Search Results (135)

Seawater reverse osmosis (SWRO) desalination is electricity-intensive, making its environmental performance highly dependent on the power supply. This study couples site-specific energy-system modelling with life cycle assessment to examine how renewable integration changes both total impacts and life-cycle hotspots. A modelled SWRO plant with a specific electricity consumption of 3.4 kWh m⁻³, derived from a process model for Mediterranean feedwater at 48% recovery with energy recovery devices, was assessed in Gela and Trapani, two grid-connected coastal sites with contrasting wind resources, and Lipari, a non-interconnected island with carbon-intensive backup generation. Grid-only, photovoltaic (PV)-grid, wind-grid, and PV-wind-grid configurations were modelled in HOMER Pro without storage and with excess electricity limited to 13%, then evaluated in SimaPro using Environmental Footprint 3.1. Hybrid configurations supplied 46.7%, 64.4%, and 53.3% renewable electricity in Gela, Trapani, and Lipari, reducing climate-change impacts by 30%, 42%, and 45%, respectively. Renewable integration also lowered fossil resource use, whereas PV-containing scenarios increased land and mineral/metal resource use. As electricity-related impacts declined, chemical consumption became the main non-energy hotspot, particularly for ecotoxicity, freshwater and eutrophication. Environmental performance therefore depends not only on renewable penetration, but also on technology choice and the residual electricity supply. Comprehensive system boundaries are essential when planning lower-carbon desalination for coastal and island water security. Full article

This research work conducts an economic, operational, and environmental evaluation of a solar–wind–battery–hydrogen hybrid renewable energy generation system for a typical household in the Limpopo province of South Africa. In the recommended configuration, the system will comprise a 5.0 kWp solar PV array, 1.0 kW wind turbine, 15 kWh lithium-ion battery, 1.5 kW electrolysis, 8 kg hydrogen storage tank, 1.0 kW fuel cell, and 5.0 kW power converter. Based on the base scenario, the proposed energy system completely satisfies the total electricity consumption of 5475 kWh per annum without any energy shortfall and a 100% RE contribution. The electricity production from solar PV and wind amounts to 8016 kWh and 1115 kWh per annum, respectively, and the green hydrogen produced is 70.3 kg/year. Though the fuel cell did not play any role in meeting the electrical requirements in the base year, hydrogen acts as a long-term storage medium and improves the resilience of the system. The total present value cost of the optimal energy system is USD 35,016, the annual cost is USD 3005/year, the electricity cost is USD 0.549/kWh, and the hydrogen cost is USD 12.02/kg. This work adds to the existing literature by offering a modeling framework for households in Limpopo. Full article

With the growing risks posed by extreme weather, such as cold waves, to the secure operation of power systems integrated with large-scale wind and PV power, conventional multi-energy complementary modes fail to cope with the drastic output fluctuations in renewable resources. In this study, a hydro–wind–PV joint-optimized scheduling model is established to quantify the compensation requirement of wind–PV power output fluctuations and to optimize the hydropower compensatory regulation, aiming to clarify the actual effects and inherent limitations of hydropower under cold-wave scenarios. Based on 86-year hourly operational simulation data of a practical virtual case in northwest China, the main simulation results, limited to a daily time horizon with five statistically extracted scenarios, are as follows: First, cold-wave events significantly raise the peak shaving and compensation pressure of hydropower, with the maximum fluctuation amplitude of new energy output reaching 86.76%. Second, compared with conventional operating conditions, hydropower can satisfy the above compensation demand, whereas the reservoir water level deviates from the normal range by −2.2–3.0 m after scheduling, which leads to water consumption or effective storage occupation of reservoirs. Third, restricted by the hydropower installed capacity and reservoir regulation constraints, the power deficit of 1962 MWh and water spillage of 10.59 million m³ cannot be completely resolved. This study can provide theoretical support for analyzing wind–PV fluctuation risks and revealing the multi-energy coupling operation mechanism in cold-wave environments. Full article

An advanced power control and energy management strategy for an isolated hybrid microgrid system is presented in this paper. With the help of a battery energy storage system (BESS), the architecture combines a wind turbine (WT) emulator, photovoltaic (PV) arrays, and a variable-speed diesel generator (VSDG) emulated by a controlled DC source on a 1/22 reduced-scale laboratory platform. Three-level converters are used in a robust power control method to reduce the inherent intermittency of renewable sources and the stochastic nature of isolated loads. These converters are used to improve power quality, lower harmonic distortion, and control dynamic interactions between the sources in real time. The main goal is to minimize the VSDG contribution and estimated fuel consumption while optimizing renewable energy penetration, with fuel consumption reduction assessed through power dispatch analysis rather than direct measurement. Comprehensive simulations and real-time experimental prototyping using the dSPACE (CP1104) controller on a 1/22-scale platform were used to validate the proposed control strategy. Results from both simulations and experiments support the strategy’s viability and efficacy in preserving system stability and maximizing energy dispatch under various load profiles. Full article

Renewable energy curtailment has emerged as a growing challenge on the Korean mainland grid as photovoltaic (PV) and wind power capacity continues to expand toward national carbon neutrality targets. Plus demand response (Plus DR), in which electricity consumers increase consumption during curtailment periods, has been introduced as a demand-side mitigation measure. Buildings represent a potential resource for Plus DR participation. However, existing studies have primarily focused on load-reduction DR, and Plus DR availability by building use type under curtailment conditions has not been systematically quantified. This study estimates Plus DR availability of building loads by use type—department store, hotel, general commercial, public facility, apartment, and school—based on representative building load profiles, PV generation data, and 2025 curtailment occurrence data from the Korean mainland grid. Curtailment events were concentrated in the 10:00–16:00 window with peak frequency at 12:00 (80 events). The combined Plus DR availability across the six use types averaged 290.3 kW during curtailment hours, peaking at 300.9 kW at 14:00. The estimated Plus DR availability operated primarily through the load-increase pathway (additional grid consumption) rather than the surplus absorption pathway (reduced PV export). Surplus generation was observed only in the school at 13:00 (0.77 kW). These results provide a quantitative basis for identifying suitable building types and curtailment-responsive time windows for building-based Plus DR program design on the Korean mainland, and may serve as a reference for mainland DR market development. Full article

This study outlines the design and assessment of a hybrid renewable energy system aimed at powering rural electrification for five villages in the Butha-Buthe district of Lesotho, which has an overall daily energy consumption of 1342 kWh and a peak demand of 112 kW. Utilizing HOMER Pro (version 3.18.4), various configurations were analyzed. The most cost-effective system, comprising PV, wind, hydro, batteries, and a diesel generator, resulted in an LCOE of USD 0.3194, alongside a renewable share of 73%. An entirely renewable setup was also explored, achieving a 100% renewable share but with a higher LCOE of USD 0.6615. Sensitivity analysis regarding diesel pricing and hydro flow rates revealed significant effects on Net Present Cost and fuel consumption. The results highlight feasible options for economically efficient, renewable-centric rural electrification in isolated areas. Full article

The industrial sector accounts for a significant share of global energy consumption and greenhouse gas emissions, making the optimal operation of industrial parks a key pathway for sustainable energy transition. This study proposes a day-ahead coordinated optimal scheduling framework for a multi-sector Industrial Park Energy Hub (IPEH) that integrates electricity, heating, and cooling systems with renewable generation and multi-energy storage. The model captures sectoral diversity across industrial, commercial, residential, and administrative sectors, enabling coordinated inter-sector operation through electricity and heating energy sharing. The scheduling problem minimizes total operating cost, including penalties for greenhouse gas (GHG) emissions and for power curtailment from photovoltaics (PV) and wind turbines (WT), while considering the physical constraints of the heating network and power tie-lines. The optimization problem is solved using the CPLEX solver in MATLAB. Results under three scenarios show that, compared with independent operation, electricity sharing alone reduces operating cost by 3.22% and renewable curtailment by 58.19%. Coordinated electricity and heat exchange further improves system performance, achieving a 6.95% reduction in operating cost, a 58.19% decrease in renewable energy curtailment, and emission reductions of 18.11% for CO₂, 23.80% for SO₂, and 38.42% for NO_x. Full article

This paper presents a complete analysis and simulation of the operation of a zero-emission marine vessel with electric propulsion. A hypothetical passenger ferry operating in the Aegean Sea, Greece, is considered, which is powered by a hydrogen fuel cell, a battery energy storage system (BESS) and photovoltaic (PV) energy. Wind-assisted ship propulsion (WASP) is employed to reduce the energy consumption of the ship. A complete analysis is performed, which includes optimal energy management, dynamic analysis and emerging stability concerns due to the high integration of power electronic converters in the shipboard microgrid. The energy management system (EMS) applies multi-objective optimization based on the corona virus optimization (CVO) algorithm and the teaching–learning-based optimization algorithm (TLBO). The dynamic behavior of the microgrid is tested using real-time digital simulations. Converter-driven stability issues are investigated, which may arise due to interactions among the various converter controllers and passive components of the microgrid. Full article

The smart hybrid microgrid energy management system is based on photovoltaic (PV) arrays, wind turbines, battery energy storage, and diesel generators, supplying clean, stable, and cost-effective energy to rural villages. Predictive control, load-demand/load-following, and SOC optimization enable supply and demand adjustments for stable operation and reduced emissions/diesel consumption. MATLAB 2024a simulations support the concept that this system operates more sustainably, reliably, and efficiently when a compromise is made between conventional and renewable sources. By addressing the reliability issue of renewable energy’s intermittent production, such hybrid systems can provide the consistent power necessary for economic productivity and health/education in rural villages. Full article

External electricity supplementation for islanded microgrids at expressway service areas is often settled under tiered electricity pricing based on cumulative energy consumption, where marginal prices increase discontinuously once tier thresholds are exceeded. This mechanism reshapes battery dispatch behavior and may alter economically optimal storage sizing. This paper proposes a unified planning—operation optimization framework for wind–PV–battery microgrids that jointly determines the storage capacity and hourly scheduling while enforcing power balance, battery state-of-charge dynamics, and tiered settlement costs. By introducing tier-wise energy allocation variables and tier cap constraints, the nonlinear settlement rule is reformulated into an equivalent piecewise-linear structure, leading to a mixed-integer linear programming (MILP) model that can be solved using standard optimization solvers. A season-weighted annualized case study using four typical seasonal days reveals critical cross-tier dispatch behaviors, where charging–discharging schedules shift near tier boundaries and external electricity purchases are actively suppressed from entering higher-priced tiers. The proposed framework quantifies the premium-avoidance value of storage and provides a practical decision support tool for premium risk-aware sizing and operation of islanded expressway service-area microgrids. Full article

To address the coupled challenges of renewable power volatility, high operating cost, and electrolyzer degradation in grid-connected wind–PV hydrogen production systems, this paper proposes a hierarchical day-ahead scheduling strategy under time-of-use (TOU) electricity prices. The upper layer performs price-responsive economic dispatch to coordinate renewable utilization, battery operation, grid transactions, and aggregate hydrogen-production power with the objective of minimizing lifecycle operating cost. The lower layer introduces a health-aware non-uniform rotation mechanism to allocate the aggregate power command among electrolyzer units, thereby reducing fluctuation exposure and balancing lifetime consumption across the array. Practical constraints, including multi-state electrolyzer operation, unit-commitment logic, battery state-of-charge dynamics, hydrogen storage limits, and system power balance, are explicitly considered. A case study of a wind–PV hydrogen production project in Northern China shows that the proposed strategy shifts electricity purchases to valley-price periods and promotes electricity export during peak-price periods. Compared with the benchmark strategy, hydrogen production during low wind–PV generation periods increases from 342,000 to 381,000 Nm³, the share of fluctuating operating time decreases from 62.5% to 12.5%, and the average daily start–stop frequency declines from 8.0 to 4.8. Consequently, the degradation penalty is reduced by about 40%, and lifecycle operating cost decreases by 27.3%. Full article

In the scenario where renewable energy sources (RESs) are connected to the power system (PS) through a flexible high-voltage direct current (HVDC) transmission system, their output becomes highly intermittent and volatile due to meteorological factors like wind direction and speed. This variability poses significant challenges to the real-time power balance and control of the PS. To address the uncertainties in system operation and the challenges of RES consumption, this paper proposes an artificial intelligence (AI) algorithm-driven collaborative optimization strategy for virtual power plants (VPPs) considering RESs transmitted by flexible HVDC. Firstly, a self-attention mechanism and multiple gated structures are integrated into a long short-term memory (LSTM) deep learning model. This enhancement improves the model’s ability to capture multi-timescale characteristics of RESs, increasing forecasting accuracy and robustness. Based on these forecasts, a total cost optimization model for VPP operation is developed, which includes high penalty costs for wind and solar curtailment. By embedding economic constraints that prioritize RESs usage, the model can reduce waste caused by traditional cost-driven scheduling. Additionally, to solve the high-dimensional nonlinear optimization problem in VPP scheduling, an improved population-based incremental learning (PBIL) algorithm is introduced. It incorporates an elite retention strategy and an adaptive mutation operator to boost global search efficiency and convergence speed. Simulations based on an VPP incorporating typical offshore wind and solar RESs transmitted via flexible HVDC demonstrate that the improved LSTM reduces MAPE by 7.14% for wind and 4.27% for PV compared to classical LSTM, and the proposed method achieves the lowest curtailment rates (wind 10.74%, PV 10.23%) and total cost (43,752 RMB), outperforming GA, PSO, and GW by 10–18% in cost reduction. Simulation results show that the proposed strategy enhances RESs consumption while maintaining system economy under flexible HVDC transmission. This work offers theoretical and practical insights for optimizing PS with high RES penetration and supports the low-carbon transition of new-type PS. Full article

High penetration and output volatility of island wind and photovoltaics (PV) pose challenges to energy consumption and supply–demand balance, and cost-effective energy storage configuration. A coupled dispatch model for a wind–PV–storage system is proposed, which treats multiple canal units as virtual ‘loads’ that switch between generation and pumping under constraints of power balance and available water head model. Considering the variable reservoir–irrigation feature, a multi-objective model framework is developed to minimize both economic cost and storage capacity required. An augmented Lagrangian–Nash product enhanced NSGA-II (AL-NP-NSGA-II) algorithm enforces constraints of irrigation shortfall and overflow via an augmented Lagrangian term and allocates fair benefits across canal units through a Nash product reward. Moreover, updates of Lagrange multipliers and reward weights maintain power balance and accelerate convergence. Finally, a case simulation (3.7 MW wind, 7.1 MW PV, and 24 h rural load) is performed, where 440.98 kWh storage eliminates shortfall/overflow and yields 1.5172 × 10⁴ CNY. Monte Carlo uncertainty analysis (±10% perturbations in load, wind, and PV) shows that increasing storage to 680 kWh can stabilize reliability above 98% and raise economic benefit to 1.5195 × 10⁴ CNY. The dispatch framework delivers coordination of irrigation and power balance in island microgrids, providing a systematic configuration solution. Full article

Organic photovoltaics (OPVs) based on non-fullerene acceptors (NFAs) are rapidly advancing as lightweight, flexible, and low-cost solar technologies, with power conversion efficiencies approaching 20%. To ensure that environmental sustainability progresses symmetrically alongside performance improvements, it is essential to quantify the environmental footprint of these emerging technologies, particularly during early development stages when material and process choices remain adaptable. This study presents a cradle-to-gate life cycle assessment (LCA) of PTB7-Th:ZY-4Cl solar cells, aiming to identify asymmetries in environmental impact distribution and guide eco-efficient optimization strategies. Using laboratory-scale fabrication data, global warming potential (GWP), cumulative energy demand (CED), acidification (AP), eutrophication (EP), and fossil fuel depletion (FFD) were evaluated via the TRACI methodology. Results reveal that electricity consumption in thermomechanical operations (ultrasonic cleaning, spin coating, annealing, and stirring) disproportionately dominates most impact categories, while chemical inputs such as PEDOT:PSS, PTB7-Th:ZY-4Cl precursors, and solvents contribute significantly to fossil fuel depletion. Substituting grid electricity with renewable sources (hydro, wind, PV) markedly reduces GWP, and solvent recovery or replacement with greener alternatives offers further gains. Although extrapolation to a 1 m² pilot-scale module reveals impacts higher than established PV technologies, prospective scenarios with realistic efficiencies (10%) and lifetimes (10–20 years) suggest values of ~150–500 g CO₂-eq/kWh—comparable to fullerene OPVs and approaching perovskite and thin-film benchmarks. These findings underscore the value of early-stage LCA in identifying asymmetrical hotspots, informing material and process optimization, and supporting the sustainable scale-up of next-generation OPVs. Full article

The rapid growth of renewable energy integration in modern power systems brings new challenges in terms of stability and quality of electricity supply. Hybrid AC/DC microgrids represent a promising solution to integrate photovoltaic panels (PV), wind turbines, fuel cells, and storage units with flexibility and efficiency. However, maintaining adequate power quality (PQ) under variable conditions of generation, load, and grid connection remains a critical issue. This paper presents the modelling, implementation, and validation of a hybrid AC/DC microgrid equipped with a fuzzy-logic-based energy management system (EMS). The study combines PQ assessment, measurement architecture, and supervisory control for technical compliance and economic efficiency. The microgrid integrates a combination of PV array, wind turbine, proton exchange membrane fuel cell (PEMFC), battery storage system, and heterogeneous AC/DC loads, all modelled in MATLAB/Simulink using a physical-network approach. The fuzzy EMS coordinates distributed energy resources by considering power imbalance, battery state of charge (SOC), and dynamic tariffs. Results demonstrate that the proposed controller maintains PQ indices within IEC/IEEE standards while eliminating short-term continuity events. The proposed EMS prevents harmful deep battery cycles, maintaining SOC within 30–90%, and optimises fuel cell activation, reducing hydrogen consumption by 14%. Economically, daily operating costs decrease by 10–15%, grid imports are reduced by 18%, and renewable self-consumption increases by approximately 16%. These findings confirm that fuzzy logic provides an effective, computationally light, and uncertainty-resilient solution for hybrid AC/DC microgrid EMS, balancing technical reliability with economic optimisation. Future work will extend the framework toward predictive algorithms, reactive power management, and hardware-in-the-loop validation for real-world deployment. Full article