Search Results (806)

This study introduces a climate chamber developed to evaluate the performance of photovoltaic (PV) and solar air heater (SAH) panels based on 12 months of climate data specific to the province of Antalya. In the test environment, the temperature can be controlled between −5 and +50 °C, relative humidity between 10% and 90%, irradiance between 0 and 1500 W/m², and wind speed between 0 and 25 m/s. Experimental data revealed that PV panels achieved the lowest electricity production of 19.21 W in December and the highest of 73.47 W in June, while SAH panels reached an outlet temperature of 31.12 °C in July. As solar radiation increased, panel efficiency rose proportionally; however, an increase in relative humidity negatively impacted efficiency. The panel surface temperature increased from 16.86 °C in January to 39.33 °C in July. The original aspect of this study is the proposal and adaptation of chaos-integrated optimization-based explainable artificial intelligence (XAI) methods instead of classical regression-based models. These models have enabled the development of transparent, understandable, and interpretable rules based on environmental parameters, such as temperature, relative humidity, radiation, and airspeed, that affect panel performance. The methods used in this study make significant contributions to sustainable energy. In particular, the climate control test chamber developed to increase and optimize the efficiency of solar panels enables the investigation of the effects of environmental parameters on panel performance under realistic conditions, thereby facilitating the more effective use of renewable energy sources. Additionally, the use of chaos-integrated optimization-based explainable artificial intelligence (XAI) methods provides reliable, transparent, and understandable decision support models for the design and management of energy systems. This method promotes the adoption of renewable energy technologies, reduces dependence on fossil fuels, lowers carbon emissions, and supports long-term environmental sustainability. Full article

This article provides an overview of current hydrogen technologies used in road transport, with particular emphasis on their potential for decarbonizing the mobility sector. The author analyzes both fuel cells and hydrogen combustion in internal combustion engines as two competing approaches to using hydrogen as a fuel. He points out that although fuel cells offer higher efficiency, hydrogen combustion technologies can be implemented more quickly because of their compatibility with existing drive systems. The article emphasizes the importance of hydrogen’s source—so-called green hydrogen produced from renewable energy sources has the greatest ecological potential. Issues related to the storage, distribution, and safety of hydrogen use in transport are also analyzed. The author also presents the current state of refueling infrastructure and forecasts for its development in selected countries until 2030. He points to the need to harmonize legal regulations and to support the development of hydrogen technologies at the national and international levels. He also highlights the need to integrate the energy and transport sectors to effectively utilize hydrogen as an energy carrier. The article presents a comprehensive analysis of technologies, policies, and markets, identifying hydrogen as a key link in the energy transition. In conclusion, the author emphasizes that the future of hydrogen transport depends not only on technical innovations, but above all on coherent strategic actions and infrastructure investments. Full article

This paper presents a comprehensive economic optimization of a grid-connected hybrid renewable energy system (HRES) enhanced with an electromagnetic frequency regulator (EFR) to improve frequency stability and provide clean and continuous electricity to the Macau City Campus while reducing dependence on fossil sources. The system includes photovoltaic (PV) arrays, wind turbines, battery storage, EFR, and a backup diesel generator. A genetic algorithm (GA) is employed to optimally size these components with the objective of maximizing the net present value (NPV) over the system’s lifetime. The GA implementation was validated on standard benchmark functions to ensure correctness and was finely tuned for robust convergence. Comprehensive sensitivity analyses of key parameters (discount rate, component costs, resource availability, etc.) were performed to assess solution robustness. The optimized design ($\mathrm{PV}\approx 35\mathrm{kWp}$, $\mathrm{WT}=30\mathrm{kW}$, $\mathrm{ESS}\approx 200\mathrm{kWh}$, and $\mathrm{EFR}=30\mathrm{kW}$) achieves a highly positive net present value of BRL 1.86 M in 2015 values (BRL 3.11 M in 2025) and discounted payback in approximately 9 years. A comparative assessment with the 2015 baseline project revealed up to a 10.1% enhancement in the net present value, underscoring the economic advantages of the optimized design. These results confirm the system’s strong economic viability and environmental benefits, providing a valuable guideline for future grid-connected hybrid energy systems. Full article

With the widespread integration of renewable energy sources such as wind and solar power into power systems, their inherent unpredictability and fluctuations present significant challenges to grid stability and security. To address these issues, Battery Energy Storage Systems (BESSs) offer an effective means of enhancing renewable energy absorption and improving the overall system efficiency. This study proposes a coordinated planning method based on the improved bat algorithm (IBA) to tackle the challenges associated with integrating renewable energy into distribution networks. A bi-level optimization framework is introduced to coordinate the planning and operation of the distributed generation (DG) and BESS. The upper-level model focuses on selecting optimal sites and determining the capacity of wind turbines, photovoltaic arrays, and storage systems from an economic perspective. The lower-level model optimizes the curtailment of wind and solar energy and minimizes network losses based on the upper-level planning outcomes. Additionally, the lower-level model also coordinates the dispatch between renewable energy generation and storage systems to ensure the reliable operation of the system. To effectively solve this bi-level optimization model, we have improved the conventional bat algorithm. Simulation results show that the improved bat algorithm not only significantly enhances the convergence speed but also improves the voltage stability, with the photovoltaic utilization rate reaching 90.27% and the wind energy utilization rate reaching 92.18%. These results highlight the practical advantages and success of the proposed method in optimizing renewable energy configurations. Full article

With the deep integration of electricity and carbon trading markets, distribution networks are facing growing operational stress and a shortage of flexible resources under high penetration of renewable energy. This paper proposes a three-layer coordinated planning model for Source–Grid–Load–Storage (SGLS) systems, considering electricity–carbon coupling and flexibility supply–demand balance. The model incorporates a dynamic pricing mechanism that links carbon pricing and time-of-use electricity tariffs, and integrates multi-source flexible resources—such as wind, photovoltaic (PV), conventional generators, energy storage systems (ESS), and controllable loads—to quantify the system’s flexibility capacity. A hierarchical structure encompassing “decision–planning–operation” is designed to achieve coordinated optimization of resource allocation, cost minimization, and operational efficiency. To improve the model’s computational efficiency and convergence performance, an improved adaptive particle swarm optimization (IAPSO) algorithm is developed which integrates dynamic inertia weight adjustment, adaptive acceleration factors, and Gaussian mutation. Simulation studies conducted on the IEEE 33-bus distribution system demonstrate that the proposed model outperforms conventional approaches in terms of operational economy, carbon emission reduction, system flexibility, and renewable energy accommodation. The approach provides effective support for the coordinated deployment of diverse resources in next-generation power systems. Full article

In Poland, renewable energy sources (RESs) are becoming increasingly significant, also in the agricultural sector. Poland has committed to EU energy policies to achieve a 21% share of RESs in gross final energy consumption until 2030. The newest data from 2023 indicates that up to that time, it was 16.56%. The situation is slightly worse in transport, where a 6% share of RESs has been achieved, compared to 14%, which is the target for 2030. The agricultural sector plays a significant role in this transition, as it offers opportunities for bioenergy production, such as biogas and biofuels, derived from agricultural waste and residues, but also by giving a place for photovoltaic panels and windmill farms. While the progress made is evident, challenges persist. This review paper presents the current status and prospects for the development of RESs with particular emphasis on the share of the agricultural sector. To do this, desk research and a literature review have been conducted. The newest statistics have been presented. A significant opportunity for the development of RESs in agriculture lies in harnessing the potential of the raw material base for biogas production, as well as leveraging funding from numerous support programs. A significant opportunity also exists for the development of agrivoltaics. Creating a legal framework for the development of agrivoltaics, as well as creating equal opportunities for all RESs to obtain funding, is a challenge. A major identified challenge that must be addressed, in order to capitalize on the potential of Polish agriculture for the development of RESs, is increasing connection capacity and expanding and modernizing the energy system. Full article

This review explores the pressing need for decarbonization strategies in the off-grid Indigenous communities of Northern Quebec, particularly focusing on Nunavik, where reliance on diesel and fossil fuels for heating and electricity has led to disproportionately excessive greenhouse gas emissions. These emissions underscore the urgent need for sustainable energy alternatives. This study investigates the potential for improving building energy efficiency through advanced thermal insulation, airtight construction, and the elimination of thermal bridges. These measures have been tested in practice; for instance, a prototype house in Quaqtaq achieved over a 54% reduction in energy consumption compared to the standard model. Beyond efficiency improvements, this review assesses the feasibility of renewable energy sources such as wood pellets, solar photovoltaics, wind power, geothermal energy, and run-of-river hydropower in reducing fossil fuel dependence in these communities. For instance, the Innavik hydroelectric project in Inukjuak reduced diesel use by 80% and is expected to cut 700,000 t of CO₂ over 40 years. Solar energy, despite seasonal limitations, can complement other systems, particularly during sunnier months, while wind energy projects such as the Raglan Mine turbines save 4.4 million liters of diesel annually and prevent nearly 12,000 t of CO₂ emissions. Geothermal and run-of-river hydropower systems are identified as long-term and effective solutions. This review emphasizes the role of Indigenous knowledge in guiding the energy transition and ensuring that solutions are culturally appropriate for community needs. By identifying both technological and socio-economic barriers, this review offers a foundation for future research and policy development aimed at enabling a sustainable and equitable energy transition in off-grid Northern Quebec communities. Full article

As the global carbon neutrality process accelerates, the proportion of distributed power sources such as wind power and photovoltaic power continues to increase. This transformation, while promoting the development of clean energy, also brings about the issue of new energy consumption. As wind and solar distributed generation rapidly expands into modern power grids, consumption issues become increasingly prominent. In this paper, a robust optimal scheduling method considering multiple uncertainties is proposed for community microgrids containing multiple renewable energy sources based on potential games. Firstly, the flexible loads of community microgrids are quantitatively classified into four categories, namely critical base loads, shiftable loads, power-adjustable loads, and dispersible loads, and a stochastic model is established for the wind power and load power; secondly, the user’s comprehensive electricity consumption satisfaction is included in the operator’s scheduling considerations, and the user’s demand is quantified by constructing a comprehensive satisfaction function that includes comfort indicators and economic indicators. Further, the flexible load-response expectation uncertainty and renewable generation uncertainty model are used to establish a robust optimization uncertainty set. This set portrays the worst-case scenario. Based on this, a two-stage robust optimization framework is designed: with the dual objectives of minimizing operator cost and maximizing user satisfaction, a potential game model is introduced to achieve a Nash equilibrium between the interests of the operator and the users, and solved by a column and constraint generation algorithm. Finally, the rationality and effectiveness of the proposed method are verified through examples, and the results show that after optimization, the cost dropped from CNY 2843.5 to CNY 1730.8, a reduction of 39.1%, but the user satisfaction with electricity usage increased to over 98%. Full article

The increasing penetration of renewable energy sources (RESs), such as photovoltaic and wind power plants, into the medium-voltage distribution grid creates significant concerns regarding voltage control at local substations. Understanding the specifics of the RES operation impact on the phenomenon and propagation of voltage fluctuations in the distribution grid is important for engineering solutions in the RES design and operation practice. The presented article describes an algorithm for estimating the impact of RES on voltage fluctuations in the medium-voltage grid. The algorithm utilises a RES fixed power factor control mode and is implemented in a grid model developed using software for power flow calculations. The study shows the impact of various RES power factor types on the nature of voltage fluctuations in the distribution grid. The RES operation with lagging reactive power factors, as a method of reducing voltage fluctuation magnitudes, results in a more complex nature of voltage fluctuation propagation compared to those with leading power factor. Based on simulations of a true medium-voltage grid, the possibility of optimal mitigation of voltage fluctuations in a grid by selecting the required RES reactive power factor has been proven. The presented model also allows for calculating changes in distribution grid energy losses depending on the RES reactive power factors, ensuring a practical solution of the control strategy. Full article

Battery energy storage systems (BESS) are considered a good energy source to maintain supply and demand, mitigate intermittency, and ensure grid stability. The primary contribution of this paper is to provide a comprehensive overview of global energy markets and a critical analysis of BESS’ participation in frequency control ancillary service (FCAS) markets. This review synthesises the current state of knowledge on the evolution of the energy market and the role of battery energy storage systems in providing grid stability, particularly frequency control services, with a focus on their integration into evolving high-renewable-energy-source (RES) market structures. Specifically, solar PV and wind energy are emerging as the main drivers of RES expansion, accounting for approximately 61% of the global market share. A BESS offers greater flexibility in storage capacity, scalability and rapid response capabilities, making it an effective solution to address emerging security risks of the system. Moreover, a BESS is able to provide active power support through power smoothing when coupled with solar photovoltaic (PV) and wind generation. In this paper, we provide an overview of the current status of energy markets, the contribution of battery storage systems to grid stability and flexibility, as well as the challenges that BESS face in evolving electricity markets. Full article

The social acceptance of Renewable Energy Sources (RESs) is a decisive factor in the successful implementation of clean energy projects. This study explores the attitudes, demographic profiles, and common misconceptions of citizens in the Region of Epirus, Greece, toward photovoltaic and wind energy installations. Special attention is given to the role of education, age, and access to information—as well as spatial factors such as visual exposure—in shaping public perceptions and influencing acceptance of RES deployment. A structured questionnaire was administered to 320 participants across urban and rural areas, with subdivision between regions with and without visual exposure to RES infrastructure. Findings indicate that urban residents exhibit greater acceptance of RES, while rural inhabitants—especially those in proximity to installations—express skepticism, often grounded in esthetic concerns or perceived procedural injustice. Misinformation and lack of knowledge dominate in areas without visual contact. Statistical analysis confirms that younger and more educated participants are more supportive and environmentally aware. The study highlights the importance of targeted educational interventions, transparent consultation, and spatially sensitive communication strategies in fostering constructive engagement with renewable energy projects. The case of Epirus underscores the need for inclusive, place-based policies to bridge the social acceptance gap and support the national energy transition. Full article

The high-proportion integration of renewable energy sources, represented by wind power and photovoltaics, into active distribution networks (ADNs) can effectively alleviate the pressure associated with advancing China’s dual-carbon goals. However, the high uncertainty in renewable energy output leads to increased system voltage fluctuations and localized voltage violations, posing safety challenges. Consequently, research on optimal dispatch for ADNs with a high penetration of renewable energy has become a current focal point. This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. Subsequently, it introduces optimization dispatch models for ADNs that focus on three key objectives: safety, economy, and low carbon emissions. Furthermore, addressing the challenge of solving non-convex and nonlinear models, the paper highlights model reformulation strategies such as semidefinite relaxation, second-order cone relaxation, and convex inner approximation methods, along with summarizing relevant intelligent solution algorithms. Additionally, in response to the high uncertainty of renewable energy output, it reviews stochastic optimization dispatch strategies for ADNs, encompassing single-stage, two-stage, and multi-stage approaches. Meanwhile, given the promising prospects of large-scale deep reinforcement learning models in the power sector, their applications in ADN optimization dispatch are also reviewed. Finally, the paper outlines potential future research directions for ADN optimization dispatch. Full article

Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO₂ emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents a promising avenue to improve the sustainability, reliability, and efficiency of urban transport networks. A storage system is needed to both ensure a continuous power supply and meet train demand at the station. Batteries (BTs) offer high energy density, while supercapacitors (SCs) offer both a large number of charge and discharge cycles, and high-power density. This paper proposes a hybrid RES (photovoltaic and wind), combined with batteries and supercapacitors constituting the hybrid energy storage system (HESS). One major drawback of trains is the long charging time required in stations, so they have been fitted with SCs to allow them to charge up quickly. A new fuzzy energy management strategy (F-EMS) is proposed. This supervision strategy optimizes the power flow between renewable energy sources, HESS, and trains. DC bus voltage regulation is involved, maintaining BT and SC charging levels within acceptable ranges. The simulation results, carried out using MATLAB/Simulink, demonstrate the effectiveness of the suggested fuzzy energy management strategy for various production conditions and train demand. Full article

This work proposes a new method to refill fuel cell electric vehicle hydrogen tanks from a storage system in hydrogen refueling stations. The new method uses the storage tanks in cascade to supply hydrogen to the refueling station dispensers. This method reduces the hydrogen compressor power requirement and the energy consumption for refilling the vehicle tank; therefore, the proposed alternative design for hydrogen refueling stations is feasible and compatible with low-intensity renewable energy sources like solar photovoltaic, wind farms, or micro-hydro plants. Additionally, the cascade method supplies higher pressure to the dispenser throughout the day, thus reducing the refueling time for specific vehicle driving ranges. The simulation shows that the energy saving using the cascade method achieves 9% to 45%, depending on the vehicle attendance. The hydrogen refueling station design supports a daily vehicle attendance of 9 to 36 with a complete refueling process coverage. The carried-out simulation proves that the vehicle tank achieves the maximum attainable pressure of 700 bars with a storage system of six tanks. The data analysis shows that the daily hourly hydrogen demand follows a sinusoidal function, providing a practical tool to predict the hydrogen demand for any vehicle attendance, allowing the planners and station designers to resize the elements to fulfill the new requirements. The proposed system is also applicable to hydrogen ICE vehicles. Full article

The large-scale integration of new energy is an inevitable trend to achieve the low-carbon transformation of power systems. However, the strong randomness of wind power, photovoltaic power, and loads poses severe challenges to the safe and stable operation of systems. Existing studies demonstrate insufficient integration and handling of source-load bilateral uncertainties in wind–solar–fossil fuel storage complementary systems, resulting in difficulties in balancing economy and low-carbon performance in their energy storage configuration. To address this insufficiency, this study proposes an optimal energy storage configuration method considering source-load uncertainties. Firstly, a deterministic bi-level model is constructed: the upper level aims to minimize the comprehensive cost of the system to determine the energy storage capacity and power, and the lower level aims to minimize the system operation cost to solve the optimal scheduling scheme. Then, wind and solar output, as well as loads, are treated as fuzzy variables based on fuzzy chance constraints, and uncertainty constraints are transformed using clear equivalence class processing to establish a bi-level optimization model that considers uncertainties. A differential evolution algorithm and CPLEX are used for solving the upper and lower levels, respectively. Simulation verification in a certain region shows that the proposed method reduces comprehensive cost by 8.9%, operation cost by 10.3%, the curtailment rate of wind and solar energy by 8.92%, and carbon emissions by 3.51%, which significantly improves the economy and low-carbon performance of the system and provides a reference for the future planning and operation of energy systems. Full article