Solar Photovoltaic Plant Research Articles

Renewable Solar Energy Facilities in South America—The Road to a Low-Carbon Sustainable Energy Matrix: A Systematic Review

South America is a place on the planet that stands out with enormous potential linked to renewable energies. Countries in this region have developed private investment projects to carry out an energy transition from fossil energies to clean energies and contribute to climate change mitigation. The sun resource is one of the more abundant sources of renewable energies that stands out in South America, especially in the Atacama Desert. In this context, South American countries are developing sustainable actions/strategies linked to implementing solar photovoltaic (PV) and concentrated solar power (CSP) facilities and achieving carbon neutrality for the year 2050. As a result, this systematic review presents the progress, new trends, and the road to a sustainable paradigm with disruptive innovations like artificial intelligence, robots, and unmanned aerial vehicles (UAVs) for solar energy facilities in the region. According to the findings, solar energy infrastructure was applied in South America during the global climate change crisis era. Different levels of implementation in solar photovoltaic (PV) facilities have been reached in each country, with the region being a worldwide research and development (R&D) hotspot. Also, high potential exists for concentrated solar power (CSP) facilities considering the technology evolution, and for the implementation of the hybridization of solar photovoltaic (PV) facilities with onshore wind farm infrastructures, decreasing the capital/operation costs of the projects. Finally, synergy between solar energy infrastructures with emerging technologies linked with low-carbon economies like battery energy storage systems (BESSs) and the use of floating solar PV plants looks like a promising sustainable solution.

Comparative LCA of thermal power plant with CCS and solar PV system: sustainability assessment in Indian context.

The study's objective is to evaluate and compare the sustainability of power production techniques for India's transition to clean power generation. It specifically focuses on coal-based power generation with emission control technologies, flue gas desulfurization (FGD) with carbon capture and storage (CCS), and compares it with solar photovoltaic (PV) systems. The study conducted a life cycle assessment (LCA) to determine the environmental impact of electricity generation in each scenario. Inventory data has been collected for each case through plant visits, emission modelling, and literature searches. The study evaluated midpoint and endpoint impact indicators utilizing the ReCiPe (H) assessment methodology. The economic viability of all the cases was determined by calculating the levelized cost of electricity (LCOE). The results showed that retrofitting an existing power plant with flue gas desulfurization (FGD) and carbon capture and storage (CCS) reduced efficiency by 30%, required 1.2 times more auxiliary power, and increased heat rates. The LCA results showed that the global warming potential (GwP) for FGD and CCS together was 0.614 kg CO2 eq. per kWh of power generation. On the other hand, the GwP for the solar PV system was much lower, at 0.043 kg CO2 eq. per kWh. There were trade-offs in both cases, but solar PV plants are more environmentally friendly than thermal power plants equipped with CCS systems in almost all categories. Furthermore, the LCOE results showed Rs 3.87 per kWh for an on-grid solar PV plant and Rs 5.33 for thermal power, with CCS and FGD showing solar as an economically more feasible option. Retrofitting thermal power facilities with emission control technology is necessary to achieve net zero emissions, but transition torenewable energy sources isinevitable.

Augmenting a Concentrated Solar Power (CSP) Plant With a Solar PV Plant

The search for enhanced dispatchability at decreased prices has led to a surge in research on hybrid renewable energy systems. This paper explores the integration of Photovoltaic (PV) technology with Concentrating Solar Power (CSP) plants to enhance energy generation and economic feasibility, focusing on optimising the size of PV augmentation for existing CSP facilities. The study considers CSP plants with both Time-of-Day (ToD) and single tariffs, employing modelling techniques to assess the synergies between these two technologies. The cost of PV technology has significantly reduced, making it a cost-effective choice for electricity generation compared to CSP. CSP-PV augmentation promises to reduce online and offline auxiliary consumption, resulting in enhanced energy generation and a subsequent reduction in energy production costs. This study aims to explore the advantages of combining solar PV with a CSP system and determine the ideal PV size to maximise return, building upon previous studies to assess the technological and economic potential of integrating solar PV with CSP, focusing on South Africa. It utilises a rigorous analysis, combining the System Advisory Model and PVSyst modelling tool within an MS Excel framework. This economic assessment and sizing exercise aims to maximise profits while adhering to the limitations imposed by the power purchase agreement of a 100 MW CSP facility. The optimal size is 15 MWp for the ToD tariff and 16 MWp for the flat tariff. This highlights the potential for CSP-PV augmentation to improve energy dispatchability and financial viability, making it a compelling solution for existing CSP plants.

Fatigue Behavior of H-Section Piles under Lateral Loads in Cohesive Soil

Most structures supporting solar panels are found on thin-walled metal piles partially driven into the ground, optimizing costs and construction time. These pile foundations are subjected to repetitive lateral loads from various external forces, such as wind, which can compromise the integrity of the pile-soil system. Given that the expected operational lifespan of photovoltaic solar plants is generally 20–30 years, predicting their service life under fatigue loads is crucial. This research analyzes the response of H-section piles to lateral fatigue loads in cohesive rigid soils through four field tests, subjected to load cycles of 55%, 72%, and 77% of the static failure load, corresponding to maximum loads of 25 kN, 32 kN, and 35 kN, respectively. Additionally, the effect of load cycles on the degradation of pile-soil adhesion is studied through two pull-out tests following cyclic tests. This study reveals that soil fatigue does not occur under repetitive loads and that soil stiffness remains constant once the cycles causing soil compaction have been overcome. Nevertheless, the accumulated plastic deflection of the soil increases steadily once soil compaction occurs due to cyclic loading. The implications of these results on the fatigue life of photovoltaic solar panel foundations are discussed.

Annual relative performance degradation in photovoltaic solar plants

This study aims to assess annual relative performance degradation σ to be used in the computations of the Levelised Cost of Energy (LCOE) of new plants based on the standard year for weather and solar resource. The assessment is based on the experimental data of power generation, weather, and resource for different years, and simulations of power generation by using the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) software. The raw data of power generation for 53 different plants spanning about one decade show a σ assessed at less than 0.29%. This makes it reasonable to assume in SAM σ=0% to σ=0.29%. This is less than the default σ=0.5% currently used in SAM based on limited outdated data. The updated performance degradation factor diminished to σ=0-0.29% reduces the computed LCOE for typical new projects in the United States from 2.86 to 2.74-2.80 ¢/kWh. Correction of the σ trends for interannual variability of weather and resource is unnecessary, providing enough years of operation are covered, given the inaccuracies in the model and the supporting data, the mitigation by management of the performance changes, and the complex phenomena correlated to the change of weather and irradiance affecting the power output in different directions. The reduced σ is the result of a significant product improvement over the last decades, especially for large power plants, compared to the plant which provided data for the prior correlation of performance degradation, and much better management and maintenance of the plants.

Thermographic inspections of solar photovoltaic plants in India using Unmanned Aerial Vehicles: Analysing the gap between theory and practice

Aerial inspection of solar PV plants using Unmanned Aerial Vehicles (UAVs) is gaining traction due to benefits such as no downtime and cost-effectiveness. This technology is proven to be the low-cost alternative to conventional approaches involving visual inspection and I-V curve tracing to identify physical damages and underperforming strings, respectively. Though the use of UAVs for thermographic solar PV inspection is a popular alternative in developed countries, its use in developing economies experience various challenges. Studies emphasizing these challenges especially in the context of rapid evolution of drones are limited. To overcome this limitation, literature scoping, a one-on-one survey, focus group discussion, and a flight campaign using a UAV with a thermal payload is conducted in India to identify the limitations. These are further categorized into Technical, Behavioural, Implementation, Pre-deployment, Deployment, and Post-deployment categories. The relevance and significance of each challenge are analysed using a hybrid multi-criteria framework developed in this study. Findings of this study highlight the importance of drone regulations, technology readiness, and workshops for drone pilots, industry professionals, and solar developers in India. This study aid developing economies in devising strategies that can promote the use of UAVs for solar PV plant commissioning activities.

Design and Performance Analysis of a Hybrid Solar Photovoltaic System With Battery Energy Storage in a Government School of Indian Village

ABSTRACTIn India, energy security and electrification of rural area remains significant challenges. In addressing energy changes, solar photovoltaic (SPV) systems will play a major role, particularly in remote and rural areas. This research presents the design and performance assessment of a hybrid SPV plant integrated with battery energy storage system (BESS) at a government school within an Indian village. This hybrid SPV system is designed to utilize grid electricity when available, switch to solar power during the day when it is available, and use stored battery power at night time. The designed SPV system is of 1785 Wp, capacity coupled with a 560 Ah battery pack. The performance metrics, energy production, and storage efficiency, are analyzed using simulation data from PVsyst software. The results shows that system produces an annual energy of 2149.28 kWh/year and shows a performance ratio (PR) of 72.75% and a solar fraction (SF) of 98.31%. This proposed hybrid SPV system ensures continuous power supply, reduces dependency on the grid, and significantly lowers CO₂ emissions.

Operating Limits and Control Variables in Photovoltaic Solar Plants with a Net Effective Capacity of 5 MW Connected to the SIN in Colombia

Operating Limits and Control Variables in Photovoltaic Solar Plants with a Net Effective Capacity of 5 MW Connected to the SIN in Colombia

Positive sequence component based directional relaying for lines integrated with solar photovoltaic plant

Different fault current characteristics of converter interfaced solar photovoltaic plants as compared to the synchronous generator based sources impose challenges to the commonly used directional relaying methods. In this work, the issues with phasor based directional relay algorithms are analysed for the solar plant connected lines. A directional relaying method is proposed for such connectivity using the phase angle difference between positive sequence voltage and the line current measured at the local bus relay. Using PSCAD/EMTDC simulations the proposed method is tested for solar plant connected 39 bus system and validated using field data. The accuracy of the proposed method is also evaluated on a real-time simulation platform. Comparative analysis with the conventional directional relaying methods reveals the superiority of the proposed method.

Design and Simulation of Smart Grid Based on Solar Photovoltaic and Wind Turbine Plants

Design and Simulation of Smart Grid Based on Solar Photovoltaic and Wind Turbine Plants

Evaluation of renewable energy technologies in Colombia: comparative evaluation using TOPSIS and TOPSIS fuzzy metaheuristic models

The study investigates the weighting and hierarchization of renewable energy sources in specific geographical regions of Colombia using the TOPSIS and Diffuse TOPSIS metaheuristic models. 5 regions were analyzed, two of them with different scenarios: Caribbean 1 and 2, Pacific 1 and 2, Andean, Amazonian and Orinoquia. The results reveal significant differences in the evaluation of technologies between the two models. In the Caribbean 1, Diffuse TOPSIS gave a higher score to Solar Photovoltaics, while TOPSIS favored Hydropower. In the Caribbean 2, Solar Photovoltaic obtained similar scores in both models, but Wind was rated better by TOPSIS. In the Pacific Region 1, Biomass and large-scale Hydropower led according to both models. In the Pacific 2, Solar Photovoltaic was better evaluated by TOPSIS, while Wind was preferred by Diffuse TOPSIS. In the Andean Region, large-scale hydroelectric and Solar photovoltaic plants obtained high scores in both models. In the Amazon, Biomass led in both models, although with differences in scores. In Orinoquia, Solar Photovoltaic was rated higher by both models. The relevance of this research lies in its ability to address not only Colombia's immediate energy demands, but also in its ability to establish a solid and replicable methodological framework. The application of metaheuristic methods such as TOPSIS and TOPSIS with fuzzy logic is presented as a promising strategy to overcome the limitations of conventional approaches, considering the complexity and uncertainty inherent in the evaluation of renewable energy sources. By achieving a more precise weighting and hierarchization, this study will significantly contribute to strategic decision-making in the implementation of sustainable energy solutions in Colombia, serving as a valuable model for other countries with similar challenges.

Review on a real time Green Enviro Solar Systems for On-grid and Off-grid Applications with AI and IoT Technologies

Abstract: Solar photovoltaic (PV) plants must be constantly protected and supervised to keep them safe and reliable during their working lifetime. Incorporating smart technological equipment including artificial intelligence (AI) and internet of things (IoT) for remote sensing, fault detection and diagnosing PV plants can help these plants achieve peak efficiency. While renewable energy appears to be thriving globally, its intermittent nature creates a need to develop solutions for ensuring grid stability.The output of solar panels is influenced by a variety of environmental factors such as the amount of solar radiation, proportion of shadow, weather conditions and so on. Constantly monitoring these variables, particularly for off-grid and remote solar energy plants is a tedious task.

Real-time harmonics optimization of seven level converter for megawatt scale solar PV-utility integration

This paper presents a new single photovoltaic (PV) array fed cascaded H bridge (CHB) submodule based three-phase 10 MW solar photovoltaic (SPV) plant for medium voltage utility applications. Each submodule comprises of a single PV array, cascaded H bridge cells and line frequency transformers. A 10 MW seven level converter based solar PV plant is realised with four submodules feeding solar PV array power to 33 kV grid. In megawatt scale multilevel converters based configuration, semiconductor switches experience reduction in voltage stress and requirement of high switching frequency for gating for switches is eliminated. Moreover, an efficient single stage MPPT based decoupled controller is implemented with genetic algorithm inspired fundamental frequency switching. GA based optimization technique is used to calculate optimal switching angles in offline mode. Obtained switching angles are incorporated to achieve closed loop optimized decoupled control of SPV system. Lower order harmonics are eliminated and power is fed to grid at enhanced power quality. This large scale PV system is modelled in MATLAB-Simulink and simulated results are validated in real time.

Energy, economic and environmental evaluation of the energy storage capabilities of artificial lakes based on pumped-hydro storage systems with a case study of Daghgoli artificial recreational lake

In the present study, Daghgoli artificial recreational lake has been investigated as an energy storage system. This lake with a capacity of 54,000 (m3) is located in the largest metropolis of northwestern Iran, above the Eynali Mountains, in the vicinity of the city. The elevation of this lake is about 450 (m) from the downstream lake with a capacity of 60,000 (m3). The energy storage capacity of the lake has been evaluated based on the pumped-hydro method. Then, the capacity of this large “battery” to store a part of the excess energy generated by the Tabriz thermal power plant has been evaluated. In addition to the technical evaluation, a full economic analysis as well as environmental investigation of application of the lake as an energy storage system has been conducted. The capacity that can be develop the existing small wind farm in the vicinity of the lake so that its generated energy can be fully stored by the energy storage system based on Daghgoli Lake has also been determined. Finally, the capacity of the photovoltaic solar power plant that can be established in the flat plain adjacent to the lake to store its generated electricity by the lake to be used at night or peak hours has been also evaluated. The results showed that using the presented energy storage plan, 74.7(MWh) of excess electrical energy generated by the thermal power plant can be stored daily. By releasing this energy during peak hours, 13.24 (MW) of electricity can be generated with an energy conversion efficiency about 71 %. At the same time, the emission of 8508 tons of carbon dioxide can be prevented during a year. The investment payback period of the project is estimated to be 4.7 years. By using the designed energy storage system, a wind farm consisting of 16 turbines with a capacity of 660 (kW) or a photovoltaic solar plant with a capacity of 9.34 (MW) can be created.

Assessment of suitability for photovoltaic power generation in periurban seminatural grasslands: toward the coexistence of seminatural grasslands and photovoltaic power generation

Renewable energy has grown substantially in recent years due to its efficacy in mitigating climate change. The rapid proliferation of solar photovoltaic (PV) systems and subsequent alterations in land use have led to concerns about the impact on local ecosystems. Particularly in Japan, seminatural grasslands, which are valuable habitats, are being developed as solar PVs. Here, we focused on stilt-mounted agrivoltaic systems, capable of both photovoltaic power generation and plant growth beneath solar panels. By repurposing this technology, the coexistence of vegetation and solar PV systems can be possibly ensured. To assess the feasibility of this proposed approach, we initially examined the suitability of installing solar PV in seminatural grasslands. The suitability of seminatural grasslands, solar PVs, and random points for solar PV was evaluated in terms of electricity generation and construction costs. The environmental conditions of seminatural grasslands were found to be advantageous for electricity generation. On the other hand, in terms of construction costs, seminatural grasslands were comparable to randomly selected sites. These findings indicate that the suitability of existing seminatural grasslands for solar PV plant installations is not considerably lower than that of other land types. The idea of reconciling solar power generation with ecosystem conservation holds promise and warrants further investigation toward its realization.

Life Cycle Assessment of Large-Scale Solar Photovoltaic Plant based in Malaysia

Abstract A cradle-to-grave life cycle assessment (LCA) has been performed on a Large Scale Solar Photovoltaic (LSSPV) plant based in Peninsular Malaysia to study the detailed environmental impact of its life cycle. The LSSPV, with a capacity of 78 MWdc, is currently one of Malaysia’s largest solar power plants. The different life cycle phases of the LSSPV, starting from resource manufacturing and transportation, through plant construction and electricity generation, and to decommissioning of the plant, were assessed using the SimaPro software with the Ecoinvent v3.8 database. Results show that the overall emission rate for the LSSPV is 0.0309 kgCO2eq/kWh. It is estimated that the construction phase of the power plant, which includes activities such as infrastructure works and production of PV modules and Balance of System, yields the largest amount of kgCO2eq/kWh emission at 85.7% and imposes the highest environmental impact as compared to the other phases. The second biggest contributor is attributed to the transportation phase, contributing to 14.0% of the total kgCO2eq/kWh emission, of which most of the emission is emitted during the sea freight transportation of PV components from China port to Malaysia port (12.4%). A sensitivity analysis was performed to compare the environmental impact between open ground installation and the slanted roof installation mounting system of LSSPV. The findings from LCA proposed that open-ground installation has a greater negative impact on the environment because it involves additional land clearing and infrastructure transformation. The findings from this study serve as a benchmark for the LSSPV system in Malaysia and present technical perspectives for the future development of PV projects considering environmental impacts across the project lifetime.

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in photovoltaic (PV) solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. In addition, an error compensation mechanism that uses an error node to capture the temporal fluctuation caused by system degradation or failures is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The results show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92 %–95 % from 1 h to one week ahead forecasting.

Mathematical model of a battery energy storage for a standalone solar photovoltaic plant

Relevance. One of the priority areas for modern energy development is the active use of renewable energy technologies, the leading position among which in terms of the volume of commissioned generating capacity and areas of practical application is occupied by photovoltaics. In recent years, solar photovoltaic plants are increasingly being used as part of autonomous power supply systems, which is largely facilitated by a significant reduction in the cost of their components due to improved technology. Autonomous power supply systems can vary significantly in power, operating conditions, requirements for uninterrupted power supply and many other factors. This determines the high importance of the task of choosing the composition of the main electrical equipment that ensures optimal technical and economic indicators of the designed energy system. To make a reasonable choice of the equipment of an autonomous photovoltaic power plant, simulation models of all its main components are required that adequately reflect their performance characteristics under real operating conditions. An important component of autonomous photovoltaic plants is the energy storage device, which includes a battery and a solar controller that manages the energy balance of the power plant. The settings of the solar controller largely determine the operating modes of the photovoltaic power plant, on which the service life of the batteries primarily depends. Taking into account the fact that the costs of energy storage constitute a significant share of the costs of the total financial investments in the designed power plant, the problem of reliably assessing the service life of batteries is very relevant. Aim. Development of a mathematical model of energy storage system for the design and optimization of the equipment of autonomous photovoltaic plants. Methods. Mathematical and numerical modeling using the MatLab/Simulink software package. Results. A mathematical model of a battery has been developed, based on the modified Shepherd model and the kinetic model of a rechargeable battery. The model is universal and can be used to simulate the static and dynamic characteristics of different types of batteries. To identify model parameters, only the technical specification data provided by the manufacturer is sufficient. The complex model includes a battery life model, which allows you to dynamically adjust the available maximum battery capacity during operation.

Thermal influence in the design of DC to AC converters due to climatic change for photovoltaic solar plants

This research article discusses the impact of climatic changes in South America, with a case study in a tropical zone, particularly the rise in temperature by 1.15 °C from 1998 to 2022, reaching a maximum of 45.85 °C in 2023. Focusing on the Electronic Conversion Unit, especially IGBT efficiency during El Niño-Southern Oscillation phenomenon in 2023. The case study employs finite element analysis using Navier Stockes-Boussinesq equations, it evaluates the heat dissipation, airflow modeling, and temperature effects, the research proposes enhancements like redesigned air flow grids, centralized air filters, and wind fans. Implementing these improvements reduces the temperature by 5.6 °C, enhances airflow speed, and mitigates the climatic impact on electronic devices over the next two decades.

Robust economic–environmental dispatch problem for BESS and PV generators in MT-HVDC systems: A MI-MPC approach

The research addresses the energy management problem (EMP) in multi-terminal high-voltage direct current (MT-HVDC) systems using a mixed-integer model predictive control (MI-MPC). The MT-HVDC system consists of conventional thermal generation plants (fossil sources), renewable generation sources (solar photovoltaic plants), and battery energy storage systems (BESS). This combination creates a complex nonlinear EMP, as it introduces the power losses of the transmission networks through B-coefficients. The main contributions of this research can be summarized in three elements: (i) the formulation of a measurement- or simulation-based approach to determine B−coefficients in MT-HVDC systems for calculating power losses; (ii) the convexification of the EMP model through MI-MPC approaches, allowing to minimize economic and environmental objective functions; and (iii) the inclusion of uncertainties through the robust convex method. Numerical validations in the 11-bus grid, including the linear transportation model for the MT-HVDC system, confirm the multi-objective nature of the EMP when considering economic and environmental indices. In addition, the effect of uncertainties on generation and demand causes significant variations in the optimal Pareto front when compared to the deterministic scenario.