Search Results (570)

Renewable energy transition (RNET) is a key factor in improving environmental quality, sustainable economic growth, energy security, and public health, but its level varies markedly across countries. Hence, this study investigates the effect of business, financial, and trade freedom, human capital, and environmental policy stringency on RNET in the E7 economies from 2000 to 2020 using panel econometric tests. The panel causality test’s outcomes indicate that financial and trade freedom, human capital, and environmental policy stringency are Granger causes of the RNET, and there is a two-way Granger causality between business freedom and the RNET. Additionally, the cointegration coefficients indicate that the effects of business, financial, and trade freedom, human capital, and environmental policy stringency on the RNET change amongst the E7 countries. Full article

The transition to climate-neutral, resilient, and decentralized energy systems is particularly challenging for regions with strong seasonal demand, high renewable potential, and limited grid flexibility. Islands such as Crete exemplify these challenges. This work provides an integrated framework for evaluating both system performance and replication potential of four Modular Renewable Energy Systems (MRES) for Renewable Energy Valleys in Crete under common Renewable Energy Penetration (REP) targets of 90%, 95%, and 99.9%. The framework incorporates output-based levelized cost indicators (LCOE), Net Levelized Electricity Cost (NLEC), Effective Community Electricity Cost (ECEC), capital expenditure (CAPEX), profitability index (PI), payback time (POT), and life-cycle environmental assessment (LCA) relative to the corresponding business-as-usual (BAU) systems. Output-based LCOE ranged from 0.059 to 0.112 €/kWh, NLEC from 0.017 to 0.074 €/kWh, and ECEC from 0.082 to 1.090 €/kWh, highlighting the influence of surplus-electricity revenues on net system economics. The attributional LCA showed substantial global-warming reductions for most configurations, reaching approximately 86% for MRES 3, although trade-offs emerged in mineral resource scarcity and water consumption. Results highlight that replication potential depends on matching each archetype to local resources, demand profiles, infrastructure constraints, and end-use priorities, while 90–95% REP provides a more balanced compromise than 99.9% REP. Full article

Sector coupling strategies are increasingly adopted to improve the flexibility and efficiency of renewable energy systems by integrating multiple end-users, energy sectors, and conversion technologies. However, their widespread deployment relies on additional infrastructure and energy conversion processes, raising questions about the associated environmental and economic trade-offs. Despite the growing interest in Power-to-X technologies, integrated assessments simultaneously evaluating energy, economic, and environmental performance at the district scale remain limited. This study proposes an integrated framework combining techno-economic analysis and life cycle assessment to evaluate alternative Power-to-X strategies within a regenerated renewable energy community in Southern Italy. Three sector coupling pathways are compared: Power-to-Power, Power-to-Gas, and Power-to-Gas-to-Power. The results highlight different trade-offs among the investigated configurations. The Power-to-Power scenario achieves complete renewable electricity self-consumption and increases system self-sufficiency from 46% to 71%, whereas the Power-to-Gas configuration provides the shortest payback period (6 years). From an environmental perspective, the baseline, Power-to-Power, and Power-to-Gas scenarios reduce average life cycle impacts by 53%, 44%, and 40%, respectively, compared with the business-as-usual configuration, while the Power-to-Gas-to-Power scenario exhibits slightly higher impacts due to the additional fuel cell system. Furthermore, the environmental ranking of the scenarios depends on the adopted system expansion assumptions, particularly the avoided burden approach. The proposed framework provides a comprehensive basis for evaluating sector coupling strategies in renewable energy communities, supporting decision making through the integrated assessment of environmental performance, economic viability, and energy self-sufficiency. Full article

The rapid transition toward electric vehicles (EVs) in Saudi Arabia requires reliable and sustainable charging infrastructure capable of supporting long-distance highway transportation. However, the deployment of emergency charging systems is challenged by sparse charging infrastructure, stochastic emergency charging demand, battery degradation under harsh climatic conditions, and the need for cost-effective integration of renewable energy resources. This study presents a three-stage unified techno-economic planning framework for renewable-assisted emergency EV charging networks that integrates strategically located charging hubs with a coordinated fleet of solar-assisted Mobile Emergency Charging Vehicles (MECVs). The proposed framework jointly optimizes charging hub locations, photovoltaic (PV) generation capacity, battery energy storage system (BESS) sizing, and MECV allocation while explicitly accounting for stochastic emergency charging demand, renewable-energy utilization, and temperature-dependent battery degradation. Emergency charging demand is modeled using Monte Carlo simulation based on EV penetration scenarios, and battery aging is incorporated into the optimization through a temperature-dependent degradation model. The planning problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model and comparatively solved using three independent metaheuristic algorithms, namely the Musical Chairs Algorithm (MCA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). The proposed framework is evaluated using two representative highway corridors in Saudi Arabia. The results indicate that renewable-assisted charging can reduce annual grid-related CO₂ emissions by approximately 25,360 and 57,641 t CO₂/year for the Riyadh–Dammam and Riyadh–Makkah corridors, respectively. Battery degradation contributes approximately 12.7–14.2% of the total annualized system cost, highlighting the importance of incorporating lifecycle degradation into infrastructure planning. Temperature sensitivity analysis further indicates the significant influence of harsh climatic conditions on battery lifetime, renewable-energy utilization, and overall system economics. The proposed framework provides a practical planning methodology for developing reliable, sustainable, and economically viable emergency EV charging infrastructure in regions with similar geographical and climatic characteristics. Full article

Nature-based solutions (NBSs) are central to urban climate-neutrality strategies, but their implementation still lags behind policy ambition. One reason is that most NBS benefits are public goods and rarely generate direct revenue, so we know far less about the institutional and financial conditions needed to deliver them than about their ecological performance. This paper develops a business model framework linking NBS interventions to financing and governance configurations, applying established NBS typologies and the Pestoff Triangle of state, market, and community provision to thirteen interventions across eleven sites in the Railway District of Thessaloniki, Greece. The interventions are organised into five business model categories: public space greening, private space upgrades, public–private hybrids, building retrofits, and renewable energy. Their financing logic is shaped less by intervention type than by ownership structure and stakeholder configuration. To address this gap, we followed category-specific blended finance strategies combining grants, private investment, regulatory incentives, and community resources, underpinned by stewardship-oriented governance. The findings suggest that scaling NBSs depends less on technical readiness than on institutional capacity to match financing and governance to local ownership and stakeholder contexts, offering a pathway from climate-neutrality strategy to implementable urban regeneration. Full article

Small and medium-sized enterprises (SMEs) represent the majority of EU businesses and a disproportionate share of its environmental impact, yet longitudinal evidence on their resource efficiency behaviour remains scarce. This study examines whether SME adoption of resource efficiency practices increased between 2017 and 2024 and whether the size gradient changed across a period spanning several major and concurrent institutional and economic events: the European Green Deal (2019), the Circular Economy Action Plan (2020), the COVID-19 pandemic and its economic aftermath (2020–2021), the energy price shock that intensified in 2021 and was amplified by the Russia–Ukraine conflict in 2022, and the early implementation phase of the Corporate Sustainability Reporting Directive (2022–2024). These events overlapped substantially in time and cannot be disentangled with the present empirical design. Using microdata from three Flash Eurobarometer waves (N = 38,165; EU27), we construct a harmonised eight-item adoption index and estimate a weighted Poisson regression with cluster-robust standard errors and wave × firm-size interactions. Adoption increased substantially: SMEs reporting no resource efficiency action fell from 10.5% to 4.2%, and renewable energy use more than doubled (+15.3 pp). More substantively, the population-level gap in resource efficiency adoption between medium-sized enterprises (50–249 employees) and microenterprises (1–9 employees) narrowed by 81%, from +0.89 practices in 2017 (out of a maximum of 8) to a statistically non-significant +0.13 and +0.17 practices in 2021 and 2024 respectively (interaction IRR ≈ 0.81–0.82, p < 0.001 in both waves), robust to nine checks. The size gradient in environmental behaviour appears not to be structural but a dynamic feature of the institutional landscape, one that narrowed substantially over a period coinciding with intensifying regulatory ambition and energy price shock—though the present repeated cross-sectional design cannot establish which mechanisms drove this compression. Full article

Thailand has committed to achieving net-zero greenhouse gas (GHG) emissions by 2050, requiring a fundamental transformation of its energy system. This study developed an integrated energy modelling framework by coupling the Low-Emission Analysis Platform (LEAP) with the Next Energy Modelling System for Optimisation (NEMO) to evaluate Thailand’s long-term energy transition under three scenarios: Business as Usual (BAU), Current Policy Scenario (CPS), and Net Zero 2050 (NZ2050). The novelty of this study lies in integrating sectoral energy demand modelling; least-cost electricity system optimisation; GHG emissions accounting; and system cost assessment within a single framework to evaluate the technical, environmental, and economic implications of decarbonisation pathways. The results show that demand-side GHG emissions increase to 370.7 MtCO₂eq by 2050 under BAU, while current policies reduce emissions to 137.6 MtCO₂eq but remain insufficient to achieve Thailand’s climate targets. In contrast, the NZ2050 scenario lowers demand-side GHG emissions to 27.23 MtCO₂eq (a 93% reduction relative to BAU) through extensive electrification; a 59% improvement in energy intensity; accelerated renewable energy deployment; coal phase-out by 2045; and the deployment of carbon capture, utilisation and storage (CCUS), and bioenergy with carbon capture and storage (BECCS). Residual transport emissions are reduced to 23 MtCO₂eq and offset through carbon removal measures. On the supply side, least-cost optimisation reduces power-sector emissions to 2.9 MtCO₂eq while lowering electricity generation costs by approximately 47% through an optimised renewable-based generation mix. The findings demonstrate that Thailand’s net-zero target is technically feasible and economically viable; the integrated LEAP–NEMO framework provides a robust decision-support tool for national energy planning and other emerging economies pursuing cost-effective net-zero transitions. Full article

Sustainable hydrogen policy and national strategy documents are rich in qualitative information whose systematic evaluation still relies largely on subjective SWOT frameworks. This study proposes a reproducible hybrid methodology that couples expert-supervised Natural Language Processing (NLP) with a stochastic techno-economic model of the Levelized Cost of Hydrogen (LCOH) to convert policy discourse into quantitative, evidence-based recommendations. TF-IDF vectorization, K-Means clustering, Shannon entropy and Correspondence Analysis (CA) are applied to a manually annotated corpus of 107 sentences drawn from Türkiye’s national hydrogen strategy documents (Cohen’s κ = 0.81, substantial agreement). CA positions Regulation/Legislation and Financing near the Weakness quadrant, Renewable Resource Potential in the Strength quadrant, and Export/Demand Risk near Opportunity—revealing structural bottlenecks that challenge the sustainable energy transition. These qualitative findings are subjected to a quantitative consistency check via a Monte Carlo simulation (N = 10,000 iterations) propagating joint uncertainty in CAPEX, electricity price, electrolyzer efficiency, annual operating hours, discount rate and plant lifetime. The deterministic 2025 LCOH baseline of 4.89 €/kg H₂ carries a P10–P90 interval of [3.95; 5.92] €/kg. Global Sobol sensitivity analysis identifies electricity price as the dominant driver (S₁ ≈ 0.52), suggesting that financing is discursively surfaced by the textual layer. Under business-as-usual technological learning, the probability of reaching a globally competitive LCOH (≤2 €/kg H₂) by 2050 is only 17.8%; a stylized proactive policy intervention (carbon pricing + subsidies) raises this probability to 78.4%. The framework is adaptable to other countries and languages (though the current implementation is Turkish-specific), providing a scalable, open methodology for evidence-based sustainable clean energy planning. Full article

Despite rapid global growth in renewable energy capacity, fossil fuels still dominate the energy mix. Renewable energy firms often face limited access to bank credit because their asset-light, technology-intensive business models provide little collateral, constraining investment in clean energy deployment. This study examines whether China’s Fintech Reform Pilot Zones, which introduce digital technology-based credit evaluation, can alleviate these financing constraints and accelerate corporate energy transition. Using a staggered difference-in-differences design on a panel of Chinese listed renewable energy firms, we find that pilot zone designation significantly improves firms’ access to external financing and increases Energy Transition Depth (ETD) by approximately 3.6 percentage points, equivalent to 24.7% of the sample mean, indicating economically meaningful improvements in corporate energy transition. The strongest effects are observed in solar photovoltaic deployment and battery storage penetration. Greater energy transition is also associated with lower firm-level greenhouse gas emission intensity, suggesting potential environmental benefits. Mediation analysis identifies two complementary pathways: an innovation-accumulation route which advances renewable energy technology, and a capital-deployment route which supports renewable energy capacity expansion by relaxing firms’ general financing constraints. Regions with more developed renewable energy industries also exhibit lower fossil energy consumption and carbon emissions, suggesting potential regional spillover effects. These findings demonstrate that Fintech-enabled financial reform can facilitate renewable energy deployment and support broader energy transition and decarbonization, with important implications for emerging economies. Full article

Enhancing renewable energy penetration (REP) is essential for accelerating the low-carbon transition of the power system. The evolution of REP is driven by the interaction of multiple factors, including policy, technology, market demand, and environmental constraints. Based on the system dynamics (SD) method, this study constructs a model to simulate the evolution of REP in China during 2012–2060 under business-as-usual (BAU), single-factor, and synergistic scenarios. The results show that, by 2060, REP reaches 77.17% under the BAU scenario. REP improvement is most pronounced under the policy support scenario, reaching 80.71%, while REP increases by 4.58%, 1.94%, 2.36%, and 1.30% relative to BAU under the policy support, technological innovation, market demand expansion, and environmental constraint scenarios, respectively. After 2030, the effect of market demand expansion gradually strengthens and surpasses environmental constraints and technological innovation, with the crossover points corresponding to REP levels of 41.69% and 57.19%, respectively. The synergistic scenario analysis further shows that policy–market synergy is the most effective pathway, with REP reaching 81.21% by 2060, followed by policy–technology synergy at 80.89%. In contrast, policy–environment synergy (80.48%) does not outperform the single policy support scenario. This suggests that environmental constraints need to be coordinated with market-based consumption and technological support to effectively promote REP. Full article

Shared energy storage is emerging as a pivotal institutional and technological arrangement for increasing power-system flexibility, integrating renewable electricity, and improving the allocation of storage resources. Focusing on power generation enterprises, this study develops a Technology–Organization–Environment (TOE) model that incorporates perceived risk and perceived benefit to explain how participation intentions toward shared energy storage are formed. Structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA) show that technological compatibility, technological maturity, top-management support, organizational slack, subjective norms, policy support, and market competition shape participation intentions by reducing perceived risk and strengthening perceived benefit. Perceived risk significantly suppresses participation intention, whereas perceived benefit significantly promotes it. The fsQCA results identify three configurational pathways to high participation intention: benefit–risk co-activation, market competition and benefit-driven participation, and market–policy dual activation. These findings show that participation in shared energy storage is generated by interdependent technological, organizational, and environmental conditions rather than by any single determinant. The study offers evidence for refining a shared-energy-storage policy and improving business models in the transition to a new power system. Full article

The aim of this article is to identify the economic and entrepreneurial factors determining the use of renewable energy sources (RES) in households. The analysis focuses on the role of running a business, the level of entrepreneurial competencies, and economic motivations in making investment decisions related to RES. The study was based on survey data, and hypotheses were tested using chi-square tests, logistic regression, and linear regression. Additionally, the reliability of the measurement scales was assessed using Cronbach’s alpha. The results indicate that households with higher levels of entrepreneurship and stronger economic motivations are significantly more likely to use RES, viewing them as a tool for optimizing energy costs and increasing energy security. Social factors, on the other hand, strengthen interest in RES technologies. The obtained results confirm the importance of the economic and energy dimensions of entrepreneurship in household energy transformation. Full article

This study conducts a comprehensive investigation into prospective policy alternatives within Pakistan’s power sector using the PAK-TIMES model, targeting the critical challenges of energy scarcity and environmental degradation. Focused on the period from 2022 to 2050, the research evaluates the impact of various policies on energy consumption, supplies, carbon emissions, and expenditures in alignment with Pakistan’s Nationally Determined Contributions (NDC) directed at combatting climate change. The study explores three distinct scenarios: a business-as-usual (BAU) scenario, along with five policy (5% Eff, 10% Eff, 15% REN, 30% REN, 50% REN) scenarios categorized into energy efficiency and renewable integration. The first scenario concentrates on the deployment of energy-efficient devices, while the second scenario delves into diverse levels of renewable energy integration. Key results reveal that energy demand is projected to surge substantially under the BAU scenario, increasing significantly from 3459 PJ in 2022 to 7912 PJ by 2050. In contrast, scenarios prioritizing energy efficiency can potentially curb the total energy supply by 2.3%, while renewable energy integration can expand up to 1.3% compared to business-as-usual by 2050. These alternative scenarios also exhibit the potential to slash greenhouse gas (GHG) emissions from the power sector by up to 15%. Notably, the PAK-TIMES model emerges as a valuable decision support tool for the Pakistani government to facilitate the execution of energy efficiency and renewable energy policies aimed at fulfilling its NDCs, while also contributing to the fulfillment of Sustainable Development Goals (SDGs) 7 (affordable and clean energy) and 13 (climate action). The study underscores the pivotal role of policy interventions in simultaneously mitigating energy challenges and combatting climate change for sustainable development. Full article

With the rapid growth of electric vehicles (EVs) and renewable energy generation, Vehicle-to-Grid (V2G) technology has emerged as a promising approach for transforming EVs from passive charging loads into flexible distributed energy storage resources. By enabling bidirectional power exchange between EV batteries and the power grid, V2G can support renewable energy accommodation, peak shaving, demand response, ancillary services, and local grid balancing. This review provides a systematic synthesis of recent advances in V2G systems for renewable energy integration, with particular emphasis on coordinated scheduling, economic mechanisms, battery degradation, and user engagement. First, the technical foundations of V2G are introduced, including Vehicle-to-Everything operating modes, bidirectional charging architecture, aggregation mechanisms, grid-support services, and renewable accommodation pathways. Second, major scheduling strategies are reviewed, including price-based, load-based, renewable-forecast-driven, centralized, distributed, and hybrid approaches. Third, the economic feasibility of V2G is examined from the perspectives of revenue streams, pricing mechanisms, business models, battery aging costs, and compensation schemes. In addition, user participation barriers, such as range anxiety, battery lifetime concerns, loss of control, uncertain financial returns, and data privacy, are discussed. Key challenges related to communication standards, interoperability, cybersecurity, market access, policy design, and pilot-scale validation are also summarized. Finally, future development directions are identified, including AI-based scheduling, aggregator platforms, fleet-scale V2G, degradation-aware optimization, carbon-aware electricity markets, and user-centered participation mechanisms. This review highlights that large-scale V2G deployment requires the integrated coordination of technical scheduling, economic incentives, battery health protection, and user acceptance in renewable-rich power systems. Full article

This paper proposes a regional distributed energy operation framework that integrates Power-to-X (P2X)-based sector coupling with Distributionally Robust Optimization (DRO) for distribution network operation environments in special zones established under South Korea’s Special Act on the Promotion of Distributed Energy. The conventional South Korean electricity market has primarily operated under a centralized Cost-Based Pool (CBP) structure, where the participation of small-scale renewable energy providers has been limited due to requirements for centralized dispatch generators. To address these structural limitations, the South Korean government introduced the distributed energy special zone policy and has promoted a Peer-to-Peer (P2P)-based electricity trading mechanism that enables direct electricity transactions between renewable energy providers and consumers within regional distribution networks. As a result of these policy initiatives, investment in small-scale renewable energy projects within designated special zones is expected to increase significantly; however, the limited local demand capacity of regional distribution networks simultaneously imposes clear constraints on the accommodation of renewable energy. Therefore, this study applies P2X-based sector coupling technologies to improve the capability to accommodate renewable energy within special zones while simultaneously establishing new energy business models. In addition, DRO is incorporated into the proposed framework to demonstrate the system’s economic feasibility and operational robustness under high uncertainty in electricity prices. Full article