Search Results (248)

The large-scale deployment of photovoltaic (PV) systems increasingly faces land-use conflicts, particularly in regions with high environmental sensitivity resulting from intensive urban development. Consequently, decision-makers require transparent, spatially explicit tools to identify suitable areas for utility-scale PV installations (>100 kWp). This study addresses these challenges through the application of a Geographic Information System (GIS) to locate optimal sites for solar farms along the coastal zone of the Region of Murcia (southeastern Spain). First, the research characterizes the territorial context and systematically reviews the European, national, and regional regulatory frameworks to identify relevant legal and environmental constraints. These constraints are translated into thematic layers within the GIS environment and progressively applied to exclude unsuitable land through spatial editing and overlay analyses. The remaining feasible areas are subsequently evaluated according to their photovoltaic potential using publicly available solar resource data. The results show that nearly one quarter of the coastal territory is legally and environmentally suitable for PV deployment. Furthermore, due to the favourable geographical conditions of this Spanish region, the annual photovoltaic potential along the coastal zone reaches nearly 48,000 GWh, which would not only meet the Region of Murcia’s annual electricity demand (approximately 8000 GWh) but also supply neighbouring areas in southeastern Spain. Full article

Photovoltaic (PV) performance in desert environments is significantly hindered by soiling and partial shading. To bridge the gap in empirical data for extreme Saharan conditions, this study presents a novel techno-economic assessment of uniform horizontal shading (UHS) specifically conducted in Mauritania. Controlled outdoor experiments were performed using a 250 W crystalline silicon PV module and a PVPM 2540C I–V curve tracer, applying progressive shading levels from 2.5% to 20%. The novelty of this work lies in the integration of high-resolution experimental I–V/P–V characterization with a localized techno-economic model for five pre-commercial PV plants. It was observed that PV modules are exceptionally sensitive to shading; specifically, a mere 10% shaded area leads to a catastrophic 90% drop in power and current, while the voltage remains remarkably stable. Thermographic analysis further validates the thermal gradients and bypass diode functionality. By quantifying the financial impacts, this research highlights that cumulative economic losses across the five real-world sites reached 87.95%, exceeding 55,000 MRU. These findings provide a strategic framework for optimizing PV systems in arid terrains and offer a robust tool for enhancing the design and operation of large-scale solar applications in desert environments. Full article

This study develops and applies an integrated modeling framework to assess the solar-to-hydrogen-to-power potential across Romania’s five hydrogen ecosystems defined in the National Hydrogen Strategy. The methodology couples PVGIS-based photovoltaic yield simulations, based on hourly solar irradiation data and including system losses, with MHOGA-based electrolysis simulation, enabling a quantitative-energetic-environmental (Q-E-E) system-level assessment. A 1 MW photovoltaic plant was simulated under three mounting configurations (15° fixed tilt, optimal tilt, and solar tracking) and interfaced with alkaline (AEL) and proton exchange membrane electrolysers (PEMEL). Specific photovoltaic yields reach up to 360 kWh/m²_PV·year under tracking conditions, producing up to 7.5 kg/m²_PV·year (AEL) and 6.8 kg/m²_PV·year (PEMEL), expressed per unit of photovoltaic surface area to enable consistent comparison across the configurations considered. The modeled round-trip efficiency of the full solar–electricity–hydrogen–electricity chain is 38.32% for AEL and 34.57% for PEMEL. Life-cycle-based emission modeling yields 0.92 kg CO₂/kg H₂ (AEL) and 1.03 kg CO₂/kg H₂ (PEMEL), while avoided emissions exceed 250 g CO₂/kWh relative to grid intensity. Land-use modeling indicates area requirements between 9402 and 18,804 m²/MW, depending on the Ground Coverage Ratio. Results demonstrate that system configuration exerts a stronger influence than regional solar variability in determining hydrogen yield, highlighting the need for integrated techno-environmental optimization for large-scale deployment. Full article

The tilt angle of photovoltaic (PV) modules strongly influences long-term energy yield, land-use efficiency, and the resulting cost of power generation, particularly under diverse climatic conditions. This study presents a systematic framework for optimizing the monthly tilt angle of PV modules with the objective of minimizing power cost while maintaining high energy output. The proposed methodology integrates solar geometry, monthly global and diffuse irradiance data, shading-constrained array layout, land-use modeling, and economic evaluation to determine location-specific optimal tilt configurations. Unlike conventional fixed-tilt or energy-only optimization approaches, the proposed framework explicitly incorporates inter-row shading constraints and land-use efficiency into power-cost-based tilt optimization. The framework was applied to multiple geographically distinct locations across Pakistan, representing different climatic regions. The results show that power cost is highly sensitive to tilt angle and exhibits a clear minimum at moderate inclinations. For Lahore and Islamabad, the average annual power cost at a 0° tilt angle was 4.3475 $/kW and 4.4128 $/kW, respectively, decreasing to 3.3596 $/kW and 3.266 $/kW at a 40° tilt angle, before increasing to 7.6390 $/kW and 6.5197 $/kW at 90°. For RYK and Karachi, the cost declined from 3.309 $/kW and 2.8189 $/kW at 0° to 2.7138 $/kW and 2.4707 $/kW at a 30° tilt angle, before rising sharply at steeper inclinations. Overall, the study confirms that monthly or seasonally adjusted tilt angles provide a superior balance between energy generation and power cost compared with fixed-tilt systems, enabling location-specific and cost-effective PV system design for large-scale deployment in Pakistan. Full article

The large-scale integration of wind turbine generators (WTGs) and photovoltaic (PV) generation increases operational uncertainty and can exacerbate stability limitations in weak transmission networks, motivating the use of green hydrogen energy storage systems (HESS). This paper presents a probabilistic planning framework for the joint siting and sizing of HESS to support hybrid WTG–PV integration under stochastic wind, solar irradiance, and load conditions. The proposed framework explicitly couples Monte Carlo-based probabilistic power flow with weak-grid security constraints by enforcing FVSI-based voltage-stability limits and an SSI-based system-strength requirement within the optimization loop, rather than treating these indices as post-analysis checks. The planning problem is formulated using a weighted-sum scalarization to minimize life-cycle carbon footprint and active power losses, subject to security constraints based on the Fast Voltage Stability Index (FVSI) and a system-strength constraint expressed through a System Strength Index (SSI). To solve the resulting constrained, nonlinear optimization problem, a sequential hybrid metaheuristic that couples Whale Optimization (exploration) with Osprey Optimization (exploitation) is developed. The framework is implemented in MATLAB using MATPOWER and evaluated on a modified IEEE 39-bus system. Simulation results report an annual carbon footprint of 22.16 Mt CO₂eq/yr, an improvement of 9.2% and 5.3% relative to PSO and GA/PSO baselines, respectively, while increasing the weakest-bus SSI to 4.68 (bus 7). The resulting HESS design comprises a 296.9 MW electrolyzer, a 262.7 MW fuel cell, and 28,012 kg of hydrogen storage. Full article

Against the backdrop of advancing the “dual carbon” goals (carbon peaking and carbon neutrality), the “fishery–photovoltaic complementary” model—integrating solar power generation with salt pan production—has been widely adopted in Tianjin. However, large-scale photovoltaic (PV) facility construction exerts complex impacts onsalt panns, a wetland ecosystem of unique ecological value, by blocking sunlight, altering local microclimates, and regulating water evaporation. Currently, systematic field studies on the comprehensive effects of PV facilities onsalt pans ecosystems remain scarce, particularly those focusing on impacts on primary producers and key environmental factors. Pond sediments harbor the densest and most diverse aquatic microbial communities. In this study, sediment samples were collected from four typical ponds in Tianjin’salt panan region in April, July, and September 2024. Post sample processing, multiple statistical analyses were conducted, including alpha diversity indexing, species abundance clustering, and beta diversity analysis (non-metric multidimensional scaling, NMDS). The results showed the following: (1) Microbial communities existed in both PV-equipped and non-PV areas, indicating no significant correlation between PV presence and alpha diversity indices. (2) Species and genus compositions aggregated in PV-equipped areas with generally consistent community structures, whereas they displayed high dispersion in non-PV areas. This regulatory effect of PV facilities was relatively stable, with deviations only at a few sampling sites, confirming that PV presence significantly affects community composition patterns at both species and genus levels. (3) Cluster heatmap analysis revealed distinct seasonal variations in clustering relationships between sampling stations and microbial genera. Among dominant genera, only Desulfotignum was unaffected by PV facilities or seasonal changes, while the distribution of other dominant genera was significantly influenced by PV construction. Full article

The rapid integration of inverter-based renewable energy sources (RES), particularly solar photovoltaic (PV) and wind power plants (WPPs), together with the large-scale deployment of battery energy storage systems (BESSs) is fundamentally reshaping modern power systems. While these technologies are essential for decarbonization, their converter-dominated and variable characteristics introduce new challenges for grid stability, operational security, and regulatory compliance. As a result, grid codes are being continuously revised to define advanced technical requirements, including fault ride-through (FRT) capability, reactive power support, frequency response, voltage control, and active power management for RESs and energy storage systems (ESS). This study presents a systematic comparative assessment of international grid codes, examining the technical and operational requirements imposed on inverter-based resources (IBR) and ESSs across multiple jurisdictions. In parallel, the current Turkish Grid Code is evaluated from a future-oriented perspective, and recommendations that can improve the existing regulatory framework are proposed, particularly regarding high-voltage ride-through capability, synthetic inertia provision, fast frequency response (FFR), hybrid power plant (HPP) coordination, and ESS-specific performance criteria. Based on the comparative analysis, the study proposes targeted amendments to the Turkish Grid Code aimed at enhancing system resilience under high renewable penetration levels. Furthermore, field-testing methodologies, model-based validation practices, and emerging digitalized compliance monitoring architectures are investigated to assess their applicability to next-generation power systems. By integrating international best practices with country-specific recommendations, this work contributes to the development of transparent, adaptive, and technically robust grid code compliance frameworks, supporting both academic research and practical grid modernization efforts. Full article

The high expansion rate of industrial-scale photovoltaic (PV) systems in emerging economies requires proper performance prediction models that consider particular climatic variabilities. Although the theoretical potential of solar energy in South Asia is well documented, there still exists a gap in the validation of simulation models to operational data over long periods in subtropical monsoon climates. Unlike prior studies, this work combines multi-year operational data with dynamic TRNSYS simulations to quantify both technical and environmental performance of a 1 MW PV system under subtropical monsoon conditions. This paper provides a detailed performance evaluation of a 1 MW grid-connected PV system located in Punjab, Pakistan. The actual performance of the system is compared with a dynamic simulation model that is created in the Transient System Simulation Tool (TRNSYS) using three years of operational data. Four different scenarios are analyzed: (1) Ideal Theoretical Operation, (2) Actual Field Data, (3) Simulated Operation with Maximum Power Point Tracking (MPPT), and (4) Simulated Operation without MPPT. The results reveal that the real system produced an average of 1342 MWh/year, whereas the MPPT-enabled simulation predicted 1664 MWh/year, indicating a performance difference of 19.3%. Statistical validation revealed a strong correlation ($R^2=0.84$) between the model and reality, yet identified a normalized Root Mean Square Error (nRMSE) of 26.8%. This deviation represents a performance gap which is deconvoluted into agricultural soiling losses and grid curtailment. The research work quantifies the technical effect of MPPT where a 27% operational advantage is realized in comparison to fixed-voltage cases, proving its necessity in climates with high diffuse radiation during monsoon seasons. Economic analysis demonstrates a Levelized Cost of Energy (LCOE) of $0.0378/kWh of the existing system, and a Simple Payback Time (SPBT) of 4.74 years at the current industrial tariffs. Sensitivity analysis also indicates that in case of an increase in grid tariffs to 50 PKR/kWh, Internal Rate of Return (IRR) increases to 18.8%. Environmental analysis confirms a carbon emission reduction of 765 tons/year. These results validate the techno-economic feasibility of large-scale PV in the area and provide an important understanding of the critical yield losses in monsoon seasons, which offers an effective robust benchmark for future industrial energy policy in developing economies. Full article

This paper presents an optimization-based method to support distribution system operators (DSOs) in planning large-scale photovoltaic (PV) integration at the medium-voltage (MV) level. The PV hosting capacity (PV-HC) problem is formulated as a mixed-integer quadratically constrained program (MIQCP) without linearizing approximations to determine PV sizes and locations while enforcing operating limits and planning constraints, including candidate PV locations, per-unit PV capacity limits, active power exchange with the upstream grid, and PV power factor. Our method defines two HC solution classes: (i) sparse solutions, which allocate the PV capacity to a limited subset of candidate nodes, and (ii) non-sparse solutions, which are derived from locational hosting capacity (LHC) computations at all candidate nodes, and are then aggregated into conservative zonal HC values. The approach is implemented in a Hosting Capacity–Distribution Planning Tool (HC-DPT) composed of a Python–AMPL optimization environment and a Python–OpenDSS probabilistic evaluation environment. The worst-case operating conditions are obtained from probabilistic models of demand and solar irradiance, and Monte Carlo simulations quantify the performance under uncertainty over a representative daily window. To support integrated assessment, the index $G_{\exp }$ is introduced to jointly evaluate exported energy and changes in local distribution losses, enabling a system-level interpretation beyond loss variations alone. A strategy was also proposed to derive worst-case scenarios from zonal HC solutions to bound performance metrics across multiple PV integration schemes. Results from a real MV case study show that PV location policies, export constraints, and zonal HC definitions drive differences in losses, exported energy, and solution quality while maintaining computation times compatible with DSO planning workflows. Full article

The increasing penetration of renewable energy introduces significant challenges to grid stability and economic performance due to the intermittent and non-dispatchable nature of solar and wind generation. These fluctuations contribute to grid congestion, frequency control issues, and price volatility, reducing revenue predictability for renewable producers. It is then clear that the challenge of energy transition can be addressed by making the introduction of renewable sources into the electricity grid sustainable. Battery Energy Storage Systems (BESSs) have emerged as a flexibility resource providing time-shifting, frequency and voltage support, congestion management, and energy arbitrage. In response, several Transmission System Operators (TSOs), such as Terna in Italy in cooperation with photovoltaic (PV) and wind power producers, have initiated flexibility projects. However, these projects are limited and should be accompanied by liberalization measures that allow BESSs to be economically sustainable only under market conditions. This study evaluates the techno-economic feasibility of utility-scale BESSs either integrated into large PV/wind farms or stand-alone for providing grid flexibility services and profit increase for the producers. Both market conditions and TSO incentives will be considered. A two-step mixed integer linear (MILP) optimization approach is employed: first, an optimization schedules BESS charge and discharge operations based on historical generation and market data; second, the Net Present Value (NPV) is maximized to determine optimal system sizing and profit. The model is validated through real case studies and sensitivity analyses including BESS degradation, market volatility, and regulatory factors. The developed model is ultimately applied to compare the study cases, and the analysis shows that, under specific conditions, the arbitrage of a stand-alone BESS can be as profitable as the incentives offered by TSOs. Full article

Despite the growing adoption of hybrid energy systems integrating solar photovoltaic (PV), pumped storage hydropower (PSH), and battery energy storage (BES), comprehensive studies on their dynamic stability and interaction mechanisms remain limited, particularly under weak grid conditions. Due to the high impedance of weak grids, ensuring stability across varied operating scenarios is crucial for advancing grid resilience and energy reliability. This paper addresses these research gaps by examining the interaction dynamics between PV, PSH, and BES on the DC side and the utility grid on the AC side. The study identifies operating-region-dependent instability mechanisms arising from negative incremental resistance behavior and weak grid interactions and proposes a virtual-impedance-based active damping control strategy to suppress poorly damped oscillatory modes. The proposed controller effectively reshapes the converter output impedance, shifts unstable eigenmodes into the left-half plane, and improves phase margins without requiring additional hardware components or introducing steady-state power losses. System stability is analytically assessed using root-locus, Bode, and Nyquist criteria within a developed small-signal state-space model, and further validated through large-signal real-time simulations on an OPAL-RT platform. The main contributions of this study are threefold: (i) a comprehensive stability analysis of a utility-scale grid-connected hybrid PV–PSH–BES system under weak grid conditions, (ii) identification of operating-region-dependent instability mechanisms associated with DC–link interactions, and (iii) development and real-time validation of a practical virtual-impedance-based active damping strategy for enhancing system stability and grid integration reliability. Full article

Climate change and increasing greenhouse gas emissions are driving the global transition to clean energy, with solar energy experiencing the fastest growth among renewable sources in 2024. Solar PV for energy generation in Kenya is gaining momentum as the country moves towards achieving 100% clean energy by 2030. As solar PV penetration in the grid grows, it is necessary to evaluate its impact on system costs to inform policy decisions on capacity expansion options in the Least-Cost Power Development Plan (LCPDP). This study investigates the effect of large-scale solar PV expansion on electricity costs using the Open-Source Energy Modelling System (OSeMOSYS), a modular, bottom-up capacity expansion model. Four scenarios were developed to assess different levels of solar PV penetration: business-as-usual (BAU), moderate-solar-PV expansion (MSPV), high-solar-PV expansion (HSPV), and very-high-solar-PV expansion (VHSPV). The results indicate that, while overall solar PV expansion significantly contributes to decarbonising Kenya’s electricity mix by displacing fossil-based generation, it also increases annual investment obligations and, consequently, total system costs. The system-levelised cost of electricity (LCOE) is shown to rise by 0.2%, 5.7%, and 14.0% under MSPV, HSPV, and VHSPV, respectively, compared to BAU. Analysing the various cost components against sustainability indicators reveals that the least-cost scenario is BAU while the most favourable scenario based on sustainability indicators is VHSPV, which performs best across technical, environmental, and institutional dimensions but less favourably on economic and social aspects, thereby highlighting a trade-off between sustainability and cost minimisation, at least in the short term. Full article

The sustained growth of electricity demand and the global transition toward low-carbon energy systems have intensified the need for efficient, flexible, and reliable operation of electrical distribution networks. In this context, the coordinated integration of distributed renewable energy resources and demand-side flexibility has emerged as a key strategy to improve technical performance and economic efficiency. This work proposes an integrated optimization framework for active power supply in a radial, distribution-like network through the optimal siting and sizing of photovoltaic (PV) units and wind turbines (WTs), combined with a real-time pricing (RTP)-based demand-side response (DSR) program. The problem is formulated using the branch-flow (DistFlow) model, which explicitly represents voltage drops, branch power flows, and thermal limits in radial feeders. A multiobjective function is defined to jointly minimize annual operating costs, active power losses, and voltage deviations, subject to network operating constraints and inverter capability limits. Uncertainty associated with solar irradiance, wind speed, ambient temperature, load demand, and electricity prices is captured through probabilistic modeling and scenario-based analysis. To solve the resulting nonlinear and constrained optimization problem, an Improved Whale Optimization Algorithm (I-WaOA) is employed. The proposed algorithm enhances the classical Whale Optimization Algorithm by incorporating diversification and feasibility-oriented mechanisms, including Cauchy mutation, Fitness–Distance Balance (FDB), quasi-oppositional-based learning (QOBL), and quadratic penalty functions for constraint handling. These features promote robust convergence toward admissible solutions under stochastic operating conditions. The methodology is validated on a large-scale radialized network derived from the IEEE 118-bus benchmark, enabling a DistFlow-consistent assessment of technical and economic performance under realistic operating scenarios. The results demonstrate that the coordinated integration of PV, WT, and RTP-driven demand response leads to a reduction in feeder losses, an improvement in voltage profiles, and an enhanced voltage stability margin, as quantified through standard voltage deviation and fast voltage stability indices. Overall, the proposed framework provides a practical and scalable tool for supporting planning and operational decisions in modern power distribution networks with high renewable penetration and demand flexibility. Full article

The Space Solar Power Station/Satellite (SSPS) is a large-scale space-borne facility intended for the direct collection and conversion of solar energy in the extra-stratospheric region. The optimization of its light collection and conversion (LCC) structures, analysis of dynamic characteristics, and design of attitude control systems represent core technical bottlenecks impeding the advancement of SSPS. To address these issues, this study investigates a novel conceptual line-focusing SSPS. Firstly, a multi-objective collaborative optimization model is developed to optimize the structural parameters of the concentrator and photovoltaic (PV) array. Subsequently, based on the optimized parameters, a coupled multi-body dynamic model is formulated, incorporating gravity-gradient torque and other space-borne disturbance factors. Finally, a distributed Proportional–Integral–Derivative (PID) controller is proposed to achieve three-axis attitude stabilization of the SSPS. Simulation results demonstrate that the light collection efficiency achieves 81.9% with a power density of 4792.24 W/m²; concurrently, a balance between the geometric parameters of the LCC system and the aforementioned key performance indicators is attained, and the proposed controller possesses favorable anti-disturbance performance. 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