Search Results (527)

Virtual power plants (VPPs) enable the efficient participation of distributed renewable energy resources in electricity markets by aggregating them. However, the profitability of VPPs is challenged by market volatility and regulatory constraints, such as price caps and imbalance penalties. This study examines the joint impact of varying price cap levels and imbalance penalty structures on the bidding strategies and revenues of VPPs. A stochastic optimization model was developed, where a three-stage scenario tree was utilized to capture the uncertainty in electricity prices and renewable generation output. Simulations were performed under various market conditions using real-world price and generation data from the Korean electricity market. The analysis reveals that higher price cap coefficients lead to greater revenue and more segmented bidding strategies, especially under asymmetric penalty structures. Segment-wise analysis of bid price–quantity pairs shows that over-bidding is preferred under upward-only penalty schemes, while under-bidding is preferred under downward-only ones. Notably, revenue improvement tapers off beyond a price cap coefficient of 0.8, which indicates that there exists an optimal threshold for regulatory design. The findings of this study suggest the need for coordination between price caps and imbalance penalties to maintain market efficiency while supporting renewable energy integration. The proposed framework also offers practical insights for market operators and policymakers seeking to balance profitability, adaptability, and stability in VPP-integrated electricity markets. Full article

Direct Air Capture (DAC) is emerging as a critical climate change mitigation strategy, offering a pathway to actively remove atmospheric CO₂. This comprehensive review synthesizes advancements in DAC technologies, with a particular emphasis on the pivotal role of nanostructured solid sorbent materials. The work critically evaluates the characteristics, performance, and limitations of key nanomaterial classes, including metal–organic frameworks (MOFs), covalent organic frameworks (COFs), zeolites, amine-functionalized polymers, porous carbons, and layered double hydroxides (LDHs), alongside solid-supported ionic liquids, highlighting their varied CO₂ uptake capacities, regeneration energy requirements, and crucial water sensitivities. Beyond traditional temperature/pressure swing adsorption, the review delves into innovative DAC methodologies such as Moisture Swing Adsorption (MSA), Electro Swing Adsorption (ESA), Passive DAC, and CO₂-Binding Organic Liquids (CO₂ BOLs), detailing their unique mechanisms and potential for reduced energy footprints. Despite significant progress, the widespread deployment of DAC faces formidable challenges, notably high capital and operational costs (currently USD 300–USD 1000/tCO₂), substantial energy demands (1500–2400 kWh/tCO₂), water interference, scalability hurdles, and sorbent degradation. Furthermore, this review comprehensively examines the burgeoning global DAC market, its diverse applications, and the critical socio-economic barriers to adoption, particularly in developing countries. A comparative analysis of DAC within the broader carbon removal landscape (e.g., CCS, BECCS, afforestation) is also provided, alongside an address to the essential, often overlooked, environmental considerations for the sustainable production, regeneration, and disposal of spent nanomaterials, including insights from Life Cycle Assessments. The nuanced techno-economic landscape has been thoroughly summarized, highlighting that commercial viability is a multi-faceted challenge involving material performance, synthesis cost, regeneration energy, scalability, and long-term stability. It has been reiterated that no single ‘best’ material exists, but rather a portfolio of technologies will be necessary, with the ultimate success dependent on system-level integration and the availability of low-carbon energy. The review paper contributes to a holistic understanding of cutting-edge DAC technologies, bridging material science innovations with real-world implementation challenges and opportunities, thereby identifying critical knowledge gaps and pathways toward a net-zero carbon future. Full article

Amid the escalating global climate crisis, the transition to sustainable energy systems has become imperative. As the world’s largest energy producer and consumer, China has established ambitious dual carbon targets, which present formidable challenges to urban energy systems that remain heavily reliant on conventional energy sources and exhibit inadequate renewable energy development. Drawing on complex adaptive systems theory, this study investigates the extent to which digital finance enhances urban energy resilience, examining both the underlying mechanisms and heterogeneous effects. Employing a multi-period difference-in-differences model with digital finance policies as a quasi-natural experiment, our analysis of panel data from 31 Chinese provinces (2016–2023) demonstrates that digital finance significantly enhances the resilience of urban energy systems and their three constituent subsystems. A mediation analysis reveals the pivotal role of innovative organizations, while machine learning techniques uncover nonlinear relationships moderated by marketization levels, fiscal energy allocations, and initial digital finance development. These findings provide critical insights for policymakers, financial institutions, and energy enterprises seeking to advance sustainable energy governance and foster financial innovation in the energy transition. Full article

Globalization and the spread of technological innovations have made world markets and economies increasingly unified and conditioned by international trade, not only for sales markets but above all for the supply of raw materials necessary for the functioning of the production complex of each country. Alongside oil and gold, the main commodities traded include industrial metals, such as aluminum and copper, mineral products such as gas, electrical and electronic components, agricultural products, and precious metals. The conflict between Russia and Ukraine tested the unification of markets, given that these are countries with notable raw materials and are strongly dedicated to exports. This suggests that commodity prices were able to influence the stock markets, especially in the countries most closely linked to the two belligerents in terms of import-export. Given the importance of industrial metals in this period of energy transition, the aim of our study is to analyze whether Industrial Metals volatility affects G7 stock markets. To this end, the BEKK-GARCH model is used. The sample period spans from 3 January 2018 to 17 September 2024. The results show that lagged shocks and volatility significantly and positively influence the current conditional volatility of commodity and stock returns during all periods. In fact, past shocks inversely influence the current volatility of stock indices in periods when external events disrupt financial markets. The results show a non-linear and positive impact of commodity volatility on the implied volatility of the stock markets. The findings suggest that the war significantly affected stock prices and exacerbated volatility, so investors should diversify their portfolios to maximize returns and reduce risk differently in times of crisis, and a lack of diversification of raw materials is a risky factor for investors. Full article

Given the widespread use of gas-fired boilers and combined heat and power (CHP) units in existing district heating (DH) systems, this study investigates the integration of medium-scale heat pumps (HPs) into such configurations. Fifteen DH system variants were analysed, differing in installed HP capacity, operational strategies, and the synchronisation of heat and electricity production with thermal demand. A dynamic simulation model incorporating real-world equipment performance was developed to assess energy efficiency, environmental impact, and economic viability under three distinct energy price scenarios. The results demonstrate that an HP sized to 17% of the total heating capacity of the DH system achieves a 54% decrease in primary energy consumption and a 68% decrease in emissions compared to the base system. Larger HP capacities enhance environmental performance and increase the share of renewable energy but also entail higher investment. An economic analysis reveals that electricity-to-gas price ratios strongly influence the cost-effectiveness of HP integration. Under favourable electricity pricing conditions, systems with HP operational priority achieve the lowest levelized cost of heating. The most economically viable configuration consists of 600 kW HP and achieves a payback period of 4.7 years. The findings highlight the potential for HPs to decarbonize DH systems while emphasising the importance of market conditions and system design in ensuring economic feasibility. Full article

In the context of the evolving energy landscape, the need to harness renewable energy sources (RESs) has become increasingly imperative. Within this framework, hydrogen emerges as a promising energy storage vector, offering a viable solution to the flexibility challenges caused by the inherent variability of RESs. This work investigates the feasibility of integrating a hydrogen-based energy storage system within an energy community in Barcelona, using surplus electricity from photovoltaic (PV) panels. A power-to-power configuration is modelled through a comprehensive methodology that determines optimal component sizing, based on high-resolution real-world data. This analysis explores how different operational strategies influence the system’s cost-effectiveness. The methodology is thus intended to assist in the early-stage decision-making process, offering a flexible approach that can be adapted to various market conditions and operational scenarios. The results show that, under the current conditions, the combination of PV generation, energy storage, and low-cost grid electricity purchases yield the most favourable outcomes. However, in a long-term perspective, considering projected cost reductions for hydrogen technologies, strategies including energy sales back to the grid become more profitable. This case study offers a practical example of balancing engineering and economic considerations, providing replicable insights for designing hydrogen storage systems in similar energy communities. Full article

According to the FAO, wheat, corn, and rice are staple crops that support global food security, providing 50% of the world’s dietary energy. The ability to predict accurately these key food crop agricultural commodity prices is important in stabilizing markets, supporting policymaking, and informing stakeholders’ decisions. To this aim, machine learning (ML), ensemble learning (EL), deep learning (DL), and time series methods (TS) have been increasingly used for forecasting due to the rapid development of computational power and data availability. This study presents a systematic literature review (SLR) of peer-reviewed original research articles focused on forecasting the prices of wheat, corn, and rice using machine learning (ML), deep learning (DL), ensemble learning (EL), and time series techniques. The results of the study help uncover suitable forecasting methods, such as hybrid deep learning models that consistently outperform traditional methods, and they identify important limitations in model interpretability and the use of region-specific datasets, highlighting the need for explainable and generalizable forecasting solutions. This systematic review adheres to the PRISMA 2020 reporting guidelines. Full article

The expanding integration of wind and photovoltaic (PV) energy is disrupting the power system planning processes. Their incorporation poses limitations to forecasting due to their inherent variability. This review compiles a total of ninety studies conducted and published between 2019 and 2025, presenting for the first time an integrated approach that simultaneously optimizes the generation, transmission, storage, and flexibility of resources given high ratios of renewable generation. We present a systematic taxonomy of conflicting optimization approaches—deterministic, stochastic, robust, and AI-enhanced optimization—outlining meaningful mathematical formulations, real-world case studies, and the achieved trade balance between optimality, scale, and runtime. Emerging international cooperation clusters are identified through quantitative bibliometric analysis, and method selection in practice is illustrated using a table with concise snapshots of case study excerpts. Other issues analyzed include long-duration storage, centralized versus decentralized roadmap delineation, and regulatory and market drivers of grid expansion. Finally, we identified gaps in the literature—namely, resilience, sector coupling, and policy uncertainty—that warrant further investigation. This review provides critical insights for researchers and planners by systematically integrating methodological perspectives to tackle real-world, application-oriented problems related to generation and transmission expansion models amid significant uncertainty. Full article

The COVID-19 pandemic and the Russia–Ukraine war have struck the world’s energy markets. This study analyzed how the recent unstable fossil fuel markets impacted the Japanese electricity contracts, classified as extra-high-, high-, and low-voltage contracts. Multiple structural break tests were conducted to endogenously determine breaks affecting electricity prices during January 2019 to November 2022. By incorporating the effects of these breaks in the autoregressive distributed lag (ARDL) model, the study analyzed the effects of natural gas, coal, and crude oil prices on the types of electricity contract prices. The results of the analyses indicated a surge in electricity prices for low- and high-voltage contracts driven by an increase in natural gas. The results imply the importance of providing proper financial support to mitigate the effects of soaring electricity prices and implementing policies to diversify the electricity generation mix in Japan. Full article

The increasing penetration of wind power—driven by the expansion of offshore projects and the repowering of existing onshore installations—poses novel challenges for power system operators. While wind energy is currently integrated without curtailment and considered fully dispatchable, its inherent variability introduces growing concerns due to its rising share in installed capacity relative to conventional sources. In Portugal, wind energy already accounts for approximately 30% of the total installed capacity, with projections reaching 38% by 2030, making it the country’s second largest energy source. In the context of the 2050 carbon neutrality targets, quantifying and managing wind power uncertainty has become increasingly important. This study proposes an integrated methodology to analyze and compare the uncertainty of onshore and offshore wind generation using real-world high-resolution data (15 min intervals over a three-year period) from three onshore and one offshore wind turbine. The framework combines statistical characterization, probabilistic modeling with zero-inflated distributions, entropy-based uncertainty quantification (using Shannon, Rényi, Tsallis, and permutation entropy), and an uncertainty-adjusted Levelized Cost of Energy (LCOE). The results show that although offshore wind energy involves higher initial investment, its lower temporal variability and entropy levels contribute to superior economic reliability. These findings highlight the relevance of incorporating uncertainty into economic assessments, particularly in electricity markets where producers are exposed to penalties for deviations from scheduled generation. The proposed approach supports more informed planning, investment, and market strategies in the transition to a renewable-based energy system. Full article

For a country to be able to sustain a policy of increasing the use of renewable energy sources to supply electricity, it must be able to continue to provide a reliable electricity supply service to its customers. Typically, electricity reliability is maintained by thermal electricity generation. To substitute solar PV for thermal electricity generation to a significant degree, it is imperative to determine the least-cost complementary technologies that will provide system reliability. In many parts of Africa and Asia, potential sites for seasonal storage dams are available or have been built. In the case studied here, maintaining service reliability by expanding the capacity of the generation plant of a seasonal storage dam in all scenarios is less costly than providing service reliability by a thermal alternative. However, maintaining service reliability while expanding generation by solar PV is in all cases costly. The levelized financial cost of the incremental energy supplied when a reliable service is maintained is between 30% and 89% greater than the levelized cost of a standalone solar PV plant. For the same set of scenarios, the range of the economic levelized cost is 28% to 85% greater with reliability than the standalone solar PV field without reliability. Given the circumstances of the electricity market, the least-cost technology to maintain a reliable service may be specific to the market. The analysis also shows that when the economic opportunity cost of funds increases from 2% to 11.5%, the levelized cost of renewable electricity generation systems doubles. Hence, if the developed countries of the world want low-income countries to maintain policies to reduce the use of fossil fuels to generate electricity, capital subsidies to low-income countries that are facing high economic opportunity costs of funds are likely to be necessary. Full article

This study investigates the thermal and energy performance of various bio-based materials, including Typha Australis, straw, banana fiber, Alfa fiber, peanut shells, and VSS (a blend of wood pulp, cotton, flax, and hemp), in comparison to conventional concrete. A combined approach integrating numerical simulations and experimental analyses was employed to ensure robust and comprehensive insights. COMSOL Multiphysics was utilized for detailed thermal modeling of wall assemblies, while TRNSYS enabled dynamic simulations to evaluate the impact of these materials on overall cooling energy demand. The results demonstrate that bio-based materials offer significantly improved thermal insulation, reducing air conditioning needs by over 30% relative to concrete, with banana fiber exhibiting the highest performance. This study underscores the need for industrial-scale optimization, supportive regulatory frameworks, and real-world implementation to promote broader adoption. Despite their strong potential, challenges remain, particularly regarding cost-effectiveness, durability, and market penetration. Ultimately, this research advocates for a transition toward more sustainable and environmentally conscious construction practices, aligning with efforts to reduce CO₂ emissions and enhance building energy efficiency. Full article

As the second largest power source in the world, hydropower plays a crucial role in the operation of power systems. This paper focuses on the key issues of regulating hydropower stations participating in the spot market. It aims at the core challenges, such as the conflict of cascade hydro plants’ joint clearing, the lack of adaptability for different types of power supply bidding on the same platform, and the contradiction between long-term operation and the spot market. Through the construction of a water spillage management strategy and settlement compensation mechanism, the competitive abandoned water problem caused by mismatched quotations of cascade hydro plants can be solved. In order to achieve reasonable recovery of the power cost, a separate bidding mechanism and capacity cost recovery model are designed. Subsequently, the sufficient electricity supply constraint of the remaining period is integrated into the spot-clearing model, which can coordinate short-term hydropower dispatch with long-term energy storage demand. The operation of the Yunnan electricity spot market is being simulated to verify the effectiveness of the proposed method. Full article

Countries aim to reduce fossil fuel usage and related environmental issues through various demand- and supply-side policies. Numerous studies have assessed the policies’ overview. However, analysis of the impacts and effectiveness of these policies in addressing transport-related CO₂ emissions is limited globally and in countries like New Zealand, which have a lower CO₂ emissions energy intensity compared to Europe, Asia, and Oceania averages. Therefore, this study first analyses the trends in energy consumption and CO₂ emissions within the transport sector across the ten largest total CO₂-emitting countries, as well as the ten largest transport CO₂-emitting OECD countries. It then provides a systematic review of the relevant policies and, finally, estimates two econometric models to explore the effects of these policies on the energy market, aimed at reducing GHG emissions globally from the transport sector, with New Zealand as a case study. The study findings indicate that the transport sector remains a significant contributor to global fossil fuel consumption and CO₂ emissions, accounting for 40.4% and 23.3%, respectively, in 2024. The ten largest CO₂-emitting countries—China, the United States, India, Russia, Japan, Germany, South Korea, Iran, Canada, and Saudi Arabia—are responsible for 68% of global emissions. Additionally, the ten OECD countries, except the US, with the highest transport CO₂ emissions—Japan, Germany, South Korea, Canada, Mexico, the UK, Italy, France, Spain, and Australia—accounted for 15.7% of the world’s total transport CO₂ emissions. Although the share of renewable energy and electricity consumption in the transport sector has steadily risen to 3.54% and 1.4%, respectively, in 2022, further adoption of these sources can considerably lower greenhouse gas emissions in this sector. Results also indicate that both demand- and supply-side policies effectively reduce greenhouse gas emissions, with their impact amplified when implemented together. In New Zealand, demand-side policies have proven to be more effective in reducing emissions than supply-side strategies alone, though combining them is the most efficient approach. This study emphasizes the importance of strategic policy implementation to guide the world toward sustainable development. Full article

This study examines the policy and technological dynamics shaping China’s road transport sector’s transition to low-carbon sustainability, focusing on battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (HFCEVs). As the world’s second-largest carbon emitter, China faces significant challenges in reducing its fossil fuel dependency in road transport, which accounts for diverse emissions and energy security risks. The present work, using a dual tech multi-level perspective (DTMLP) framework integrating multi-level perspective (MLP) and an advocacy coalition framework (ACF), analyzes the interplay of landscape pressures (global carbon constraints), regime dynamics (policy–market interactions), and niche innovations (BEV/FCEV competition). The results reveal BEVs’ dominance in light-duty markets, achieving remarkable operational emission reductions but facing lifecycle carbon lock-ins from battery production and coal-dependent power grids. HFCEVs demonstrate potential for heavy-duty decarbonization but struggle with gray hydrogen reliance and infrastructure gaps. Policy evolution highlights shifting governance from subsidies to market-driven mechanisms, alongside regional disparities in implementation. This study proposes a three-phase roadmap: structural optimization (2025–2030), technological adaptation (2030–2045), and hydrogen–electric system integration (post-2045), emphasizing material innovation, renewable energy alignment, and multi-level governance. Our findings underscore the necessity of coordinated policy–technology synergies, grid decarbonization, and circular economy strategies, to overcome institutional inertia and achieve China’s ‘Dual Carbon’ targets. This work provides actionable insights for global sustainable transport transitions amid competing technological pathways and geopolitical resource constraints. Full article