Search Results (789)

Due to the increasingly severe energy crisis and extreme climate conditions in recent years, the development and use of alternative clean energy sources have become increasingly important. This study evaluates the energy performance of applying residential solid oxide fuel cells (SOFCs) in a typical passive-designed residential village house in Xi’an. Furthermore, the study integrates photovoltaic (PV) systems and storage batteries with a solid oxide fuel cell co-generation system (SOFC-CGS) to enhance its overall energy performance. The results show that when the SOFC-CGS operates independently, it can provide stable electricity. However, due to its limited capacity, it only meets 43% of the total energy demand and cannot fully satisfy the heating requirements. In this energy supply scenario, the SOFC-CGS heating efficiency reaches 25%, the power generation efficiency reaches 42%, and the overall efficiency reaches 67%. After integrating the PV battery system with the SOFC-CGS, the addition of photovoltaic and battery systems boosts the energy self-sufficiency rate by 32 percent, reaching 75%. In other words, this clean energy combination can cover 75% of the household’s traditional energy consumption. In addition, the heating efficiency increases by 2 percentage points to 27%, the power generation efficiency rises by 4 percent to 46%, and the overall system efficiency improves by 6 percent to reach 73%. Furthermore, the utilization rate of the photovoltaic battery system also rises from 25% to 73%: an increase of 48 percent. Therefore, according to the analysis results, integrating PV and storage batteries with the SOFC-CGS proves to be a profitable and efficient solution for application in passive-designed village houses in Xi’an. Full article

This paper presents a high-efficiency wireless power transfer (WPT) architecture employing a resonant inductive coupling to power smart sensor nodes in remote or sealed environments, where conventional power delivery is unfeasible. The system integrates a photovoltaic (PV) energy source with a step-down DC-DC converter based on the LM2596 buck regulator to adjust the voltage from the PV. The proposed conditioned power system supplies the entire electronic circuit consisting of a PWM modulator based on an NE555, which drives an IR2110 gate driver connected to a Class D power amplifier. The amplifier excites a pair of high-Q resonant coils designed for mid-range inductive coupling. On the receiver side, the inductively coupled AC signal is rectified and regulated through an AC-DC conversion stage to charge a secondary energy storage unit. The design eliminates the need for physical electrical connections, ensuring efficient, contactless energy transfer. The proposed system operates at a resonant frequency of 24.46 kHz and achieves up to 80% transmission efficiency at a distance of 113 mm. The receiver provides a regulated DC output between 4.80 V and 4.97 V, sufficient to power low-consumption smart sensors. Full article

As renewable energy penetration increases, the volatility and uncertainty of photovoltaic generation and load demand pose significant challenges to power-system stability. This paper proposes a data-driven probabilistic load-flow method that employs a Gaussian mixture model (GMM) to model uncertainties in photovoltaic generation and load demand. Cumulative quantity analysis is then applied to conduct probabilistic load-flow studies, quantifying the impact of these uncertainties on the power system. Building upon this foundation, a two-layer optimization model is constructed to optimize the siting, capacity, and operational strategies of energy storage systems. Experimental results demonstrate that this method effectively reduces the probability of voltage-limit violations, ensures the reliability of supply–demand balance, and enhances system stability and reliability even under fluctuating PV generation and load-demand conditions. Full article

Power converters are essential for solar energy systems but achieving over 96% efficiency at 1 kW and 300 kHz with compact magnetic and EMC compliance remains challenging for high-power-density PV applications. This study presents the design, modeling, and experimental validation of a 1 kW two-phase interleaved boost converter operating from 12 V input to 48 V/20 A output, featuring a single EE32 Litz-wound coupled-core inductor with coupling coefficient k = −0.475 that reduces per-phase current ripple to just 120 mA (0.6% relative) at full load, a load-selective active zero-current switching (ZCS) circuit activated above 5 A threshold via DCR sensing to minimize switching losses without light-load penalties, and digital peak-current control with 2P2Z compensator implemented on an XMC4200 microcontroller, ensuring robust stability. Experimental results demonstrate peak efficiency of 98.6% at approximately 190 W load, full-load efficiency of approximately 96% with total losses limited to 40 W dominated by conduction rather than switching, thermal rise below 80 °C on key components, voltage regulation with less than 1% deviation down to 2 A minimum load, and full compliance with electromagnetic compatibility standards, including EN 55014-1/2 and EN 61000-4-2 ESD testing. The novel integration of selective ZCS, single-core magnetic, and high-frequency operation outperforms prior interleaved boost converters, which typically achieve 94–97% peak efficiency at lower switching frequencies of 20–100 kHz using multiple inductors or complex always-active resonant networks, making this solution particularly suitable for compact photovoltaic micro-converters, electric vehicles, and industrial power supplies requiring high efficiency, reliability, and regulatory compliance. Full article

This paper compares two common dispatch policies—Load-Following (LF) and Cycle-Charging (CC)—for a photovoltaic Battery Energy Storage System (PV–BESS) microgrid (MG) with a 12 kW diesel generator, using a full-year of real 15 min PV and load data from an industrial use case in Germany. A forward time-step simulation enforces the battery State-of-Energy (SoE) window (total basis [20, 100] %, DoD = 80%) and computes curtailment, generator use, and unmet energy. Feasible designs satisfy a Loss of Power Supply Probability (LPSP) ≤ 0.03. Economic evaluation follows an Equivalent Annual Cost (EUAC) model with PV and BESS Capital Expenditure/Operation and Maintenance (CAPEX/O&M) (cycle life dependent on DoD and 15-year calendar life), generator costs, and fuel via SFC and diesel price. A value of lost load (VOLL) can be applied to unserved energy, with an optional curtailment penalty. Across the design space, a clear cost valley appears toward moderate storage and modest PV, with the baseline optimum at ≈56 kWp PV and 200 kWh BESS (DoD = 80%). Both policies meet the reliability target (in our runs LPSP ≈ 0), and their SoE trajectories are nearly identical; CC only lifts the SoE slightly after generator-ON events by using headroom to charge, while LF supplies just the residual deficit. Sensitivity analyses show that the optimum is most affected by diesel price and discount rate, with smaller shifts for ±10% changes in SFC. The study provides a transparent, reproducible workflow—grounded in real data—for controller selection and capacity planning. Full article

Large-scale renewable power supply system design for remote hydrogen production is a challenging task due to the 100% power electronics sending-end subsystem. The proper grid-forming strategy for a sending-end system to achieve large-scale remote hydrogen production still remains a research gap. This study first designs two grid-forming strategies for the concerned renewable power supply system, with one being based on virtual synchronous generator (VSG) and another one being based on V/f control. Then, the impedance analysis is carried out for ensuring the small-signal stable operation of the sending-end system including wind power plant and PV plant. Numerical simulation results implemented on PSCAD verify that the VSG-based grid-forming strategy configured on the sending-end modular multilevel converter (MMC) station of the MMC-based high-voltage direct-current (HVDC) link has a larger transient stability margin. Hence, the MMC-HVDC-based grid-forming strategy is a better choice for the power supply of large-scale remote hydrogen production. The enhanced stability margin ensures more robust operation under disturbances, which is critical for maintaining continuous power supply to large-scale electrolyzers. Full article

Photovoltaic (PV) generation, a vital component of renewable energy, is key to supporting energy supply and reducing reliance on traditional energy sources. Given the substantial energy consumption of oilfield well groups, increasing the proportion of PV energy is imperative. Furthermore, as oilfields enter mid-to-late production stages, wells experience reduced oil production with increased energy consumption, necessitating intermittent pumping schedules. This paper addresses the optimized scheduling of pumping unit well groups within a photovoltaic-grid microgrid. The article aims to minimize the difference between the well group system’s total energy consumption and the PV power generation. A nonlinear mixed-integer programming (NMIP) model is constructed, incorporating a PV power forecasting model, a well group energy consumption model, and relevant constraints. An improved Particle Swarm Optimization (PSO) algorithm, integrating a hybrid coding scheme and multiple improvement strategies, is proposed to efficiently solve the NMIP model. The resulting optimal intermittent pumping schedule maximizes on-site PV power consumption, effectively mitigating PV energy wastage and potential grid stability issues associated with direct grid integration. The effectiveness of the proposed optimization algorithm is validated through numerical simulation case studies. Full article

As the penetration of distributed energy resources (DERs) continues to increase, there is conjecture concerning the power quality implications of the inverters used to interface these DERs with low-voltage (LV) electricity supply networks. As a power electronics converter, inverters are a known source of harmonic emissions. Using a combination of large-scale field measurements, laboratory evaluations of inverter performance, and power system modelling, this study applies an empirical data-driven approach to investigate the impact of small-scale solar PV inverters on LV harmonic distortion magnitudes. This multi-facetted approach, involving field data analysis, laboratory assessments of inverter performance, and power system simulation to evaluate the impact of small-scale DER on harmonic distortion in LV networks, is novel in comparison to other studies, which only utilise one or two of the analysis methods of simulation, laboratory evaluation, or analysis of field measurements but not all three. The analysis of field measurement data collected over the past decade does not indicate any significant changes in harmonic distortion magnitudes that can be attributed to the increasing penetration of DERs. Power system modelling, which incorporates data obtained from laboratory inverter performance evaluations, indicates that, even at very high levels of penetration, the harmonic current emissions from solar PV inverters are only sufficient to add modest levels of harmonic distortion to LV networks, a 0.25% increase in THD for 40% penetration and a 0.62% increase in THD for 100% penetration, providing an explanation for the findings of the field data analysis. Full article

The global low-carbon transition is driving the use of renewable energy for ecological monitoring. Traditional power supply for forest monitoring sensor equipment is constrained by high wired costs, frequent battery replacement, and the limitations of low light levels and special spectra under forest canopies on photovoltaic (PV) compatibility. Existing research lacks exploration of the correlation between under-forest spectra and PV performance. This study measured the summer understory light spectra of five tree species in Beijing, evaluated the performance of three types of PV cells—monocrystalline silicon, polycrystalline silicon, and amorphous silicon—and designed a low-light energy harvesting circuit. Results indicate that spectral differences under tree canopies are concentrated from 380–680 nm, exhibiting a distinctive forest-specific spectral feature of “high-band enrichment” above 680 nm. Under low-light conditions, polycrystalline silicon photovoltaics demonstrates optimal performance when adapted to this high-band spectrum. The designed circuit can activate at 5 W/m² irradiance and stably output 4.16 V voltage. This study fills a spectral gap in northern summer tree canopies, providing a comprehensive solution of “material adaptation + circuit customization” for the practical deployment of shaded forest PV systems. Full article

High penetration of distributed photovoltaic (PV) generation introduces operational challenges for thermal power plants, including increased cycling, higher losses, and reduced system flexibility. This study proposes an integrated optimization framework that combines Mixed Integer Nonlinear Programming (MINLP)-based Unit Commitment (UC) with a Particle Swarm Optimization (PSO)-assisted Optimal Power Flow (OPF) solved using the Newton–Raphson method. Applied to the IEEE 30-bus system for a 24-h horizon, the UC stage schedules 3717.8 MW of thermal generation at a cost of $8771.14. Load flow validation indicates a required supply of 3793.7 MW due to network losses, increasing the cost to $9031.64 and causing several constraint violations. The PSO-assisted OPF resolves all violations and produces an adjusted total generation of 3778.5 MW, reducing losses and lowering the overall operating cost to $8912.47 through optimal redispatch and voltage regulation. To further evaluate system robustness, multiple load scenarios—including reduced, nominal, and increased demand—are analyzed. Across all scenarios, the OPF stage is able to eliminate operational violations, decrease real power losses, and maintain voltage profiles within acceptable limits, demonstrating consistent performance under varying system stress levels. Overall, the integrated UC–OPF framework enhances economic efficiency, operational reliability, and resilience under renewable variability and shifting load conditions. Full article

The rapid adoption of electric vehicles (EVs) has increased the need for sustainable charging infrastructure supported by renewable energy. This study presents a comprehensive techno-economic and environmental analysis of private EV charging stations in Kuwait powered by grid-connected solar and wind systems using the HOMER Pro 3.18.4 optimization software. Four configurations—grid-only, grid–solar, grid–wind, and grid–solar–wind—were modelled and evaluated in terms of energy output, cost performance, and carbon emission reduction under Kuwait’s climatic conditions. HOMER simulated 484 systems, of which 244 were technically feasible. The optimal configuration, combining grid, 5 kW photovoltaic (PV) (BEIJIAYI 600 W panels), and a 5.1 kW AWS wind turbine, achieved a renewable fraction of 78%, reducing grid dependency by 78.1% and annual CO₂ emissions by approximately 7027 kg. Although the hybrid system required a higher initial investment (USD 7662) than the grid-only setup (USD 1765), it achieved the lowest Levelized Cost of Energy (LCOE = USD 0.017/kWh) and long-term cost competitiveness through reduced operating expenses. Sensitivity analysis confirmed the hybrid system’s robustness against ±15% variations in wind speed and ±10% changes in solar irradiance. The results highlight that hybrid solar–wind systems can effectively mitigate intermittency through diurnal complementarity, where daytime solar generation and nighttime wind activity ensure continuous supply. The findings demonstrate that integrating renewables into Kuwait’s EV charging infrastructure enhances economic viability, energy security, and environmental sustainability. The study provides practical insights to guide renewable policy development, pilot deployment, and smart grid integration under Kuwait Vision 2030’s clean-energy framework. Full article

To achieve optimal performance of renewable hydrogen production systems (RHPS), this study proposes a novel optimization framework for synergistically integrating wind–solar resources with diversified electrolyzers. A comprehensive techno-economic model is developed, incorporating both alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL), and enabling the determination of the optimal wind–solar configuration ratio, electrolyzer types and capacities, and system-level economic performance. The results reveal that the nature of the renewable energy source predominantly influences the selection of electrolyzers. Specifically, pure photovoltaic (PV) systems tend to favor PEMEL, with an optimal PEMEL:AEL capacity ratio of 2:1, whereas pure wind turbine (WT) systems and PV–WT hybrid systems are more suited to AEL, with corresponding AEL:PEMEL ratios of 8:3 and 7:3, respectively. The combined operation of wind–solar complementarity and diversified electrolyzers reduces the levelized cost of hydrogen (LCOH) to USD 4.52/kg, representing a 41.1% reduction compared to standalone PV systems, with a renewable energy utilization rate of 92.26%. Case studies confirm that collaborative AEL–PEMEL operation enhances system stability and efficiency, with PEMEL mitigating power fluctuations and AEL supplying baseload hydrogen production. This synergy improves hydrogen production efficiency, extends equipment lifespan, and provides a viable and theoretically sound solution for RHPS optimization. Full article

The large-scale integration of renewable energy has reduced power system flexibility and exacerbated supply–demand imbalances. In industrial parks, the combined variability of high energy-consuming industrial loads and photovoltaic (PV) generation further complicates the energy management challenge. Aiming to enhance the operational flexibility of industrial parks and mitigate supply–demand imbalances, this paper proposes a multi-time-scale stochastic energy management strategy that accounts for the uncertainty associated with PV generation. First, a conditional generative adversarial network (CGAN) is employed to generate the representative PV generation scenarios, thereby enabling the modeling of PV generation uncertainty within the optimal dispatch model. Considering the coupling mechanisms and control characteristics of various regulation resources within the industrial park, a multi-time-scale dispatch model is developed. In the day-ahead dispatch phase, the operational costs are minimized by optimizing the production plans of industrial loads. In contrast, in the intraday phase, the more flexible measures, such as adjusting the tap positions of arc furnaces and controlling the charge/discharge of energy storage systems, are employed to smooth power fluctuations within the park. A case study validated the effectiveness of the proposed approach, demonstrating a 7.56% reduction in power fluctuations and a 4.34% decrease in daily operating costs. These results highlight the significance of leveraging industrial loads in park-level systems to enhance cost efficiency and renewable energy integration. Full article

This paper describes the modeling, simulation, and experimental validation of a Hybrid supercapacitor–battery Energy Storage System (HESS) for photovoltaic (PV) modules under partial shading. The system is intended to provide an uninterruptible power supply for a DC primary load. The Hybrid Power System (HPS) architecture includes a DC/DC boost converter with a Maximum Power Point Tracking (MPPT) algorithm that optimizes photovoltaic (PV) energy extraction. Furthermore, two bidirectional DC–DC converters are dedicated to the battery and supercapacitor subsystems to allow the bidirectional power flow within the HPS. The proposed HESS is evaluated through MATLAB/Simulink simulations and experimentally validated on a prototype using real-time hardware based on the dSPACE DS1104. To optimize power flow within the HPS, two energy management strategies are implemented: the Thermostat-Based Method (TBM) and the Filter-Based Method (FBM). The results indicate that the thermostat-based strategy provides better battery protection under shading conditions. Indeed, with this approach, the battery can remain in standby for 300 s under total permanent shading (100%), and for up to 30 min under dynamic partial shading, thereby reducing battery stress and extending its lifetime. Full article

Substations’ auxiliary systems support the station’s operational loads and are crucial for grid security, often requiring backup power to ensure uninterrupted operation. A new alternative for this backup power supply is a microgrid composed of photovoltaic (PV) generation and storage. This paper proposes an electric–hydrogen microgrid as backup power supply for substation auxiliary systems. This microgrid ensures power supply during emergencies, provides clean and stable energy for daily operations, and enhances environmental friendliness and profitability. Firstly, using a 220 kV substation as an example, the construction principles of the proposed backup power microgrid are introduced. Secondly, operation strategies under different scenarios are proposed, considering time-sharing tariffs and different weather conditions. Following this, the capacity configuration optimization model of the electric–hydrogen microgrid is proposed, incorporating critical thresholds for energy reserves to ensure system robustness under fault conditions. Finally, the Particle Swarm Optimization (PSO) algorithm is used to solve the problem, and a sensitivity analysis is performed on hydrogen market pricing to evaluate its impact on the system’s economic feasibility. The results indicate that the proposed electric–hydrogen microgrid is more economical and provides better fault power supply time than battery-only power supply. With the development of hydrogen energy storage technology, the economy of the proposed microgrid is expected to improve further in the future. Full article