Search Results (3,513)

Water supply systems (WSSs) are energy-intensive infrastructure that present significant opportunities for decarbonization through the integration of renewable energy (RE). This study evaluated the RE generation potential within the WSSs of Incheon Metropolitan City (IMC), Republic of Korea, using a site-specific, data-driven approach. Three RE technologies were considered: solar photovoltaic (PV) systems installed in water-treatment plants (WTPs), micro-hydropower (MHP) utilizing the residual head at the inlet chamber of a WTP, and in-pipe MHP recovery using the discharge from water supply tanks in water distribution networks. Actual facility data, hydraulic simulations, and spatial analyses were used to estimate an annual RE generation potential of 32,811 MWh in the WSSs of IMC, including 18,830 MWh from solar PV in WTPs, 4938 MWh from MHP in WTPs, and 9043 MWh from in-pipe MHP. This corresponds to an energy self-sufficiency rate of approximately 22.3%, relative to the IMC WSS total annual electricity consumption of 147,293 MWh in 2022. The results demonstrated that decentralized RE deployment within existing WSSs can significantly reduce grid dependency and carbon emissions. This study provides a rare empirical benchmark for RE integration in large-scale WSSs and offers practical insights for municipalities seeking energy-resilient and climate-aligned infrastructure transitions. Full article

In recent years, there has been a fast expansion in the usage of renewable energy sources (RESs) in power distribution systems. Numerous advantages result from this advancement, such as environmental friendliness, cost-effective power generation, easier maintenance, and energy sustainability and reliability. Reducing reliance on fossil fuels, which are of significant environmental concern, and increasing energy efficiency are two benefits of integrating RESs into maritime systems, such as port microgrids. As a result, ports are implementing several programs to increase energy efficiency using various RESs that are supported by power electronic converters. To highlight the most recent developments in seaport electrification and infrastructure, this work conducts a systematic review. It addresses important issues like energy efficiency enhancements, environmental concerns, the integration of renewable energy sources, the Internet of Things (IoT), and regulatory and legal compliance. The study also discusses technology strategies like digitization, electrification, onshore power supply systems, and port energy storage options. Operational tactics, including peak-shaving methods and energy-efficient operations, are also covered. Additionally, an infrastructure framework—which includes port microgrids and smart seaport microgrids—that is intended to enhance energy efficiency in contemporary ports is examined. Full article

This study investigates the energy consumption characteristics of individual and clustered thermal storage electric heating systems, focusing on their sustainability implications for regional load distribution and user energy consumption patterns. Simulation results show that thermal storage electric heating shifts peak energy demand from daytime to nighttime low-price hours, reducing electricity costs and optimizing grid load balancing. As the proportion of thermal storage electric heating increases from 10% to 30%, the daytime minimum load reduction rate rises from 7% to 22%, while the nighttime maximum load increase rate increases from 16% to 63%. This operational mode supports sustainable energy usage by alleviating daytime grid peak pressure and leveraging low-cost, off-peak electricity for heat storage. The findings highlight the potential of thermal storage electric heating to enhance energy efficiency, integrate renewable energy, and promote grid stability, contributing to a more sustainable energy system. Full article

While technologies like renewable energy and low-carbon transportation are known to mitigate carbon emissions from urban expansion, achieving carbon neutrality during this process remains a critical unresolved challenge. This issue is particularly pressing for developing countries striving to balance urbanization with carbon reduction. Taking Qionglai City as a case study, this study simulated the territorial spatial functional patterns (TSFPs) and carbon emission distribution for 2025 and 2030. Based on the key drivers of carbon emissions from urban expansion identified through the Geographical and Temporal Weighted Regression (GTWR) model, carbon-neutral pathways were designed for two scenarios: urban expansion scenarios under historical evolution patterns (Scenario I) and urban expansion scenarios optimized under carbon neutrality targets (Scenario II). The results indicate that (1) urban space is projected to expand from 6094.73 hm² in 2020 to 6249.77 hm² in 2025 and 6385.75 hm² in 2030; (2) total carbon emissions are forecasted to reach 1.25 × 10⁶ t (metric tons) and 1.40 × 10⁶ t in 2025 and 2030, respectively, exhibiting a spatial pattern of “high in the central-eastern regions, low in the west”; (3) GDP, Net Primary Productivity (NPP), and the number of fuel vehicles are the dominant drivers of carbon emissions from urban expansion; and (4) a four-pronged strategy, optimizing urban green space vegetation types, replacing fuel vehicles with new energy vehicles, controlling carbon emissions per GDP, and purchasing carbon credits, proves effective. Scenario II presents the optimal pathway: carbon neutrality in the expansion zone can be achieved by 2025 using the first three measures (e.g., optimizing 66.73 hm² of green space, replacing 800 fuel vehicles, and maintaining emissions at 0.21 t/10⁴ CNY per GDP). By 2030, carbon neutrality can be achieved by implementing all four measures (e.g., optimizing 67.57 hm² of green space, replacing 1470 fuel vehicles, and achieving 0.15 t/10⁴ CNY per GDP). This study provides a methodological basis for local governments to promote low-carbon urban development and offers practical insights for developing nations to reconcile urban expansion with carbon neutrality goals. Full article

The article discusses the current challenges facing the energy sector in the context of climate policy, technological transformation, and the urgent need to increase energy efficiency while reducing greenhouse gas emissions. Modern thermal energy conversion technologies are analyzed, including supercritical steam and gas–steam cycles, as well as distributed systems using renewable fuels and microturbines. Particular attention is given to innovative systems with isothermal expansion, which theoretically allow operation close to the efficiency limit defined by the Carnot cycle. The study presents calculation results for conventional systems (steam, gas with regeneration, and Organic Rankine Cycle) and proposes a novel isothermal air turbine cycle. In a combined gas–steam configuration, the proposed cycle achieved an efficiency exceeding 43% at a relatively low heat source temperature of 700 K, clearly outperforming conventional steam and ORC systems under the same thermal conditions. The use of a simple working medium (air), combined with the potential for integration with renewable energy sources, makes this concept a promising and viable alternative to traditional Rankine and Brayton cycles in thermally constrained applications. Full article

To enhance the efficiency of renewable energy consumption and reduce reliance on fossil fuels, the study addresses the challenges of distributed photovoltaic and energy storage integration in distribution networks, such as voltage fluctuations, safety risks, and insufficient converter considerations to the distribution network. Through a four-dimensional comprehensive evaluation system including grid-strength quantification indicators like the generalized short-circuit ratio, a multi-objective mathematical model-based performance evaluation system using an analytic hierarchy process and criteria importance through the intercriteria correlation method has been established, and an optimization model for the configuration of photovoltaic and energy storage equipment is optimized. The study innovatively proposes a multi-type synchronous control framework enabling dynamic GFL/GFM converter selection at different nodes, overcoming traditional single-control limitations. The simulation results show that the proposed optimal configuration scheme can effectively improve the operating states and reduce the energy consumption of the distribution network. Full article

Bamboo, as a rapidly renewable biomass material, has garnered significant attention in contemporary research due to its cost effectiveness as a viable source for supercapacitor electrode materials. However, untreated bamboo as an electrode material often leads to poor connectivity and uneven pore distribution. This study introduces a novel approach by using bamboo-derived biological carbon as a conductive substrate, subjecting it to carbonization through white-rot fungal pretreatment to enhance the pore structure and then loading it with nano-MnO₂ sheets via a hydrothermal process. The result is a binderless, self-supporting supercapacitor electrode material, denoted as MnO₂/hyphae/bamboo-derived carbon (HBC-2M). When compared to untreated bamboo carbon (HBC-0), HBC-2M exhibits an increased number of energy storage sites, enhanced electrolyte ion transport channels, and superior electrochemical performance. HBC-2M achieves a maximum mass-specific capacitance of 133.69 F·g⁻¹ and a maximum area-specific capacitance of 2367.95 mF·cm⁻² and retains approximately 87.46% of its capacitance after 2000 cycles. This research suggests a promising future for bamboo charcoal in supercapacitors. Full article

Islanded DC microgrids face challenges in voltage stability and communication overhead due to renewable energy variability. A novel enhanced distributed coordinated control framework, based on adaptive event-triggered mechanisms, is developed for the efficient management of multiple hybrid energy storage systems (HESSs) in islanded DC microgrids (MGs). We propose a hierarchical distributed control framework integrating ANN-based controllers and adaptive event-triggered mechanisms to dynamically regulate power flow and minimise communication. This system utilises a hierarchical coordinated control method (HCCM) with primary virtual resistance droop control integrated with state-of-charge (SoC) management and secondary control for voltage regulation and proportional current distribution through optimised communication networks. The integration of artificial neural network (ANN)-based controllers alongside traditional PI control leads to an improvement in system responsiveness. The control approach dynamically adjusts the trigger parameters to minimise communication overhead with tight voltage regulation. An extensive simulation using MATLAB/Simulink shows how the system can effectively manage variability in renewable energy sources and maintain stable voltage profiles with precise power distribution and minimal bus voltage fluctuations. Simulations confirm enhanced voltage regulation (±0.5% deviation), proportional current sharing (98% accuracy), and 60% communication reduction under load transients (outcomes). 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

Renewable Energy Communities (RECs) are central to Europe’s strategy for reducing greenhouse gas emissions and advancing a sustainable, decentralized energy system. RECs aim to transform consumers into prosumers—individuals who both produce and consume energy—thereby enhancing energy efficiency, local autonomy, and citizen engagement. This study introduces a novel Geographic Information System (GIS)-based methodology that integrates socio-economic and spatial data to support the design of optimal REC configurations. QGIS 3.40.9 “Batislava” tool is used to simulate site-specific energy distribution scenarios, enabling data-driven planning. By combining a Composite Energy Vulnerability Index (CEVI), Rooftop Solar Potential (RSP), and the distribution of urban gardens (UGs), the approach identifies priority urban zones for intervention. Urban gardens offer multifunctional public spaces that can support renewable infrastructures while fostering local resilience and energy equity. Applied to the city of Rome, the methodology provides a replicable framework to guide REC deployment in vulnerable urban contexts. The results demonstrate that 11 of the 18 highest-priority areas already host urban gardens, highlighting their potential as catalysts for collective PV systems and social engagement. The proposed model advances sustainability objectives by integrating environmental, social, and spatial dimensions—positioning RECs and urban agriculture as synergistic tools for inclusive energy transition and climate change mitigation. Full article

The global transition toward renewable energy and the electrification of transportation is imposing unprecedented power quality (PQ) challenges on modern distribution networks, rendering traditional governance models inadequate. To bridge the existing research gap of the lack of a holistic analytical framework, this review first establishes a systematic diagnostic methodology by introducing the “Triadic Governance Objectives–Scenario Matrix (TGO-SM),” which maps core objectives—harmonic suppression, voltage regulation, and three-phase balancing—against the distinct demands of high-penetration photovoltaic (PV), electric vehicle (EV) charging, and energy storage scenarios. Building upon this problem identification framework, the paper then provides a comprehensive review of advanced mitigation technologies, analyzing the performance and application of key ‘unit operations’ such as static synchronous compensators (STATCOMs), solid-state transformers (SSTs), grid-forming (GFM) inverters, and unified power quality conditioners (UPQCs). Subsequently, the review deconstructs the multi-timescale control conflicts inherent in these systems and proposes the forward-looking paradigm of “Distributed Dynamic Collaborative Governance (DDCG).” This future architecture envisions a fully autonomous grid, integrating edge intelligence, digital twins, and blockchain to shift from reactive compensation to predictive governance. Through this structured approach, the research provides a coherent strategy and a crucial theoretical roadmap for navigating the complexities of modern distribution grids and advancing toward a resilient and autonomous future. Full article

Smart Grid, integrating modern information and communication technologies with traditional power infrastructure, is already widely used in many countries around the world. Its domain is generating large amounts of energy and, at the same time, measuring data from various sources, especially Renewable Energy Sources. Acquiring measurement data from generators and power receivers requires appropriate infrastructure and tools. An even greater challenge is the effective processing of measurement data in order to obtain information helpful in energy management in Smart Grid. The article will present an effective method of acquiring and processing measurement data from a photovoltaic system with a peak power of 50 kWp supplying the administrative building of the university. Unsupervised clustering will be used to create signatures of both generated and consumed power. Analysis of the relationships between measured network parameters in the three-state space allows for a quick determination of the power generated by the photovoltaic system and the power needed to power the building. The applied approach can have a wide practical application, both in Energy Management in institutional buildings. It can also be successfully used to train AI algorithms to categorize operating states in Smart Grid. The traditional and AI-assisted algorithms used by the authors are used to obtain practical information about the operation of Smart Grid. Such expert-validated knowledge is highly desirable in Advanced Process Control, which aims to optimize processes in real time. 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

Recent advances in prefabricated construction have enabled modular systems offering structural performance, rapid assembly, and design flexibility. Textile Ceramic Technology (TCT) integrates ceramic elements within a stainless-steel mesh, creating versatile architectural envelopes for façades, roofs, and pavements. This study investigates the integration of silicon photovoltaic (PV) modules into TCT to develop an industrialized Building-Integrated Photovoltaics (BIPV) system that maintains energy efficiency and visual coherence. Three full-scale solar brick prototypes are presented, detailing design objectives, experimental results, and conclusions. The first prototype demonstrated the feasibility of scaling small silicon PV units with good efficiency but limited aesthetic integration. The second embedded PV cells within ceramic bricks, improving aesthetics while maintaining electrical performance. Durability tests—including humidity, temperature cycling, wind, and hail impact—confirmed system stability, though structural reinforcement is needed for impact resistance. The third prototype outlines future work focusing on modularity and industrial scalability. Results confirm the technical viability of silicon PV integration in TCT, enabling active façades that generate renewable energy without compromising architectural freedom or aesthetics. This research advances industrialized, sustainable building envelopes that reduce environmental impact through distributed energy generation. Full article

South Africa’s transition to a renewable-powered grid faces critical challenges due to the inherent variability of wind and solar generation as well as the need for economically viable and reliable dispatch strategies. This study proposes a scenario-based stochastic optimization framework that integrates machine learning forecasting and uncertainty modeling to enhance operational decision making. A hybrid Long Short-Term Memory–XGBoost model is employed to forecast wind, photovoltaic (PV) power, concentrated solar power (CSP), and electricity demand, with Monte Carlo dropout and quantile regression used for uncertainty quantification. Scenarios are generated using appropriate probability distributions and are reduced via Temporal-Aware K-Means Scenario Reduction for tractability. A two-stage stochastic program then optimizes power dispatch under uncertainty, benchmarked against Deterministic, Rule-Based, and Perfect Information models. Simulation results over 7 days using five years of real-world South African energy data show that the stochastic model strikes a favorable balance between cost and reliability. It incurs a total system cost of ZAR 1.748 billion, with 1625 MWh of load shedding and 1283 MWh of curtailment, significantly outperforming the deterministic model (ZAR 1.763 billion; 3538 MWh load shedding; 59 MWh curtailment) and the rule-based model (ZAR 1.760 billion, 1.809 MWh load shedding; 1475 MWh curtailment). The proposed stochastic framework demonstrates strong potential for improving renewable integration, reducing system penalties, and enhancing grid resilience in the face of forecast uncertainty. Full article