Search Results (12,518)

This paper proposes an optimal operational framework for enhancing the economic, technical, and environmental performance of a renewable energy-based microgrid. The proposed system integrates photovoltaic (PV) generation, wind turbines (WTs), battery energy storage systems (BESSs), diesel generators (DGs), and utility grid interaction. Three multi-objective optimization algorithms, namely Multi-Objective Particle Swarm Optimization (MOPSO), Multi-Objective Genetic Algorithm (MOGA), and Multi-Objective Celestial Orbit Optimization (MOCOO), are employed to minimize the total operating cost and grid dependency. The obtained results demonstrate that MOPSO achieves the best techno-economic performance with a minimum operating microgrid cost of 2.2 M$/year and a low grid dependency ratio of 0.0333. The operational analysis confirms that the proposed renewable-priority scheduling strategy significantly reduces operational emissions and reliance on the utility grid through coordinated BESS charging/discharging and efficiency-aware DG dispatch. The microgrid (MG) achieves zero-emission operation during operating periods dominated by renewable generation. Furthermore, the DG operates within an efficiency range of 36.8–39.3%, improving fuel utilization and reducing unnecessary emissions. The battery degradation analysis indicates high lifetime cycle capability under shallow depth-of-discharge operation, demonstrating improved long-term operational sustainability. Overall, the proposed framework provides a reliable and economically balanced solution for sustainable microgrid energy management. Full article

The accelerating integration of renewable energy sources into modern power grids has created unprecedented operational challenges, with significant system cost volatility under extreme uncertainty events. To address this challenge, this paper presents a risk-aware stochastic approximate dynamic programming (SADP) algorithm based on machine learning and parallel computing architectures. The algorithm learns optimal coordination strategies for source-grid-load-storage resources while explicitly quantifying and mitigating tail risk events that conventional approaches overlook. First, a risk-averse stochastic optimization model is constructed, which captures the complex interdependencies between renewable generation uncertainty, demand variability, and flexible resource coordination through second-order cone programming formulations. This model integrates the GlueVaR (Glued Value-at-Risk) metric, enabling simultaneous optimization across multiple risk horizons with adjustable conservatism parameters. Second, to solve the established model efficiently, an SADP algorithm based on risk-averse approximate value functions (RAVFs) is proposed, in which the training process of the RAVFs employs machine learning principles to directly encode risk preferences into operational decisions. By integrating GlueVaR into offline training across 5000 probabilistically weighted scenarios, the algorithm discovers emergent coordination patterns between distributed resources, which are rarely identified by human operators. Third, a large-scale parallel computing architecture is implemented for the SADP algorithm. This architecture decomposes the multi-period optimization problem into single-period coordinated sub-problems. During offline training, parallel computing of a series of single-period sub-problems can be performed across all probabilistic scenarios, significantly reducing training time. Extensive validation on both the modified IEEE 33-bus and 69-bus systems with integrated wind turbines, photovoltaic plants, energy storage systems, and demand response capabilities demonstrates remarkable performance improvements. Convergence analysis reveals that the AVFs stabilize within 30 training iterations, achieving sub-160 s solution times in online application even for complex networks with heterogeneous resources. By enabling real-time risk-aware decision-making under severe uncertainty, the proposed method provides grid operators with actionable strategies that balance economic efficiency and operational resilience. Full article

To alleviate grid peak-shaving pressure from high-penetration renewable energy integration, coupling thermal energy storage (TES) with coal-fired power plants is an effective approach for enhancing operational flexibility. This paper systematically investigates the peak-shaving performance of a coal-fired unit integrated with molten salt storage and heat pump storage systems, focusing on load response characteristics, peak-shaving capability, and the influence of discharge strategies on thermodynamic performance under various rated turbine heat acceptance (THA) conditions. The results indicate that, under identical peak-shaving capacity, the molten salt system exhibits greater storage capacity, which increases with rising THA levels, whereas the heat pump storage capacity remains largely THA-independent. Regarding discharge strategies, replacing high-pressure extraction steam achieves the fastest ramp rate and largest incremental power output, introducing steam into the intermediate-pressure cylinder yields the slowest response but highest round-trip efficiency, and replacing low-pressure extraction steam delivers the smallest peak-shaving capacity and lowest round-trip efficiency. Although TES integration slightly reduces thermal efficiency due to heat exchange losses, this trade-off is justified by significant flexibility improvement, demonstrating clear engineering value for high-renewable grids. Full article

This study presents a comparative evaluation of geopolymer foams incorporating either commercially available shape-stabilized phase change materials (PCMs) or laboratory-developed diatomite–paraffin PCM granules with controlled particle size fractions ranging from <1.6 mm to >2.5 mm. All PCM variants were incorporated at a constant dosage of 7.5 wt.% to isolate the influence of PCM type on the properties of the resulting composites. The commercial materials comprised PX-4, PX15, and PX20 (Rubitherm Technologies GmbH), whereas the laboratory-developed PCM consisted of paraffin immobilized within a porous diatomite matrix to produce granular shape-stabilized composites. The experimental program included the determination of bulk density, total porosity, pore size distribution, thermal conductivity (λ), thermal resistance (R), specific heat capacity (Cp), and compressive strength. The pore structure was characterized by mercury intrusion porosimetry (MIP), while the morphology and dispersion of PCM particles within the geopolymer matrix were investigated using scanning electron microscopy (SEM). All mixtures were produced using the same alkali-activated matrix and identical curing conditions, with the PCM content maintained at 7.5 wt.%. The results demonstrated that the type of PCM significantly affected the microstructure and thermophysical performance of the geopolymer foams. The laboratory-developed diatomite–paraffin PCM provided the most favorable thermal insulation performance, exhibiting the lowest thermal conductivity (0.095 W/m·K) together with the highest thermal resistance (0.278 m²·K/W). In contrast, the commercial PX15 and PX20 materials exhibited the highest specific heat capacities (1.740 and 1.778 kJ/kg·K, respectively), indicating superior thermal energy storage capability. In addition, the estimated production cost of the laboratory-developed PCM (2.5–4.0 EUR/kg) was substantially lower than that of the commercial PX materials (approximately 20 EUR/kg), highlighting its potential as a cost-effective alternative for sustainable, energy-efficient building materials. These findings demonstrate that both commercial and laboratory-developed PCM systems can effectively enhance the functionality of geopolymer foams, although they provide different balances between thermal insulation, heat storage capacity, and production cost. Full article

With the rapid development of commercial aerospace, emerging applications such as satellite constellations, space-based communications, and orbital computing platforms have significantly increased the demand for efficient and reliable spacecraft power systems. Abundant exploitable energy exists in the space environment, including Air Mass Zero (AM0) solar radiation, spacecraft surface temperature gradients, ambient electromagnetic radiation, and radioisotope thermal energy, making multi-source energy harvesting a promising approach for improving satellite energy autonomy and system redundancy. This paper reviews the following four key space energy harvesting technologies: photovoltaic power generation, radio frequency (RF) energy harvesting, thermoelectric energy harvesting, and radioisotope thermoelectric generators (RTGs). The impacts of harsh space environmental factors on device performance and reliability are analyzed, and the applicability of different technologies in low Earth orbit (LEO), geostationary orbit (GEO), and deep-space missions is discussed. Furthermore, a multi-source self-powered satellite energy architecture integrating energy harvesting, energy storage, and power management is proposed. Finally, the major challenges and future development trends of satellite energy harvesting systems are summarized. Full article

Sustainable agricultural development requires regional agricultural systems to balance output growth, resource efficiency, ecological protection, and long-term resilience. In mountainous and ecologically sensitive regions, identifying the development constraints and statistically derived marginal contribution thresholds of agriculture is essential for promoting green transformation and sustainable land use. Taking Yunnan Province, China, as a representative plateau mountainous agricultural region, this study uses provincial annual data from 1990 to 2023 to quantitatively identify the key drivers and threshold characteristics of agricultural development under multidimensional constraints. A multidimensional indicator system was constructed covering fiscal and investment support, agricultural production inputs, rural infrastructure, and labor and population conditions. Ridge regression was employed to address multicollinearity among explanatory variables, Bootstrap approximate inference was used to improve the robustness of coefficient estimation, and the SHAP interpretation framework was introduced to rank key driving factors and identify marginal contribution thresholds. By integrating ridge regression, Bootstrap approximate inference, SHAP-based contribution ranking, and threshold identification, the proposed framework advances prior agricultural sustainability studies by linking coefficient-based factor analysis with interpretable marginal contribution thresholds under conditions of high multicollinearity and multidimensional resource constraints. The results show that agricultural development in Yunnan is characterized by multidimensional resource and infrastructure constraints. Rural electricity consumption, total reservoir storage capacity, fixed asset investment in agriculture, forestry, animal husbandry and fisheries, local public fiscal budget expenditure, and agricultural population generally act as positive supporting factors. Rural electricity consumption is the most stable and core driver across the aggregate and three sectoral models. In contrast, pesticide and fertilizer inputs show significant negative associations in most models, suggesting that future agricultural development in Yunnan is unlikely to be sustainably supported by continued expansion of high-intensity chemical inputs. Sectoral heterogeneity is also evident: agriculture and animal husbandry are more dependent on energy, water resources, and mechanization, whereas forestry shows a more distinct operational structure. The SHAP dependence analysis identifies several statistically derived marginal contribution thresholds, including rural electricity consumption of approximately 6.055 billion kWh, total reservoir storage capacity of approximately 10.395 billion m³, total agricultural machinery power of approximately 19.8324 million kW, pesticide use of approximately 37,500 tons, and fertilizer application of approximately 1.5238 million tons. These values should be interpreted as empirical transition points in the modeled marginal contributions rather than definitive biophysical ecological limits. They indicate that the sustainability-related constraint structure of agricultural development in Yunnan is not a single output ceiling but a composite interval shaped by infrastructure support capacity, factor allocation conditions, and the declining marginal contribution of high-intensity chemical inputs. The findings provide directional quantitative evidence for sustainable agricultural governance, agricultural green transformation, and differentiated policy discussion in mountainous agricultural regions and offer reference implications for advancing SDG 2 and SDG 15 through the coordination of food-related production, resource use efficiency, and ecosystem conservation. The identified thresholds should be interpreted as model-derived marginal contribution transition points rather than operational policy cutoffs or directly enforceable ecological standards. Full article

Pumped hydro storage remains one of the most established technologies for balancing supply and demand in electricity markets with high shares of renewable energy. This paper investigates the short-term economic optimization of a pumped hydro storage plant operating under real day-ahead market conditions. A Mixed-Integer Linear Programming model is used to optimize hourly dispatch decisions based on actual day-ahead electricity prices in Slovenia for the year 2024. The model accounts for technical constraints, including turbine and pump capacities, round-trip efficiency, energy storage limits, and restricted startup frequencies. The simulation results show that pumped hydro storage can achieve a positive market-based operating result by responding effectively to price volatility and frequent negative pricing events. Seasonal variations reveal higher revenues during summer months due to solar overproduction. The findings confirm the potential of pumped hydro storage to enhance grid flexibility and support the implementation of national energy transition objectives. By linking large-scale energy storage operations with renewable energy integration, grid flexibility, and market-based dispatch, the study also contributes to the technical and economic dimensions of sustainable energy system development. Full article

Adding an upper reservoir to conventional cascade hydropower stations to create pumped-storage systems is an effective strategy for enhancing hydropower regulation capacity and promoting high proportion of variable renewable energy consumption. To leverage the cross-seasonal energy and intra-day power regulation capabilities of such hybrid systems, this paper proposes a multi-scale nested dispatch and benefit assessment method. The coordination principles between pumped storage and cascade hydropower under high variable renewable energy penetration are first analyzed. Subsequently, a dynamic time-of-use electricity pricing mechanism is developed by capitalizing on the temporal characteristics of net load, and a multi-scale nested scheduling model that incorporates grid regulation demands is established. A techno-economic assessment framework is further developed to assess the comprehensive benefits of the pumped-storage retrofitting. The Wujiang Basin case study demonstrates significant benefits: a 4.5% improvement in peak–valley difference reduction, a decrease of 1039 GWh in annual variable renewable energy curtailment (8.8% of the system’s total), and a 30.8% rise in generation benefits. Under wet and dry hydrological years, generation benefits increase by 787 million and 645 million CNY, respectively. These results indicate that implementing pumped-storage retrofitting in cascade hydropower basins with abundant but seasonally uneven inflow can better align grid regulation requirements with project economic viability. Full article

This scientific article presents a comprehensive case study detailing the design of a fully off-grid household in Poland, utilizing an energy solution that combines high-pressure hydrogen energy storage and photovoltaic (PV) technology. In response to the growing demand for sustainable and self-sufficient energy sources, the current study investigates the efficiency and yearly energy balance of this innovative system. The off-grid household is powered by a hybrid system that seamlessly integrates PV panels to harness solar energy and a high-pressure hydrogen energy storage system for long-term energy management. The presented case study examines the design and performance of a system integrating solar energy production with hydrogen storage. Through an analysis of real-world data and operational parameters, this research contributes valuable insights into the viability of such an off-grid solution in Polish environmental conditions. These findings provided an interesting approach to off-grid residential systems, offering a glimpse into the possible future of residential energetic autonomy in the pursuit of a greener and more resilient energy landscape. Full article

This review shows that lignocellulosic biomass is not merely an abundant feedstock for nanocellulose production but a strategic platform for building the next generation of sustainable, high-performance materials, integrating feedstock diversity, processing logic, characterization, market direction, and translational applications into a single narrative. Comparing woody and non-woody biomass through the lens of processability, recalcitrance, and value creation while showing why agricultural residues are increasingly central to low-cost, circular nanocellulose production beyond the usual acid-hydrolysis-centered discussion by emphasizing enzymatic hydrolysis as a lower-energy, lower-toxicity alternative while still acknowledging the persistent industrial advantages and environmental costs of chemical and mechanical routes. A further strength of this review is its effort to bridge structure and function: it links extraction strategy to morphology, crystallinity, thermal stability, and surface chemistry, then connects these properties to real applications in packaging, drug delivery, electronics, filtration, energy storage, and biomedical systems. Its distinctive contribution lies in showing that the future of nanocellulose depends not only on how it is extracted but also on how intelligently the biomass source, processing route, material performance, and market need are aligned. Full article

This paper presents a comprehensive review of state-of-the-art developments in electric vehicle (EV) charging technologies, charging stations, and charging protocols, with particular emphasis on their integration with renewable energy sources (RESs). EV chargers are generally classified into on-board and off-board configurations. This study examines recent designs and advanced control strategies for both AC/DC and DC/DC power conversion stages, highlighting key technical aspects, recent innovations, and existing challenges. Furthermore, it provides an in-depth discussion of emerging multiport EV charger architectures that integrate photovoltaic (PV) systems, energy storage units, EVs, and the power grid within a unified framework. A comparative analysis is also presented to evaluate various converter topologies and energy management strategies used in the AC/DC and DC/DC stages of EV charging systems. Critical performance indicators such as power rating, output voltage level, efficiency, economic feasibility, and system complexity are also discussed. A comprehensive comparison is conducted among 13 review papers between 2015 and 2026, identifying key trends, methodological differences, and common findings. Full article

Conventional soft open points (SOPs) suffer from limited transfer capacity during distribution network faults. To address this issue, this paper proposes an integrated energy storage system and soft open point (ES-SOP) along with a power path dynamic reconfiguration method. The device consists of an M × N AC switch matrix, N AC/DC converters, and a common DC bus with energy storage. This structure provides three distinct power paths: a mechanical direct path, a third-party grid path, and an energy storage path. A seamless reconfiguration technology is developed to eliminate inrush currents during mechanical switching. It combines multi-unit virtual synchronous generator (VSG) pre-synchronization with a DC bus voltage droop coordination mechanism. The overall control follows a two-time-scale strategy. On a long time scale, a heuristic rule selects the most suitable healthy grid as the mechanical source. On a short time scale, the droop parameters of the converters are optimized to autonomously share the remaining power between the third-party grid path and the energy storage path. This allocation minimizes losses and requires no fast communication. Hardware-in-the-loop experiments verify the performance: the proposed method completely suppresses inrush current, keeps DC bus voltage fluctuation below 20 V during mode transitions, and achieves a transfer efficiency of approximately 98.5%. Full article

To explore the optimized operating strategies coupling floor cooling with cold storage for thermal active systems (TABSs), effects of operating time on indoor thermal environment, cold storage capacity, energy use and running cost were studied. Simulations were conducted based on an actual office building equipped with floor cooling. To take full advantage of the TABS and off−peak electricity, four operating cases with nighttime floor cold storage were proposed, namely C₁ (2:00–8:00), which operated only during the off−peak hours, C₂ (2:00–10:00), C₃ (2:00–12:00), and C₄ (2:00–14:00), which operated during the off−peak and flat hours. A simulation case of C₀ operating during daytime (7:00–17:00) was also proposed. Simulation results show that the C₁ and C₂ conditions with shorter operating hours result in higher indoor temperatures, which cannot ensure indoor thermal comfort. The PMV index in C₃ and C₄ conditions can be kept between −1 and 1, which meets the thermal comfort demand of Grade II. Considering that the operating duration of C₃ is the same as the occupied hours, the cold storage capacity, cooling loss, cooling supply and release process, etc., of this case are further analyzed based on data of a typical day. The floor and ceiling slabs store most of the cooling energy (72.7%) during the night; inner walls also store part of the cooling energy (23.3%) and cooling loss during cold storage accounts for approximately 3.1%. During working hours, the cooling energy released is lower than the cooling load, which makes indoor temperatures increase continuously. Compared with case C₀, case C₃ has same power use while saving 2.8% of running costs. Case C₄ provides a higher level of thermal comfort, while saving 0.9% of costs with a 1.5% increment in electricity use. This study provides detailed data about cold storage strategies coupling with floor cooling in TABS, which can be used to save running cost. Full article

Amid the global drive for carbon peaking and carbon neutrality, integrating renewable energy into building energy systems to mitigate photovoltaic (PV) intermittency and realize low-carbon energy supply has become a critical research frontier. This study proposes a novel dual-storage renewable energy system integrating solar energy storage system (SES), hydrogen energy storage system (HES), and an alkaline fuel cell (AFC). The model was validated using a two-story single-family residence as the case study, with residential load profiles and Xi’an’s climatic conditions considered under real-world scenarios. An adaptive energy management strategy is developed to dynamically coordinate PV utilization, hydrogen dispatch, and grid interaction, while recovering AFC waste heat to enhance overall efficiency. Targeting minimized lifecycle cost (LCC) and levelized cost of energy (LCOE), the GenOpt multi-objective optimization model optimizes key design parameters. Key results show 74.2% annual renewable energy penetration, 68.5% carbon reduction versus conventional systems, and robust seasonal operation: PV dominates summer supply (81.3% self-sufficiency), while AFC compensates in winter (62.4% hydrogen contribution). The system reduces annual grid dependence by 43.7% with a minimum LCOE of ~ 12.9 USD/MWh, bridging technical feasibility and economic practicality to provide actionable insights for building-scale renewable integration. Full article

In modern power systems with high penetration of renewable energy, the efficient interaction between demand-side flexible resources and the power grid has become a key approach to mitigating renewable generation fluctuations. As a typical flexible load, air conditioning loads exhibit significant potential for renewable energy utilization due to their large scale, low cost, and fast response capability. However, existing strategies for photovoltaic (PV) accommodation fail to fully consider the coordinated scheduling between heterogeneous air conditioning clusters and energy storage systems, and lack explicit modeling of the dynamic response of air conditioning loads. As a result, they are unable to effectively address the requirements induced by renewable energy fluctuations. To address these issues, this paper proposes a coordinated scheduling strategy for heterogeneous air conditioning clusters considering dynamic response characteristics, aimed at PV fluctuation smoothing. A hierarchical framework of “fixed-frequency priority, variable-frequency compensation, and energy storage backup” is developed. By incorporating response dynamics into the scheduling process, power–energy complementarity between air conditioning clusters and energy storage systems is achieved. Experimental results demonstrate that the proposed strategy improves the PV fluctuation smoothing rate from 77.16% to 100%, significantly enhancing the local PV accommodation capability within the park. Full article