution bottom-up engineering energy demand simulation model is introduced, which projects energy demands both for a high spatial and high temporal scale and enables spatial explicit simulation of model parameters. The model is applied for exploring implications of the electrification of heat by a large-scale uptake of heat pumps for water and space heating in the United Kingdom and to simulate heat pump related demand side management opportunities. We simulate a change in peak electricity heating load of −0.4 t– 21.5 GW for 50% heat pump uptake for space heating demands across different scenarios resulting in an increase of total peak electricity demand of 3.3–31.2 GW (6.3–59.8%). The simulation results show considerable regional differences in change of electricity load factors (−17.2–8.4%) and peak electricity demands (−9.9–206.1%). The potential to reduce national electricity peak load with managed heat pump load profiles for heating is simulated to be 0.2–5.8 GW (0.4–11.1%). These results exemplify the importance of discussing heat-pump induced change in peak electricity demands within a scenario context. Including different drivers in energy demands and their variability considerably affects the scale of anticipated electricity peak demand. [ABSTRACT FROM AUTHOR]

Highlights • An overview of the state of the art in community energy storage (CES) is provided. • CES is conceptualized and analyzed as complex socio-technical system. • Responsibility in CES design and implementation is operationalized. • CES is not only technical but also social innovation. • The added-value of CES go beyond economic benefits to wider societal benefits. Abstract The decreasing cost of energy storage and increasing demand for local flexibility are opening up new possibilities for energy storage deployment at the local level. Community energy storage (CES) is expected to contribute positively towards energy transition while accommodating the needs and expectations of citizens and local communities. Yet, the technological and societal challenges of integrating CES in the largely centralized present energy system demand for socio-technical innovation. In this article, we develop and discuss several configurations of CES. Applying system innovation and socio-technical transition frameworks and conceptualizing CES as a complex socio-technical system, different dynamics of CES in the energy systems such as coordination and interaction among actors and components of CES and the larger energy system is explored. The responsible research and innovation (RRI) framework can provide a new discourse in design and implementation of CES, facilitating the transition to a sustainable, reliable, inclusive and affordable future energy system. [ABSTRACT FROM AUTHOR]

Highlights • Analysis of electricity demand in neighbourhoods, districts and municipalities. • Data-driven classification of electricity demand profiles of nearly 15000 urban areas. • Three statistically different urban area types found: residential, business and mixed. • Urban area types differ in terms of demand profiles and energy user composition. • Often-used residential-type demand represents only a minority of analysed areas. Abstract Cities and communities worldwide are seeking to become more sustainable by transitioning to renewable energy resources, and by introducing electric transportation and heating. The impact and suitability of such technologies for a given area heavily depend on local conditions, such as characteristics of local demand. In particular, the shape of a local demand profile is an important determinant for how much renewable energy can be used directly, and how charging of electric vehicles and use of electric heating affect a local grid. Unfortunately, a systematic understanding of local demand characteristics on different urban scales (neighbourhoods, districts and municipalities) is currently lacking in literature. Most energy transition studies simplify local demand to household demand only. This paper addresses this knowledge gap by providing a novel data-driven classification and analysis of demand profiles and energy user compositions in nearly 15000 neighbourhoods, districts and municipalities, based on data from the Netherlands. The results show that on all urban scales, three types of areas can be distinguished. In this paper, these area types are termed "residential", "business" and "mixed", based on the most prevalent energy users in each. Statistic analysis of the results shows that area types are pairwise significantly different, both in terms of their profiles and in terms of their energy user composition. Moreover, residential-type demand profiles are found only in a small number of areas. These results emphasise the importance of using local detailed spatio-temporal demand profiles to support the transition of urban areas to sustainable energy generation, transportation and heating. To facilitate the implementation of the obtained insights in other models, a spreadsheet modelling tool is provided in an addendum to this paper. [ABSTRACT FROM AUTHOR]

Multi-energy systems can improve the performance of traditional energy systems, where energy carriers and sectors are decoupled, in terms of economic, environmental, and social sustainability, measured as the total cost of energy, emissions per energy demand, and self-sufficiency, respectively. This study assesses the impact that policy mechanisms can have in enabling these sustainability benefits. A mixed-integer linear problem is implemented, which optimizes the design and operation of multi-energy systems to minimize the total annual cost of supplying energy to residential end-users. Four policy types are tested for a Swiss case study, namely a feed-in tariff, an investment support mechanism, a carbon tax, and a regulation-based carbon cap. To assess how the policy impact varies between different end-users, we distinguish between passive consumers, that cannot access subsidies, and prosumers, who can. In our case study, subsidies, such as a feed-in tariff and an investment support mechanism, decrease the cost of energy for prosumers by up to 10%, but increase the cost for consumers by up to 33%, which points to the need of including energy equity considerations when designing policies. The carbon cap and the carbon tax impact all end-users equally, and tend to perform better in terms of reducing emissions. Emission reductions of up to 60% and 39% are observed for the carbon cap and carbon tax, respectively. The feed-in tariff and carbon cap perform best in fostering self-sufficiency and achieve balanced energy autonomy for high policy levels, revealing a trade-off between the different sustainability dimensions. [Display omitted] • Economic, environmental, social sustainability of residential multi-energy systems. • Assessment of the impact of policy schemes on all sustainability dimensions. • Financing subsidies via levy on retail electricity leads to unjust cost allocation. • Analysis of synergies and trade-offs between sustainability dimensions. • Carbon cap and carbon tax are most cost-efficient for decarbonization. [ABSTRACT FROM AUTHOR]

Water Distribution Networks (WDNs) represent a noteworthy field for possible implementation of Small Hydropower (SHP), by replacing Pressure Reduction Valves (PRV) with turbomachines, in particular Pump as Turbines (PaTs), to control and regulate the pressure, while harvesting energy otherwise wasted. Different models were developed to predict the performance and select the positioning of the PaTs for the maximum energy recovery but most of them neglect practical aspect such as: power grid limitations and optimal harvesting strategy. In this framework, we intend to propose a new method to select a PaT, defining its optimal working point, by introducing an energy exploitation coefficient. The proposed methodology is based on the experimental results of a real PaT tested in the high capacity hydraulic laboratory at Polytechnic University of Bari. Firstly, the selected commercial centrifugal pump was tested in both pump and turbine modes. Then, three different approaches, for the Best Efficiency Point (BEP) selection, are described and compared in terms of energy exploitation and capacity factor for a WDN. The first consists of selecting the BEP at the average flow rate, the second one considers the probability distribution of the flow rate and the corresponding available hydraulic energy, whereas the latter is based on the highest energy harvesting. By applying energy production, economic and environmental analyses, the new proposed methodology, based on the third approach, shows a remarkable advantage in terms of exploited energy. Indeed a remarkable 60% energy recovery is achieved with 334 ton CO 2 /year avoided. Furthermore, the impact of the electrical motor on the maximum power generation (cut-off) is considered. Eventually, useful insights for the future PaT selection and installation are discussed. • Characterization of a PaT selected to work at the mean flow rate of a WDN. • Two new approaches are proposed for PaT selection, given real data of PaT and WDN. • Methods comparison: mean flow rate, max available energy and max energy recovery. • Runaway and blocked rotor curves, affinity laws and technical needs are considered. • Over 3.5 MWh/day, a 60% energy recovery is achieved with 334 ton CO 2 /year avoided. [ABSTRACT FROM AUTHOR]

The integration of large shares of wind and solar power into the power system benefits from transmission network expansion. However, the construction of new power lines requires long planning phases and is often delayed by citizen protests. As an non-invasive alternative, Dynamic Line Rating (DLR) offers the potential to leverage the existing grid by dynamically adjusting the transmission line capacities to the prevailing weather conditions. In this study, we present the first investment model that includes DLR in a large-scale power system with real-world network data and a high temporal resolution. Using Germany as an example, we show that a system-wide integration of DLR improves the integration of existing and additional renewables while reducing grid congestion. The evolving synergies between DLR and increased wind generation result in total cost savings of about 3% of all system costs for a scenario with 80% renewable power production, mainly due to reduced storage and solar capacity needs. If considering a fully decarbonized electricity system, the cost savings from DLR amount to up to 5.5% of the system costs, i.e. 4 billion Euro per year. Our results underscore the importance of a rapid implementation of DLR in power systems to support the energy transition and relieve grid congestion. • System effects of Dynamic Line Rating (DLR) on the German power grid are investigated. • DLR boosts power transmission capacity by accounting for weather-related cooling effects. • System wide application of DLR in Germany leads to significant system cost reduction. • Optimal network layout with DLR requires less energy storage. • DLR is a cost-effective measure in the transformation to a decarbonized power system. [ABSTRACT FROM AUTHOR]

Highlights • Energy justice is won through the exnovation of carbon intensive energy structures. • Exnovation takes away burdens which result from fossil-fueled energy production. • Organized publics push for exnovation and by so doing enhance energy justice. • Organized publics push for exnovations in transparent and accountable ways. Abstract Whereas campaigners for energy justice frequently seek to achieve decarbonization through innovation, little light has been shed on how energy justice might be won through the removal of carbon intensive energy structures—a process known as exnovation, which is the opposite of innovation. Whereas practicing exnovation to decarbonize energy systems and thus achieving greater energy justice appears to be a promising approach, it remains a challenge in light of the deep incumbency of established fossil-fuel-based energy industries. Using the example of Germany, which represents such a setting of deep fossil fuel incumbency, this article compares two organizations aiming to achieve energy justice via exnovation when formal policy-making toward decarbonization seems impossible. Offering a perspective on strategies for energy justice, the article identifies the repertoires of contention of two organizations. This concerns knowledge dissemination, symbolic protest, and rule compliance, which can be understood as soft (non-obligatory) policy instruments to bring about exnovation. The article then discusses the relationship between exnovation and intra- and intergenerational energy justice. It concludes that the means of contention analyzed here are successful in divesting and in stopping the construction of planned coal plants. [ABSTRACT FROM AUTHOR]

Designing future energy scenarios is an important topic to energy planners. As designing future optimized scenarios is a multi-objective optimization problem; therefore, it is required to identify trade-off scenarios (Pareto-front) in order to optimize conflicting objectives. In this study, three Pareto-fronts are identified for designing future scenarios for Val di Non (VdN) for three different time horizons. As the community has to reach different emission targets in different time horizons, it is require to select the optimized scenarios that fulfill the targets. In this regards, we propose a new approach for selecting scenarios based on maximizing decision space diversity in order to provide a diverse set of scenarios to the decision makers. The technique is tested on optimized scenarios of VdN and three sets containing 10 diverse scenarios for different time horizons are selected. Moreover, a smooth transition (in terms of decision variables) is desirable when having a transition from a scenario from one time horizon to a consecutive time horizon. A novel method is proposed to choose scenarios from the sets for a smooth transition based on minimizing distances among the scenarios. The approach is applied on VdN where transient scenarios are identified among different possible optimized scenarios. [ABSTRACT FROM AUTHOR]

There is more or less consensus around the problems related to the existing energy systems. Most focus has been on the negative environmental effects of using fossil fuels. Many papers and reports conclude that renewable energy has the potential to run the world and the technology needed to do so is available. An important question is: why such a big potential is only marginally utilized? This paper analyzes the reasons why we ended up in today’s energy systems. In order to develop pathways for change, scenarios can be used to support decision making involving all key actors in the society. The scenarios must be established on the comparison between different primary energy sources at a fundamental thermodynamic level. The paper proposes the principles for evolutionary forecasting scenarios (EFS) with two sets of criteria to investigate technology development and long-term energy transition. Primary criteria are based on the first and second law of thermodynamics. They can be used to simulate the development of energy transformation technologies. The result implies that engineers must consider the system level when they develop energy technology. The secondary criteria, which are mainly based on subjective-values, should be used for evaluating different roadmaps obtained from these simulations. It is important that the evaluations of scenarios are carried out in broad dialogue processes with key actors in order to make the roadmaps easy to implement and follow up in practice. [ABSTRACT FROM AUTHOR]

• A novel hybrid concentrating photovoltaic-pumped two-phase loop system is modeled. • A multi-parameter optimization problem with several constraints is formulated. • System thermodynamic under changing solar irradiation intensity is optimized. • Efficient PV cell cooling and waste heat utilization are simultaneously addressed. • The hybrid system brings about 6.9% overall exergy efficiency improvement. Linear concentrating photovoltaic (LCPV) is a promising technology to increase the power density of the solar power generation system. However, the efficiency of LCPV is highly undermined due to inefficient thermal management. Active cooling-based thermal management via a mechanically pumped two-phase loop (MPTL) system can facilitate the heat transfer across LCPV. However, efficient thermal management and waste heat utilization are still challenges due to high heat flux, complex two-phase dynamics, strong internal couplings and dynamic external environment. To simultaneously address these crucial parameters, this paper presents a mathematical model for the hybrid LCPV-MPTL system, including two-phase flow and other auxiliary components. An iterative solution algorithm is proposed to derive the steady-state values under different conditions. Simulations under four operating conditions have been performed based on the developed model, indicating the effects of each parameter. A multi-parameter optimization problem with several constraints is formulated by taking the changing solar irradiation intensity and other environmental factors into account, maximizing the net output of electrical energy while satisfying the safety and operational requirements. Finally, exergy analysis is carried out, showing that the hybridization of MPTL with LCPV can improve its overall exergy efficiency by 6.9%, resulting in high performance PV with greatly controlled cell temperature. In all, the scientifically viable thermal management solution and the underlying design guidelines can be inferred for industrial applications. [ABSTRACT FROM AUTHOR]

We introduce a bottom-up modeling framework that allows both the decentral and central planning of an integrated energy system with high shares of renewable generation. We take into account the distribution network structure as well as the changing local consumption due to high electrification rates of building heat supply and the transportation sector. This approach allows the analysis of pathways in between a cost-optimal system design and an equitable spatial distribution of renewable generation and battery storage capacities within the system. In addition, we investigate the optimal combination of short- and medium-term battery storage technologies, namely lithium-ion and redox flow batteries. Our results for the case of Baden-Wuerttemberg, a state in southern Germany, show that a central planning of renewable generation and storage capacity requirements results in lower levelized costs of electricity than a decentral design, as expected. However, pathways in between the two planning paradigms can lead to a more equitable inclusion of communities in the energy transition at reasonable cost increases, which might increase acceptance. The results of this study are of significance for policy-makers and local stakeholders, as they must address the conflicts that arise on a local level when expansion targets are planned centrally. • Framework for modeling local electricity consumption, considering structural changes • Optimal combination of short- and medium-term storage technologies (LiB and RFB) • Costs, storage and renewable capacity requirements for decentral vs. central planning [ABSTRACT FROM AUTHOR]

• Novel data-driven platform to predict and evaluate energy transition policies. • Quantitatively evaluate impacts of energy transition policies. • Make effective forecasting and timely adjustment in energy policies. • Powerfulness of platform is demonstrated in representative metropolitan regions. • Adjustment recommendations for different stakeholders in energy industry. To meet widely recognised carbon neutrality targets, over the last decade metropolitan regions around the world have implemented policies to promote the generation and use of sustainable energy. Nevertheless, there is an availability gap in formulating and evaluating these policies in a timely manner, since sustainable energy capacity and generation are dynamically determined by various factors along dimensions based on local economic prosperity and societal green ambitions. We develop a novel data-driven platform to predict and evaluate energy transition policies by applying an artificial neural network and a technology diffusion model. Using Singapore, London, and California as case studies of metropolitan regions at distinctive stages of energy transition, we show that in addition to forecasting renewable energy generation and capacity, the platform is particularly powerful in formulating future policy scenarios. We recommend global application of the proposed methodology to future sustainable energy transition in smart regions. [ABSTRACT FROM AUTHOR]

In order to analyse international effects of national energy policies, we investigate the spill-over effects of the German Energiewende on the Dutch power market, which is closely connected to the German market. We estimate the impact of the German supply of wind and solar electricity on the Dutch day-ahead price of electricity and the utilisation of the conventional power plants. We take cross-border capacity constraints into account and use hourly plant-level data over 2006–2014. We find that the price elasticity of German wind on Dutch day-ahead prices is −0.03. However, this effect vanishes when the cross-border capacity is fully utilised. We find a modest negative impact on the utilisation of the Dutch power plants. As such, we conclude that the German Energiewende has had modest spill-over effects to the Dutch market. The recent dramatic performance of the Dutch gas-fired plants can be attributed to the changes in the relative prices of coal versus natural gas. We conclude that national energy policies in one country do not necessarily strongly affect neighbouring markets in case of constrained cross-border capacities. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions and energy data are used to show the rationale for global hydrogen trade. • We identify countries likely to import or export hydrogen, highlighting cost differences. • Our international trade model highlights renewable energy, carbon policies, and market distances. • Numerical simulations show a market shift from fossil-based to renewable energy-based hydrogen. Existing research offers insights into production, operation, and cost efficiencies for the expanding variety of hydrogen (H 2) technologies, suggesting that not a single one, but a portfolio of technologies, may be competitive in emerging markets. In turn, policy studies point out that economic and market conditions may be altered to promote certain options, for instance, renewable energy-based "green" hydrogen over fossil fuel-based alternatives. Such regionally oriented analyses, however useful, do not provide a perspective on a global market or international trade development, which is critical for infrastructure development, demand expansion, and supply commitments. This paper aims to fill this gap by addressing two interrelated questions: 1) what are the prerequisites for hydrogen trade in the context of a global transition to carbon neutrality and 2) how will regional energy system characteristics and regulations affect the growth and the "color" of the hydrogen market? Focused on green H 2 , we start our analysis with the evaluation of renewable energy generation potential of individual countries to identify geographic and economic factors and constraints for regional H 2 development. Revealing resource-rich countries with green H 2 export potential and resource-poor regions, likely green H 2 importers, we turn to energy price data showing why green H 2 is likely to face competition from other H 2 colors. We capture those insights with an international hydrogen trade model, focusing on H 2 supply diversity and factors determining local demand, including prices for renewable energy versus fossil fuels, emission constraints, and cost associated with carbon utilization and or disposal. Incorporating supply and demand drivers within a common framework enables us to embrace the complexity and to understand the discrepancies in existing H 2 trade projections. We use the model to explore the role of carbon regulations, rate of renewable energy adoption, transportation costs, and input energy prices in the future H 2 market evolution. To gain further insights into the future trade dynamics, we perform simulations mimicking the emerging German market. Hence, our work provides a unique comprehensive energy system perspective at the global scale, supported by analytical and empirical data analyses. [ABSTRACT FROM AUTHOR]

• Weather factors are crucial for risk assessment in small renewable energy projects. • A methodology is proposed to price an insurance contract that hedges weather risk. • An analog of financial VaR is estimated for solar radiation using quantile regressions. • The methods proposed are applied to the illustrative case of 40 European cities. • The study contributes to the mitigation of VRE projects' volumetric risk. We propose a methodology to price an insurance contract designed to hedge the volumetric risk associated with weather conditions. Our methodology is based on conditional quantile regressions and adapts Value at Risk (VaR) and Expected Shortfall statistics from the literature on financial econometrics. In our empirical application, we use actual daily meteorological and radiation data for 40 European cities in 13 countries, from April 1, 2011, to December 31, 2021, and calculate the value of the annual insurance premium under reasonable assumptions on the technology of the solar panels and expected energy demand. We consider variables such as temperature, wind speed, and precipitation in our calculations. Our results for the different cities in our sample show that due to the nonlinear impact of weather (mainly temperature and precipitation) on the expected generation losses, it is appropriate to use quantile regressions to calculate the VaR of radiation, conditional on weather factors. Our insurance premium calculations also present a high degree of variation across European, which indicates that risk-diversification opportunities of catastrophic risk due to weather conditions faced by insurance companies exist. This variation is explained by different weather conditions, model adjustment, and the average price of electricity. [ABSTRACT FROM AUTHOR]

Renewable energy communities (RECs) are prominent initiatives to provide end consumers an active role in the energy sector, raise awareness on the importance of renewable energy (RE) technologies and increase their share in the energy system thus reducing greenhouse gas (GHG) emissions. The economic viability of RECs though, depends on multiple interdependent factors that require careful examination for each individual context. This study aims at investigating the impact of electricity tariffs, ratio of electrification of heating and transportation sectors, prices of RE technologies and storage systems, and internal electricity exchange prices on the annual cost for electricity provision of a REC and its GHG emissions. A mixed-integer linear model is developed to minimize energy provision costs for a representative REC in Flanders, Belgium. The results indicate that RECs have the potential to reduce these costs by 10 to 26% and emissions by 5 to 13% compared to business-as-usual. The cost reduction depends on the type of electricity tariffs and the level of uptake of flexible assets such as heat pumps and electric vehicles. The shift towards a higher power component in the electricity tariff makes electricity storage systems more attractive, which leads to higher electricity self-consumption. The introduction of flexible assets adds the possibility to shift demand when tariffs are lower and makes higher installed capacities of photovoltaic systems economically viable due to the increase in the total electricity demand. However, RECs cost reduction compared to individual smart-homes amounts to only 4%–6% in the best cases. Uncertainties stemming from the costs of setting up a REC may reduce the estimated benefits. • First evaluation of economic viability or renewable energy communities in Flanders. • A multi-energy mixed-integer linear model is used to find the cost-optimal solution. • Electricity tariffs and uptake of flexible assets are the most influential factors. • Communities can achieve a cost-reduction up to 26% against business-as-usual cases. • Only 4%–6% cost-reduction when compared against individual prosumers. [ABSTRACT FROM AUTHOR]

As part of its energy transition strategy, China has set ambitious targets for increasing the contribution of renewable energy and, in particular, of wind power. However, the Chinese power sector has not undergone the necessary reforms to facilitate the integration and absorption of a larger share of variable renewable energy. This is evident from the difficulties in absorbing wind power from already commissioned wind farms and the resultant curtailment of wind power. Pumped storage hydroelectricity (PSH) is a flexible power source that can facilitate higher penetration levels of wind power as well as complement China’s growing nuclear power capacity. However, regulatory policy constraints have restricted the effective utilization of existing PSH capacity and discouraged investment in new PSH capacity. This paper examines these constraints and assesses the likely impact of new policies designed to address them. Finally, policy recommendations and concluding remarks are provided. This paper contributes to the literature on renewable energy integration from a new perspective. The lessons from China are relevant to other countries going through the energy transition. [ABSTRACT FROM AUTHOR]

• We estimated the job creation of Japan's energy transition towards deep mitigation. • We extended PE IAMs into an IO framework and investigated multiple scenarios. • Positive total job creation in 2030 but workforce shortage in 2050 may occur. • More employment would be induced in non-electricity and manufacture sectors. • Over 30% of induced employment would be overseas. Energy transition towards carbon neutrality by 2050 in Japan will involve renewable energy development and a shift from fossil fuel energy. Investigating the domestic employment level in response to such energy transition and their implications of different decarbonization scenarios is urgently needed. We introduced the results from partial equilibrium (PE) integrated assessment models (IAMs), which provided a more comprehensive representation of power generation mix and capacity (based on a bottom-up modeling approach), to the input–output (IO) framework, which served as an efficient tool for mapping inter-sectoral transactions in the macroeconomy (based on a top-down modeling approach). By this approach, the uncertainties among different Japan national decarbonization scenarios can be investigated. We estimated the job creation in manufacturing sectors, construction sectors, electricity supply sectors, and all other sectors induced by the investment in the introduction of renewable energy capacity introduction and all power generation activities. The results show that: i) positive numbers in total job creation may occur in 2030 (e.g., under the default scenario reaching 80% emission reduction by 2050), as the job creation in the manufacture and construction of renewable related activities will exceed the job losses in mining, construction of thermal power, and thermal power generation activities; ii) however, such job creation will dramatically increase in 2050, leading to possible workforce shortages within Japan; iii) over 30% of the employment in non-electricity and manufacture sectors may be induced overseas in 2050. Compared with high renewable potential pathways, the long-term labor supply issues could be eased under low energy service demand pathways in Japan. [ABSTRACT FROM AUTHOR]

In the energy transition context, islands are identified as particularly challenging regions due to their isolation, and energy dependence; while their excellent renewable resource and rapid growth makes them exceptionally interesting test cases. With the growing number of countries targeting 100% renewable penetration during the next decades, it is important to assess not only how to do so, but also whether we should. This paper focuses on the perspective of a generally overlooked set of regions; island developing nations. Their common challenges and energy policies are exemplified with a comprehensive generation and storage expansion planning (GSEP) for the island of São Vicente, Cape Verde. Formulated as an optimisation problem with hourly resolution, the GSEP minimises investment, maintenance, operation and emissions costs over a 20 year horizon from 2021. The extreme seasonal dependence of wind and solar resources is captured along with the operational dynamics of the generation and storage. Three scenarios are defined, one Business As Usual (BAU) keeping the current operational paradigm, another, Green, aligned with the local government goals, targeting 50 and 100% renewable shares in 2030 and 2040, and, lastly, one finding the Optimal. To reduce uncertainty influence, we consider three load growth levels for each scenario, defined based on expectations from national and international sources, corresponding to 1, 3 and 5%. The robust analysis obtained by combining scenarios and load levels provides a thorough view of Cape Verde's energy system to consider in future energy policy design. Green is the most expensive, BAU represents a 7% cost reduction, while Optimal a 30%, in addition to providing 90% renewable penetration, significant emissions reduction, and enough flexibility to modify the planning course if needed. [Display omitted] • Cape Verde can meet its goal of 50% renewables today by integrating energy storage. • A 100% Renewable System is achieved from 2026, with a 20 year cost from 68 to 107 M€. • Current paradigm doubles emissions in 20 years and costs ranges from 71 to 107 M€. • The optimal configuration achieves 90% renewable shares with a cost from 50 to 75 M€. • Solar is the main driver of the renewable transition, supported by wind and storage. [ABSTRACT FROM AUTHOR]

• Electricity, the most direct and effective use of RES, is in center of energy transition. • An interdisciplinary procedure suitable for the planning of RES is presented. • Key points and procedures for the assessment of large-scale RES installation is presented. • Simulation on Eygiption case shows the technical and economical viability. Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international, regional, and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, "RES-PLAT" 1 1 https://res-plat.est.polito.it. , we demonstrate the scheme in a case study in Egypt, which evaluates the impacts and benefits of a large-scale RES expansion. 2 2 The short version of the paper was presented at Applied Energy Symposium: MIT A+ B, August 13–14, Boston. This paper is a substantial extension of the short version of the conference paper. [ABSTRACT FROM AUTHOR]

Highlights: [•] Grid capacity problems due to EV integration expected in 2015 in urban areas. [•] A GIS-based simulation assesses risks associated with large scale EV integration. [•] Risks are assessed on neighbourhood level using GIS data. [•] Grid operators can use our method to improve investment planning. [ABSTRACT FROM AUTHOR]