Search Results (2,118)

With the widespread adoption of renewable energy, distribution grids face increasing challenges in efficiency, safety, and economic performance due to stochastic generation and fluctuating load demand. Traditional operational models often exhibit limited adaptability, weak coordination, and insufficient holistic optimization, particularly in early-/mid-stage distribution planning where feeder-level network information may be incomplete. Accordingly, this study adopts a planning-oriented formulation and proposes a distributed energy storage system (DESS) planning strategy to enhance distribution network resilience under high uncertainty. First, representative wind and photovoltaic (PV) scenarios are generated using an improved Gaussian Mixture Model (GMM) to characterize source-side uncertainty. Based on a grid-based network partition, a priority index model is developed to quantify regional storage demand using quality- and efficiency-oriented indicators, enabling the screening and ranking of candidate DESS locations. A mixed-integer linear multi-objective optimization model is then formulated to coordinate lifecycle economics, operational benefits, and technical constraints, and a sequential connection strategy is employed to align storage deployment with load-balancing requirements. Furthermore, a node–block–grid multi-dimensional evaluation framework is introduced to assess resilience enhancement from node-, block-, and grid-level perspectives. A case study on a Zhejiang Province distribution grid—selected for its diversified load characteristics and the availability of detailed historical wind/PV and load-category data—validates the proposed method. The planning and optimization process is implemented in Python and solved using the Gurobi optimizer. Results demonstrate that, with only a 4% increase in investment cost, the proposed strategy improves critical-node stability by 27%, enhances block-level matching by 88%, increases quality-demand satisfaction by 68%, and improves grid-wide coordination uniformity by 324%. The proposed framework provides a practical and systematic approach to strengthening resilient operation in distribution networks. Full article

Given global efforts to promote sustainable energy transitions, this study investigates how the deployment of renewable energy technologies (RETs) relates to multidimensional societal welfare and provides empirical evidence on these linkages in Lithuania. The purpose of the study is to provide an integrated, Lithuania-specific assessment of how economic, social, and environmental determinants associated with RET deployment are related to multiple dimensions of societal welfare. Drawing on scientific literature, an integrated indicator framework is developed that links the economic, social, and environmental determinants of renewable energy technology (RET) deployment to six societal welfare dimensions, as defined by the Lithuanian Quality of Life Index. Using official Lithuanian statistics for 2020–2024, a standardized panel dataset is constructed and Pearson correlation analysis and multiple linear regression are applied using aggregated determinant categories, with model assumptions verified using the Breusch–Pagan and Durbin–Watson tests. Correlation results show very strong positive links between RET intensity indicators and key economic welfare measures (for example, wages, GDP per capita, foreign direct investment, disposable income), with absolute correlation coefficients typically between 0.90 and 0.99 (p < 0.05), and strong negative correlations between air-pollution indicators and GDP, income, FDI, and education (correlation coefficients between −0.96 and −0.90; p < 0.05). The results indicate that RET-related economic determinants have a statistically significant positive effect on the societal welfare dimensions of material living conditions; entrepreneurship/business competitiveness; and public infrastructure, living-environment quality/safety. Social factors also significantly support the societal welfare dimensions of entrepreneurship/business competitiveness and public infrastructure, living-environment quality/safety. In the retained regression models, explanatory power is very high (R² between 0.91 and 0.999), with positive and statistically significant coefficients for the economic determinant (regression coefficients between 0.43 and 0.96; p < 0.05) and negative, statistically significant coefficients for the environmental determinant in the entrepreneurship and public-infrastructure dimensions (regression coefficients between −1.13 and −1.51; p < 0.05). Environmental determinants are associated with lower air pollution but show negative effects on the societal welfare dimensions of entrepreneurship/business competitiveness and public infrastructure, living-environment quality/safety. Overall, the findings suggest that RET deployment is an important correlate of the economic aspects of societal welfare, while environmental and social dimensions display more complex, domain-specific impacts. Full article

This study investigates the determinants of green energy penetration in the Next Eleven (N-11) economies over the period 2000–2022, with a particular focus on the roles of foreign direct investment (FDI), green transition, governance quality, industrial growth, and urbanization. The primary objective of the study is to assess how investment flows, structural transformation, and institutional capacity jointly shape the adoption of renewable energy in fast-growing emerging economies. To achieve this goal, the study employs a second-generation panel econometric and machine-learning framework that accounts for cross-sectional dependence, slope heterogeneity, and long-run equilibrium relationships. Specifically, cross-sectional dependence and slope homogeneity tests are conducted, followed by CADF and CIPS unit root tests and the Westerlund cointegration approach. Long-run effects are then estimated using Partialing-Out LASSO and Cross-Fit machine-learning estimators, complemented by SHAP analysis to interpret nonlinear and heterogeneous effects. The results indicate that green transition, governance quality, and urbanization significantly promote green energy penetration. In contrast, FDI and industrial growth exert adverse effects, reflecting carbon-intensive investment and production structures. The findings highlight the importance of coordinated investment strategies, institutional strengthening, and urban planning in accelerating renewable energy transitions in emerging economies. These results provide policy-relevant insights for achieving sustainable energy development while supporting long-term economic growth in the N-11 countries. Full article

Hydrogen has emerged as a cornerstone of global decarbonisation strategies, offering a flexible pathway to reduce dependence on fossil fuels and accelerate progress towards net-zero targets. However, the development of a globally integrated hydrogen economy remains uneven, reflecting disparities in renewable energy potential, infrastructure readiness, investment capacity, and policy commitment. To better understand these differences and the barriers they create, this study undertakes a comprehensive comparative assessment of the global hydrogen supply chain encompassing resources, production, storage, transport, and end-use applications. Further, a structured analytical framework comprising ten principles and twenty-nine sub-factors was developed to evaluate national hydrogen policies, technological readiness, and enabling conditions across twenty-six countries. The results show that the United States, China, Japan, South Korea, and Germany lead global progress, while many countries remain at an early stage of engagement. These findings further inform persistent regional asymmetries and emphasise the need for stronger international coordination. Drawing on these findings, the paper advances targeted policy and research recommendations to lower production costs, expand storage and transport capacity, and harmonise regulatory frameworks, thereby defining a coherent pathway towards a secure, cost-competitive, and equitable global hydrogen economy by 2050. Full article

Grid-integrated energy service (GIES) projects are characterized by strong cross-energy coupling and long investment horizons, resulting in multidimensional and nonlinear risk profiles. To address these challenges, this study develops an indicator-based risk evaluation framework by integrating an entropy–back-propagation (BP) combined weighting method with fuzzy matter-element theory. A 30-indicator system covering economic, environmental, and safety and reliability dimensions is constructed to support systematic risk assessment. The entropy–BP scheme combines data-driven objectivity with nonlinear correction, producing stable and interpretable indicator weights, as confirmed through robustness tests based on indicator removal and data perturbation. A real-world GIES project in East China is used as a case study. The results show clear risk grade differentiation among alternative scenarios and identify key risk drivers related to renewable energy integration, investment structure, and energy supply reliability. The proposed framework provides effective decision support for GIES project planning and risk management. Full article

Digital platforms are one of the main forms of media used by cultural and creative industries (CCIs) to communicate sustainability, yet the alignment between institutional strategies and online narratives remains insufficiently explored. This study investigates how ten Greek cultural institutions—including museums, performing arts organizations, and cultural centers—represent their sustainability efforts online. A mixed-methods approach combined organizational mapping, content analysis of 1761 Facebook posts (January–September 2025), and targeted semi-structured interviews with four communication professionals within the sample. Results show a pronounced emphasis on social sustainability, highlighting accessibility, education, and community engagement, while environmental sustainability is under-represented despite significant investments in energy efficiency, renewable energy, and waste management. Economic sustainability receives moderate attention, primarily framed through transparency. Interviews reveal that institutions face challenges in translating environmental initiatives into compelling digital narratives due to audience preferences, storytelling limitations, and resource constraints. Findings also indicate that strategic sophistication varies according to organizational scale, governance, and capacity. By linking institutional practices with their online representation, this research provides insights into the communication–practice gap and offers guidance for managers and policymakers to foster more balanced, authentic, and multidimensional sustainability storytelling in the cultural sector. Full article

This study investigates a water–energy investment in the Consorzio di Bonifica della Romagna Occidentale (Northern Italy) over the period 2015–2022, analysing how integrated irrigation and energy infrastructures can support agricultural resilience. In this area, pressurised irrigation systems are increasingly replacing traditional gravity-fed networks, enabling precise water distribution. However, their energy intensity raises operational costs and exposure to volatile electricity prices. To address these challenges, the research evaluates the coupling of pressurised irrigation with floating photovoltaic (PV) systems on irrigation reservoirs. Using plot-level economic data for vineyards and orchards, the analysis shows that, although pressurised systems entail higher costs in terms of Relative Water Cost (RWC) and Economic Water Productivity Ratio (EWPR), integrating them with PV production significantly improves economic performance. The findings show an average reduction in RWC of 1.44% for vineyards and 5.52% for orchards, and an average increase in EWPR of 38.51 units for vineyards and 24.81 units for orchards. This suggests that combining efficient irrigation systems with renewable energy could represent a viable pathway toward more sustainable water management. Policy implications may concern incentives for joint water–energy investments, adjustments to zero-injection rules, and broader reforms in agricultural, energy, and environmental policies. Full article

The development of renewable energy has emerged as a cornerstone of sustainable economic transformation, offering a pathway to reduce carbon dependence and enhance long-term energy security. As a result, this study examines the influence of supply chain digitalization, economic growth, and environmental stringency policies on renewable energy consumption (REC) across 33 OECD countries from 2000 to 2021. Using the Method of Moments Quantile Regression (MMQR) approach, the research provides robust, distribution-sensitive insights into how these factors shape renewable energy dynamics. In addition to the main variables, financial development and economic globalization were included as control variables to capture broader macroeconomic effects. The empirical results reveal that supply chain digitalization exerts a negative and consistent influence on REC across all quantiles, suggesting that technological advancement within supply chains may still be heavily dependent on non-renewable energy inputs. Conversely, environmental stringency policies demonstrate a positive and significant impact on REC at all quantiles, indicating that stricter environmental regulations effectively drive the transition toward cleaner energy sources. However, the effect of economic growth varies across quantiles, reflecting a nonlinear relationship—fostering renewable energy use in some instances while increasing conventional energy demand in others. Among the control variables, economic globalization enhances REC, implying that greater international integration facilitates technology transfer and access to green innovations. In contrast, financial development negatively affects REC, suggesting that current financial systems may still prioritize fossil fuel investments. Overall, the study emphasizes the need to align digital transformation strategies, financial reforms, and policy frameworks to strengthen renewable energy development and ensure a sustainable, low-carbon future across OECD nations. Full article

Renewable energy investment evaluation continues to rely predominantly on techno-economic and environmental criteria, while equity-related considerations remain weakly embedded within formal decision-support frameworks. Although recent research increasingly acknowledges social impacts, spatial constraints, policy uncertainty, and financing structures, these dimensions are rarely integrated in a systematic and operational manner into investment appraisal. This paper addresses this gap by advancing an equity-oriented conceptual framework for renewable energy investment evaluation. Using an integrative literature review combined with thematic analysis, the study synthesises insights from techno-economic assessment, multi-criteria decision-making, energy justice scholarship, and equity-focused modelling studies. The analysis demonstrates that existing evaluation approaches inadequately capture distributional impacts, accessibility constraints, differentiated vulnerability, and equity-adjusted risk. In response, the proposed framework systematises these equity dimensions and embeds them directly into the core logic of investment evaluation alongside conventional criteria. By consolidating fragmented research insights into a coherent evaluative structure, the study contributes to the literature by clarifying how equity can be operationalised within renewable energy investment decision-making. The framework provides a foundation for future empirical applications and supports more socially responsive and analytically robust investment evaluation. Full article

This study critically examines the sectoral dynamics of renewable energy (RE) adoption across the EU-27 from 1990 to 2023, addressing the persistent gap between electricity generation and end-use sectors. Utilizing Eurostat energy balance data, the research employs a robust multi-methodological framework. We apply the Logarithmic Mean Divisia Index (LMDI) decomposition to isolate driving factors, and the Self-Organizing Maps (SOM) of Kohonen to cluster countries with similar transition structures. Furthermore, the Method of Moments Quantile Regression (MMQR) is used to estimate heterogeneous drivers across the distribution of RE shares. The empirical findings reveal a sharp dichotomy: while the share of renewables in the electricity generation mix (RES-E-Renewable Energy Share in Electricity) reached approximately 53.8% in leading member states, the aggregated share in the transport sector (RES-T) remains significantly lower at 9.1%. This distinction highlights that while power generation is decarbonizing rapidly, end-use electrification lags behind. The MMQR analysis indicates that economic growth drives renewable adoption more effectively in countries with already high renewable shares (upper quantiles) due to established market mechanisms and grid flexibility. Conversely, in lower-quantile countries, regulatory stability and direct infrastructure investment prove more critical than market-based incentives, highlighting the need for differentiated policy instruments. While EU policy milestones (RED I–III-) align with progress in power generation, they have failed to accelerate transitions in lagging sectors. This study concludes that achieving climate neutrality requires moving beyond aggregate targets to implement distinct, sector-specific interventions that address the unique structural barriers in transport and thermal applications. Full article

Amidst the ongoing global energy crisis, environmental deterioration, and the exacerbation of climate change, the development of renewable energy, particularly solar energy, has become a central topic in the global energy transition. This study investigates a solar photovoltaic thermal (PVT) heat pump system that utilizes an expanded honeycomb-channel PVT module to enhance the comprehensive utilization efficiency of solar energy. A simulation platform for the solar PVT heat pump system was established using Aspen Plus software (V12), and the system’s performance impact mechanisms and engineering applications were researched. The results indicate that solar irradiance and the circulating water temperature within the PVT module are the primary factors affecting system performance: for every 100 W/m² increase in solar irradiance, the coefficient of performance for heating (COP_h) increases by 13.7%, the thermoelectric comprehensive performance coefficient (COP_co) increases by 14.9%, and the electrical efficiency of the PVT array decreases by 0.05%; for every 1 °C increase in circulating water temperature, the COP_h and COP_co increase by 11.8% and 12.3%, respectively, and the electrical efficiency of the PVT array decreases by 0.03%. In practical application, the system achieves an annual heating capacity of 24,000 GJ and electricity generation of 1.1 million kWh, with average annual COP_h and COP_co values of 5.30 and 7.60, respectively. The Life Cycle Cost (LCC) is 13.2% lower than that of the air-source heat pump system, the dynamic investment payback period is 4–6 years, and the annual carbon emissions are reduced by 94.6%, demonstrating significant economic and environmental benefits. This research provides an effective solution for the efficient and comprehensive utilization of solar energy, utilizing the low-global-warming-potential refrigerant R290, and is particularly suitable for combined heat and power applications in regions with high solar irradiance. Full article

Existing buildings consume a large portion of the total current energy production, especially in developing countries such as Egypt. Increasing energy demand, coupled with decreasing availability and increasing cost of conventional non-renewable energy resources, have encouraged a “building green” retrofit trend in order to maximize the energy performance of the built environment. This paper outlines the development of an Energy Retrofit Decision-Support System (ERDSS) for hot, arid climates that models building retrofit scenarios and determines the impact of each retrofit measure on the overall energy consumption of a proposed building retrofit program. The methodology combines building an energy simulation with a database-driven, budget-constrained optimization framework based on the Savings-to-Investment Ratio (SIR) to evaluate and prioritize retrofit measures. In addition, ERDSS determines the impact of each retrofit measure on the overall energy consumption of a proposed building retrofit program, ranks the retrofit measures according to their Savings-to-Investment Ratio (SIR) and uses optimization to develop a suggested retrofit program for a given budget. ERDSS is applied on a case study of an education building in New Cairo, Egypt, in order to illustrate the performance of the framework. Results show that savings for the commissioned retrofit, standard retrofits, and deep retrofits reached 15 percent, 35 percent, and 45 percent, respectively. Full article

Many nations have been investing in hydrogen energy in the most recent wave of development and numerous projects have been proposed, yet a substantial share of these projects remain at the conceptual or feasibility stage and have not progressed to final investment decision or operation. There is a need to identify initial potential sites for green hydrogen production from renewable energy on an objective basis with minimal upfront cost to the investor. This study develops a decision support system (DSS) for identifying optimal locations for green hydrogen production using solar and wind resources that integrate economic, environmental, technical, social, and risk and safety factors through advanced Multi-Criteria Decision Making (MCDM) techniques. The study evaluates alternative weighting scenarios using (a) occurrence-based, (b) PageRank-based, and (c) equal weighting approaches to minimize human bias and enhance decision transparency. In the occurrence-based approach (a), renewable resource potential receives the highest weighting (≈34% total weighting). By comparison, approach (b) redistributes importance toward infrastructure and social indicators, yielding a more balanced representation of technical and economic priorities and highlighting the practical value of capturing interdependencies among indicators for resource-efficient site selection. The research also contrasts the empirical and operational efficiencies of various weighting methods and processing stages, highlighting strengths and weaknesses in supporting sustainable and economically viable site selection. Ultimately, this research contributes significantly to both academic and practical implementations in the green hydrogen sector, providing a strategic, data-driven approach to support sustainable energy transitions. Full article

The energy transition in Ibero-American countries demands significant diversification, yet the vast potential of offshore renewable energies (ORE) remains largely untapped. Slow adoption is often attributed to the hostile marine environment, high investment costs, and a lack of institutional, regulatory, and industrial readiness. A critical barrier for policymakers is the absence of methodologically robust tools to assess national preparedness. Existing indices typically rely on simplistic weighting schemes or are susceptible to known flaws, such as the rank reversal phenomenon, which undermines their credibility for strategic decision-making. This study addresses this gap by developing a multi-criteria decision-making (MCDM) framework based on a problem-specific synthesis of established optimization principles to construct a comprehensive Offshore Readiness Index (ORI) for 13 Ibero-American countries. The framework moves beyond traditional methods by employing an advanced weight-elicitation model rooted in the Robust Ordinal Regression (ROR) paradigm to analyze 42 sub-criteria across five domains: Regulation, Planning, Resource, Industry, and Grid. Its methodological core is a non-linear objective function that synergistically combines a Shannon entropy term to promote a maximally unbiased weight distribution and to prevent criterion exclusion, with an epistemic regularization penalty that anchors the solution to expert-derived priorities within each domain. The model is guided by high-level hierarchical constraints that reflect overarching policy assumptions, such as the primacy of Regulation and Planning, thereby ensuring strategic alignment. The resulting ORI ranks Spain first, followed by Mexico and Costa Rica. Spain’s leadership is underpinned by its exceptional performance in key domains, supported by specific enablers, such as a dedicated renewable energy roadmap. The optimized block weights validate the model’s structure, with Regulation (0.272) and Electric Grid (0.272) receiving the highest importance. In contrast, lower-ranked countries exhibit systemic deficiencies across multiple domains. This research offers a dual contribution: methodological innovation in readiness assessment and an actionable tool for policy instruments. The primary policy conclusion is clear: robust regulatory frameworks and strategic planning are the pivotal enabling conditions for ORE development, while industrial capacity and infrastructure are consequent steps that must follow, not precede, a solid policy foundation. Full article

To mitigate the mismatch between fluctuating renewable generation and load demand in highway service area multi-microgrid systems, this paper develops a day-ahead capacity optimization model based on the coordinated operation of fixed and mobile energy storage. A ring-structured multi-microgrid architecture is established, incorporating a “one-to-many” interaction mode of mobile storage stations. A coordinated control strategy is then proposed to enable flexible power dispatch and resource sharing among microgrids. The objective function minimizes both investment and operating costs of energy storage on a day-ahead timescale, and the model is solved using an optimization approach. Case study results demonstrate that introducing mobile energy storage significantly reduces the required capacity of local fixed storage, enhances energy interconnection among microgrids, and improves overall storage utilization and system economy. Full article