Search Results (2,947)

With carbon neutrality as a target and the increased penetration of renewable energy, the operational flexibility of power systems has begun to face challenges. In order to explicitly represent the operational flexibility of power systems, two types of flexibility indexes and corresponding models for their evaluation are established in this paper. One of the indexes is the supply–demand balance, which evaluates the adequacy of operational flexibility at the system level. The other is the availability of flexible resources, which comprehensively quantifies the flexibility of the power system from the perspectives of power generation, load, and energy storage. In the case study presented here, the proposed evaluation method is illustrated and validated based on a provincial power system in China. Next, the role of energy storage in enhancing flexibility is quantitatively analyzed using the proposed indexes. Then, the economic model reveals the nonlinear decline in the marginal benefit of investment in energy storage. Energy storage alone cannot fully meet the requirements for supply–demand balance in the power system, necessitating a comprehensive consideration of the available capacity for flexibility from the perspectives of generation, load, and energy storage. Analysis of a typical scenario shows that the provincial power system has 5000 MW of upward and downward flexibility in capacity. The numerical results highlight the critical importance of integrating flexibility across all components. Full article

The inherent randomness and intermittency of offshore renewable energy sources, such as wind and solar power, pose significant challenges to the stable and secure operation of the power grid. These fluctuations directly affect the performance of grid-connected systems, particularly in terms of harmonic distortion and load response. This paper addresses these challenges by proposing a novel harmonic control strategy and load response optimization approach. An integrated three-winding transformer filter is designed to mitigate high-frequency harmonics, and a control strategy based on converter-side current feedback is implemented to enhance system stability. Furthermore, a hybrid PI-VPI control scheme, combined with feedback filtering, is employed to improve the system’s transient recovery capability under fluctuating load and generation conditions. Experimental results demonstrate that the proposed control algorithm, based on a transformer-oriented model, effectively suppresses low-order harmonic currents. In addition, the system exhibits strong anti-interference performance during sudden voltage and power variations, providing a reliable foundation for the modulation and optimization of offshore wind–solar coupled hydrogen production power supply systems. Full article

Global agriculture remains dependent on nitrogen fertilizers produced through fossil fuel-based processes, contributing to greenhouse gas emissions, energy use, and supply chain vulnerabilities. This review introduces plasma-activated water (PAW) as a novel, electricity-driven alternative for sustainable nitrogen delivery. Generated by non-thermal plasma, PAW infuses water with reactive oxygen and nitrogen species, offering a clean, decentralized substitute for conventional synthetic fertilizers derived from the Haber–Bosch and Ostwald processes. It can be produced on-site using renewable energy, reducing transportation costs and depending on fertilizers. Beyond its fertilizer properties, PAW enhances seed germination, plant growth, stress tolerance, and pest resistance, making it a multifunctional input for controlled environment agriculture. We also assess PAW’s techno-economic viability, including energy requirements, production costs, and potential scalability through renewable energy. These factors are crucial for determining its feasibility in both industrial systems and localized agricultural applications. Finally, the review examines PAW’s contribution to the ten United Nations Sustainable Development Goals, particularly in climate action, clean energy, and sustainable food production. By combining agronomic performance with circular production and emissions reduction, PAW presents a promising path toward more resilient, low-impact, and self-sufficient agricultural systems. Full article

Ghana’s electricity grid remains heavily fossil-fuel dependent (69%), resulting in high costs and unstable low-voltage (LV) networks, exacerbating supply shortages. This study evaluates the technical and economic feasibility of converting the Obaa-Yaa LV substation in Drobo, Ghana, into a solar-powered microgrid. Using the forward–backward method for technical analysis and financial metrics (NPV, IRR, DPP, and PI), the results show that rooftop solar on seven households generates 676,742 kWh annually—exceeding local demand by 115.8 kW—with no voltage violations (240 V ± 6%) and minimal losses (9.24 kW). Economic viability is demonstrated via an NPV of GHS 2.1M, IRR of 17%, and a 10-year payback. The findings underscore solar microgrids as a pragmatic solution for Ghana’s energy challenges, urging policymakers to incentivize decentralized renewable systems. Full article

Off-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage systems (HESS) can mitigate power fluctuations, traditional power allocation rules based solely on electrolyzer power limits and HESS state of charge (SOC) boundaries result in insufficient energy supply capacity and unstable electrolyzer operation. To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. In Stage I, hydrogen production power and HESS initial allocation are determined through the deep coupling of real-time electrolyzer operating conditions with reserved energy. Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. The proposed method enhances hydrogen production stability and HESS supply capacity while reducing renewable curtailment rates and average production costs. Case studies demonstrate its superiority over three conventional rule-based power allocation methods. Full article

The adoption of wind energy is pivotal for advancing sustainable power systems, particularly in off-grid microgrids where infrastructure limitations hinder conventional energy solutions. The inherent variability of wind generation, however, challenges grid reliability and demand–supply balance, necessitating accurate forecasting models. This study proposes a hybrid framework for short-term wind speed prediction, integrating deep learning (Long Short-Term Memory, LSTM) and ensemble methods (random forest, Extra Trees) to exploit their complementary strengths in modeling temporal dependencies. A multivariate approach is adopted using meteorological data (including wind speed, temperature, humidity, and pressure) to capture complex weather interactions through a structured time-series design. The framework also includes a feature selection stage to identify the most relevant predictors and a hyperparameter optimization process to improve model generalization. Three wind speed variables, maximum, average, and minimum, are forecasted independently to reflect intra-day variability and enhance practical usability. Validated with real-world data from Cuenca, Ecuador, the LSTM model achieves superior accuracy across all targets, demonstrating robust performance for real-world deployment. Comparative results highlight its advantage over tree-based ensemble techniques, offering actionable strategies to optimize wind energy integration, enhance grid stability, and streamline renewable resource management. These insights support the development of resilient energy systems in regions reliant on sustainable microgrid solutions. Full article

The energy sector underwent a significant transformation with increasing demand for efficiency, transparency, and sustainability. The traditional or conventional system often faces several challenges, such as inefficient energy trading, a lack of transparency in renewable energy generation verification, and complex regulatory guidelines that affect its widespread adoption. Thus, blockchain technology has emerged as a potential solution to overcome these challenges, as it is known for its transparent, secure, and decentralized nature. However, despite the promising application of blockchain, its integration into the energy supply chain (ESC) is underexplored. The purpose of this research is to analyze the potential applications of blockchain technology in ESC in order to enhance efficiency, transparency, and sustainability in energy systems. The aim is to investigate the integration of blockchain with emerging technologies (such as IoTs, smart contracts, and P2P energy trading) in order to optimize energy production, distribution, and consumption. Furthermore, by comparing different blockchain platforms (like Ethereum, Solana, Hedera, and Hyperledger Fabric), this study discusses the security and scalability challenges of using blockchain in energy systems. It also examines the practical use cases of blockchain for the tokenization of RECs, dynamic energy pricing, and P2P energy trading by providing the Energy Web Foundation and Power Ledger as real-world examples. The article concludes that blockchain technology has the potential to transform ESC by enabling decentralized energy trading, which subsequently enhances transparency in energy transactions and the verification of renewable energy generation. It also identifies smart contracts and tokenization of energy assets as key parameters for dynamic pricing models and efficient trading mechanisms. However, regulatory and scalability challenges remain significant obstacles to its widespread adoption. Finally, this study provides the basis for future advancement in the adoption of blockchain technology in ESC, which offers a valuable resource for industry professionals, regulating authorities, and researchers. Full article

Nuclear energy cogeneration, which integrates electricity generation with thermal energy utilization, presents a transformative pathway for enhancing energy efficiency and decarbonizing industrial and urban sectors. This comprehensive review synthesizes advancements in technological stratification, economic modeling, and sectoral practices to evaluate the viability of nuclear cogeneration as a cornerstone of low-carbon energy transitions. By categorizing applications based on temperature requirements (low: <250 °C, medium: 250–550 °C, high: >550 °C), the study highlights the adaptability of reactor technologies, including light water reactors (LWRs), high-temperature gas-cooled reactors (HTGRs), and molten salt reactors (MSRs), to sector-specific demands. Key findings reveal that nuclear cogeneration systems achieve thermal efficiencies exceeding 80% in low-temperature applications and reduce CO₂ emissions by 1.5–2.5 million tons annually per reactor by displacing fossil fuel-based heat sources. Economic analyses emphasize the critical role of cost allocation methodologies, with exergy-based approaches reducing levelized costs by 18% in high-temperature applications. Policy instruments, such as carbon pricing, value-added tax (VAT) exemptions, and subsidized loans, enhance project viability, elevating net present values by 25–40% for district heating systems. Case studies from Finland, China, and Canada demonstrate operational successes, including 30% emission reductions in oil sands processing and hydrogen production costs as low as USD 3–5/kg via thermochemical cycles. Hybrid nuclear–renewable systems further stabilize energy supply, reducing the levelized cost of heat by 18%. The review underscores the necessity of integrating Generation IV reactors, thermal storage, and policy alignment to unlock nuclear cogeneration’s full potential in achieving global decarbonization and energy security goals. Full article

This paper shows that using renewable energy sources in the power supply of transportation infrastructure is gradually becoming a new trend. Renewable energy systems are already valuable for railway and automotive infrastructure in various countries; however, this use is limited. This paper examines the improvement of control in a grid-connected, hybrid renewable energy system to meet the needs of a railway transportation infrastructure object by utilizing an additional diesel generator in autonomous mode. The aim is to reduce the depth of battery discharge and limit energy consumption from the grid during peak demand hours, considering the wide fluctuations in power consumption of the object and deviations in renewable energy generation relative to the forecast. Additionally, the task of ensuring long-term autonomous operation of the system is addressed. A control system is proposed based on the deviation of the battery’s state of charge relative to a set schedule, which is determined according to the forecast using an additional variable that sets the power consumption limit. This ensures the minimum possible depth of discharge and peak consumption, taking into account the generation of renewable energy sources, with a power-increase factor ranging from 1 to 1.5 relative to the calculated value. In autonomous mode, the task of minimizing energy consumption by the diesel generator is addressed. Solutions have been developed to implement control in grid and autonomous modes with the corresponding calculation algorithm. The system is not sensitive to the load schedule, and the battery’s depth of discharge limitations are maintained even when renewable energy generation is below the forecast by up to 20%. When generating renewable energy sources below the average monthly value in summer, it is possible to maintain a DoD of no less than 60%. Full article

This study explores advanced multivariate models that incorporate non-climatic exogenous variables for very short-term photovoltaic energy forecasting. By integrating historical energy data from multiple photovoltaic plants, the research aims to improve the prediction accuracy of a target plant while addressing critical challenges in electric power systems (EPS), such as frequency stability. Frequency stability becomes increasingly complex as renewable energy sources penetrate the grid because of their intermittent nature. To mitigate this challenge, precise forecasting of photovoltaic energy generation is essential for balancing supply and demand in real time. The performance of long short-term memory (LSTM) networks and bidirectional LSTM (BiLSTM) networks was compared over a 5 min horizon. Including energy generation data from neighboring plants significantly improved prediction accuracy compared to univariate models. Among the models, multivariate BiLSTM showed superior performance, achieving a lower root-mean-square error (RMSE) and higher correlation coefficients. Quantile regression applied to manage prediction uncertainty, providing robust confidence intervals. The results suggest that incorporating an exogenous power series effectively captures spatial correlations and enhances prediction accuracy. This approach offers practical benefits for optimizing grid management, reducing operational costs, improving the integration of renewable energy sources, and supporting frequency stability in power generation systems. Full article

This paper presents the optimal sizing of a hybrid renewable energy system (HRES) for an isolated residential building using modified smell agent optimization (mSAO). The paper introduces a time-dependent approach that adapts the selection of the original SAO control parameters as the algorithm progresses through the optimization hyperspace. This modification addresses issues of poor convergence and suboptimal search in the original algorithm. Both the modified and standard algorithms were employed to design an HRES system comprising photovoltaic panels, wind turbines, fuel cells, batteries, and hydrogen storage, all connected via a DC-bus microgrid. The components were integrated with the microgrid using DC-DC power converters and supplied a designated load through a DC-AC inverter. Multiple operational scenarios and multi-objective criteria, including techno-economic metrics such as levelized cost of energy (LCOE) and loss of power supply probability (LPSP), were evaluated. Comparative analysis demonstrated that mSAO outperforms the standard SAO and the honey badger algorithm (HBA) used for the purpose of comparison only. Our simulation results highlighted that the PV–wind turbine–battery system achieved the best economic performance. In this case, the mSAO reduced the LPSP by approximately 38.89% and 87.50% over SAO and the HBA, respectively. Similarly, the mSAO also recorded LCOE performance superiority of 4.05% and 28.44% over SAO and the HBA, respectively. These results underscore the superiority of the mSAO in solving optimization problems. Full article

This paper analyses Poland’s participation in implementing European climate policy within the framework of the National Energy and Climate Plan (NECP), looking toward 2040. It assesses the feasibility of Poland’s commitments to the European Union’s decarbonisation targets, particularly with regard to transitioning from fossil fuels to renewable energy sources and nuclear power. The study highlights the challenges related to the speed of the energy transition, the security of electricity supply, and the competitiveness of the national economy. The study also assesses the energy mix scenarios proposed in the NECP, taking into account historical energy consumption data, economic and demographic projections, and expert analyses of energy security. It also critically examines the risks of delayed investment in nuclear and offshore wind, the potential shortfall in renewable energy infrastructure, and the need for transitional solutions, including coal and gas generation. An alternative scenario is proposed to mitigate potential energy supply shortfalls between 2035 and 2040, highlighting the role of energy storage, strategic reserves, and the maintenance of certain fossil fuel capacities. Poland’s energy policy should prioritize flexibility and synchronization with EU objectives, while ensuring economic stability and technological feasibility. The analysis underlines that the sustainable development of the national energy system requires not only alignment with European climate goals, but also a long-term balance between environmental responsibility, energy affordability, and security. Strengthening the sustainability dimension in energy policy decisions—by integrating resilience, renewability, and social acceptance—is essential to ensure a just and enduring energy transition. Full article

The global energy matrix needs to undergo considerable changes to achieve the clean and affordable energy target as per the Sustainable Development Goals determined by the United Nations (UN) by 2030. Hydrogen has stood out worldwide as a potential substitute for current non-renewable sources. Once thought to be minor, if not non-existent, natural hydrogen is now becoming a more significant alternative that is being explored. Natural hydrogen can be obtained from subsurface rocks by the generation process of serpentinization, radiolysis, rock fracturing, or magma degassing, using extraction technology similar to that already used in the oil and gas industries. Thus, the goal of this research was to perform a consistent technical–scientific and bibliometric review of natural hydrogen, presenting the Brazilian context. The results showed that from 2017 onwards, there has been an increase in research publications related to the topic. France is the country with the most publications. In Brazil, the potential of natural hydrogen sources has been studied in states such as Goias, Tocantins, Minas Gerais, Roraima, Bahia, and Ceará. It is still difficult to predict the potential cost of natural hydrogen production. However, estimates through the Hydroma company show a cost of 0.5 USD/kg, and Australia and Spain target price projects at approximately 1 USD/kg of natural decarbonization could be aided by natural hydrogen, which could supply the world’s energy needs for generations. Geological processes, reserve behavior, and the efficiency of extraction are among the unknowns, though. Brazil requires a strong regulatory framework and additional research. For exploration to be sustainable, cooperation between the government, businesses, and society is essential. Full article

Electricity markets with a high share of variable renewable energy require significant balancing reserves to ensure stability by preserving the balance of supply and demand. However, they were originally conceived for dispatchable technologies, which operate with predictable and controllable generation. As a result, adapting market mechanisms to accommodate the characteristics of variable renewables is essential for enhancing grid reliability and efficiency. This work studies the strategic behavior of a wind power producer (WPP) in the Iberian electricity market (MIBEL) and the Portuguese balancing markets (BMs), where wind farms are economically responsible for deviations and do not have support schemes. In addition to exploring current market dynamics, the study proposes new market designs for the balancing markets, with separate procurement of upward and downward secondary balancing capacity, aligning with European Electricity Regulation guidelines. The difference between market designs considers that the wind farm can hourly bid in both (New 1) or only one (New 2) balancing direction. The study considers seven strategies (S1–S7) for the participation of a wind farm in the past (S1), actual (S2 and S3), New 1 (S4) and New 2 (S5–S7) market designs. The results demonstrate that new market designs can increase the wind market value by 2% compared to the optimal scenario and by 31% compared to the operational scenario. Among the tested approaches, New 2 delivers the best operational and economic outcomes. In S7, the wind farm achieves the lowest imbalance and curtailment while maintaining the same remuneration of S4. Additionally, the difference between the optimal and operational remuneration of the WPP under the New 2 design is only 22%, indicating that this design enables the WPP to achieve remuneration levels close to the optimal case. Full article

This study examines the feasibility of deploying renewable energy sources and storage systems to provide ancillary services (ASs), traditionally supplied by conventional power systems, in an electric-island power grid. As renewable energy penetration grows, grid stability becomes increasingly challenged as reduced system inertia and higher variability occur. The study focuses on Israel, which currently lacks operational AS markets. This research explores regulatory, economic, and technical mechanisms to enable renewables and storage systems to provide such services, using a comparative analysis of Germany and California, US, as use cases, along with interview analysis with experts from the Israeli energy sector. The findings highlight, on the one hand, notable regulatory and infrastructural barriers limiting the ability of alternative sources to provide ancillary services. On the other hand, the feasibility and importance of integrating renewables and storage, as regulatory adjustments, market-based procurement mechanisms, and incentive schemes, are to be undertaken. Adopting a structured AS market in Israel, influenced by international best practices, can improve grid resilience, allowing higher renewable integration and supporting long-term energy security and sustainability. Full article