Solar Photovoltaic Power Plant Research Articles

PERANCANGAN PLTS TERAPUNG UNTUK MENDUKUNG WISATA HIJAU DI BENDUNGAN TAMBLANG, DESA SAWAN, KABUPATEN BULELENG

The Province of Bali have many dams, one of it is the Tamblang Dam, which is located in Sawan Village, Sawan District, Buleleng Regency. The Government of Buleleng Regency is planning to make Tamblang Dam as a new Tourist Destination Area (Daerah Tujuan Wisata or (DTW) in order to improve the existing tourism conditions in North Bali. It is planned to utilizing Renewable Energy (Energi Baru Terbarukan or EBT) sources to support the needs of DTW and to support government programs to reaching the Bali's clean energy target on 2050. The Renewable Energy Power Plant that will be designed is a Floating Solar Photovoltaic (PV) Power Plant, as it the potential source of energy considering that Indonesia is located on the equator. The Solar PV Power Plant is designed using the tool from website by utilizing 5% of the surface area of the dam water which is 4,561.97 m2, based on Kementrian PUPR no 6 Tahun 2020 regulation. So that a Floating Solar PV Power Plant capacity of 0.6 MW is obtained by using 1,533 solar modules and produce energy reaching of 926,539 kWh in a year. The designed Floating PV need an initial investment cost of IDR 13,551,481,157, with the result of economic analysis, obtained value of each parameter including the NPV value is IDR 7,470,053,884, BCR is 2.66, and PP is less than 25 years.

Implementation of String Inverters for 50 MW Large Scale Solar Power Plant in Malaysia

The growth of large-scale solar photovoltaic (LSSPV) power plant site development in Malaysia has increased the demand for the reliability and potentiality of the system in achieving efficient monitoring, operation, and maintenance for the plants. A configuration of string inverters is applied in a 50 MW large-scale solar photovoltaic installation because of its flexibility and scalable technological advancements. This installation demonstrates that the plant can optimise the power output and monitor the performance of the system up to the string level with a cost-efficient implementation. The output from each photovoltaic (PV) string provides a guarantee of better maximum power point tracking (MPPT) capability. Instead of having shorter DC wires compared to the central inverter, this system offers the potentiality of monitoring the solar PV module at a string level, which also affords scalability for future expansion. The tests conducted verify that the string inverter configuration serves as a reliable outcome for grid code test (GCT) requirements. Furthermore, the string inverters provide a potential approach to achieving maximum power generation in different climate conditions, thus reducing the need for manpower in operation and maintenance activities. The string system offers a feasible implementation of effective configurations and decarbonisation for LSSPV in Malaysia without frequent shutdowns of plant generation due to defects or damage to PV equipment and modules.

Performances Analysis of Three Grid-Tied Large-Scale Solar PV Plants in Varied Climatic Conditions: A Case Study in Algeria

Currently, for the determination of the suitable and optimal PV power plant according to the climate conditions of the concerned region, researchers focus on the estimation of certain performance factors, which are reported to be the key parameters for the analysis of the performances of grid-connected photovoltaic (PV) power systems. In this context, this paper focuses on on-site real-time analysis of the performance of three solar photovoltaic plants: Sidi-bel-Abbés (12 MWp), Laghouat (60 MWp), and Ghardaïa (1.1 MWp). These plants are located in different regions experiencing diverse climatic conditions in Algeria. The analysis was carried out by the standardized norms of IEC 61724, using monitoring data collected over one year. The photovoltaic power plants were evaluated in terms of performance factors, such as the reference yield (Yr), final yield (Yf), performance ratio (PR), and capacity factor (CF). On the other side, based on real data collected at the concerned sites, two linear functions depending on solar irradiance and the PV module temperature for each site are proposed for the evaluation of the generated alternative power output (PAC) for the three PV plants. The obtained results based on the study presented in this paper can help designers of PV power plants of different technologies and different climate conditions to precisely decide the convenient technology that allows the best production of the electrical energy for grid-tied PV systems. Furthermore, this study can contribute in giving a clear vision of the implementation of upcoming large-scale solar PV power plants in Algeria within the studied area and other areas.

Predictive modeling of PV solar power plant efficiency considering weather conditions: A comparative analysis of artificial neural networks and multiple linear regression

This study investigates the surface parameters and environmental factors affecting the energy production of a 500 kWp photovoltaic (PV) solar power plant in Igdir province. Using both the PV panel characteristics and the weather conditions specific to the power plant location, a total of 7 detailed features were included. The estimation of the power plant efficiency, a novel contribution not found in previous studies, is also a major focus. The performance evaluation of different models, including feed-forward neural networks and multiple linear regression, demonstrates the effectiveness of artificial neural networks in capturing the complex relationships between features and efficiency despite limited data availability. Principal Component Analysis (PCA) was used to reduce feature dimensions, showing that even with a reduced feature set, accurate efficiency prediction is still achievable. Prediction using PCA is one of the novelties of the paper. The effects of solar irradiation, module power, and module temperature on power plant efficiency are revealed. The results provide valuable insights for optimizing energy investments in the Igdir region and highlight the potential of artificial neural networks in energy forecasting, demonstrating their suitability for capturing complex patterns in solar power plant efficiency.

New concept on 100.74 kWp floating solar photovoltaic plant and a real mechanical failures assessment: Case of study at Santa Clara hydroelectric power plant reservoir in southern Brazil

Structural failures and partial sinking were assessed in a 100.74 kWp floating solar photovoltaic power plant installed in southern Brazil, at the Santa Clara HPP reservoir. Their occurred during a torrential rain of 159.6 mm, accompanied by wind gusts of 72 km/h, resulting in the platform losing its linearity and causing permanent deformations in the metallic structures. Computer simulation tests calculated the instantaneous forces to be greater than 22 kN. Repairs were carried out replacing the mobile longitudinal fastening elements between modules with rigid and semi-rigid sets. To prevent direct contact between the mooring modules and the PV platform, transverse footbridge lines and a new concept of anchorage modules were introduced, incorporating semi-rigid elements to absorb energy from impacts. Since then, the anchoring systems have been functioning, even under adverse subtropical climate conditions, as occurred in July 2023, with an extratropical cyclone with wind gusts of around 150 km/h.

An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting

The installation of large-scale solar (LSS) photovoltaic (PV) power plants continues to rise globally as well as in Malaysia. The data provided by LSS PV consist of five weather stations with seven parameters, a 22-unit inverter, and 1-unit PQM Meter Grid as a big dataset. These big data are rapidly changing every minute, they lack data quality when missing data, and need to be analyzed for a longer duration to leverage their benefits to prevent misleading information. This paper proposed the forecasting power LSS PV using decision tree regression from three types of input data. Case 1 used all 35 parameters from five weather stations. For Case 2, only seven parameters were used by calculating the mean of five weather stations. While Case 3 was chosen from an index correlation of more than 0.8. The analysis of the historical data was carried out from June 2019 until December 2020. Moreover, the mean absolute error (MAE) was also calculated. A reliability test using the Pearson correlation coefficient (r) and coefficient of determination (R2) was done upon comparing with actual historical data. As a result, Case 2 was proposed to be the best input dataset for the forecasting algorithm.

A solar radiation intelligent forecasting framework based on feature selection and multivariable fuzzy time series

Accurate solar radiation forecasting can effectively improve solar energy utilization efficiency and decrease the operational cost of solar photovoltaic power plants. However, some common forecasting methods have certain limitations, such as neglecting data fuzziness, meteorological factors, feature selection, and seasonal adjustment. Therefore, a solar radiation intelligent forecasting framework based on feature selection and multivariable fuzzy time series is proposed. Specifically, a combined fuzzy strategy is used to fuzzy the data, and an improved multi-objective optimization algorithm is proposed to search for the optimal parameters. A seasonal multivariable fuzzy time series is proposed to achieve multivariable inputs and seasonal adjustments. The experimental analysis, statistical test, and robustness analysis all verify the superiority of the proposed forecasting framework compared with competitive models. The MAPE values of the proposed forecasting framework for two regions are about 6% and 4%, respectively, which outperform some common basic models such as BPNN(about 11% and 9%), ELM(about 12% and 10%), LSTM(about 9% and 7%). The comparison analysis further indicates that the vital parts of the forecasting framework containing feature selection, seasonal adjustment, multi-objective optimization, and multivariable inputs can all have a positive influence on forecasting performance.

Feasibility Analysis of a 100MW Photovoltaic Solar Power Plant at Rajshahi, Bangladesh Using RETScreen Software

Feasibility Analysis of a 100MW Photovoltaic Solar Power Plant at Rajshahi, Bangladesh Using RETScreen Software

ANALYSIS OF SOLAR ENERGY POTENTIAL IN THE PT. SUMEDANG TELEVISI UTAMA BUILDING AS AN ALTERNATIVE ENERGY SOURCE

Indonesia is a tropical region with significant solar energy potential, where the average daily sunlight reaches 4.5 - 4.8 kWh/m²/day. This makes solar energy one of the promising forms of renewable energy worthy of development. The instability of electricity supply from the national grid (PLN) is a prevalent issue across various regions. PT. Sumedang Televisi Utama (SMTV), a television broadcasting company, frequently encounters disruptions in TV broadcasts due to power supply issues originating from PLN. Hence, this research holds the urgency to explore alternatives that can provide electricity supply during interruptions in the PLN power distribution. The contribution of this study lies in the development of a practical and applicable Photovoltaic Solar Power Plant (PLTS) module. With the implementation of this module, it is anticipated that PT. Sumedang Televisi Utama (SMTV) and other entities can have a backup electricity supply source, mitigating the impact of power supply disturbances from PLN. Suggesions for further research include delving deeper into the efficiency and performance assessment of the designed PLTS module under various environmental conditions and weather patterns that are typical in Indonesia. Furthermore, subsequent research could focus on integrating a more effective energy storage system with the PLTS module, thereby maximizing solar energy utilization even during periods of limited sunlight. This endeavor would enhance the resilience and availability of alternative power supply during instances of disruptions in the national grid (PLN) distribution.

Evaluation and modeling of a solar photovoltaic power plant: Case of the Sakal plant

This paper proposes an evaluation and modeling of the Sakal solar PV plant. In this work, we have developed and validated a model that takes into account shading effects. The studied solar power plant is mobile on a horizontal north-south axis of east-west tracking. The results showed that the model tracked the system with a correlation coefficient of 0.993. In the following, we considered the power plant fixed to evaluate the gain between the fixed and mobile collector power plants. Subsequently, we considered the plant a two-axis mobile plant. The performance of the different configurations was evaluated. The results showed that the power plant with a two-axis mobile sensor provided a gain of 40.49 % compared to the power plant configured with a fixed sensor, and a gain of 5.378 % compared to the power plant with a single-axis mobile sensor.

Stability model integration for large scale solar photovoltaic system using Western electricity coordinating council model

<span lang="EN-US">Due to the increased demand for renewable energy, the interest in the large-scale solar photovoltaic (LSSPV) power plant has recently grown dramatically. However, when a large amount of electricity is produced from the LSSPV power plant to the grid interconnection, the system commonly experiences instability and thus disrupt the grid system in disturbance issues such as bus fault, line-to-line fault, three-phase fault, and tripping. This sudden disturbance occurrence is tended to interrupt the stability of the system from providing balanced electrical production within the electrical grid. A dynamics response from the simulation is used to study the stability and the behavior of the photovoltaic (PV) plant into the grid interconnection by developing 118 bus system. The observation of critical clearing time (CCT) duration shows that the result from the simulation where the duration takes less than t=15 s for the system to get back to its pre-fault condition in three-phase fault and tripping in a dynamic simulation to shows that the system reaches its stability been observed through the simulation result by using from user-specific models to generic models like those advocated by the Western electricity coordinating council (WECC) in power system simulator for engineering (PSSE) software.</span>

Simulation of a floating solar farm in waves with a novel sun-tracking system

The awareness of the energy and climate crisis has accelerated the development of renewable energy sources. Photovoltaic (PV) solar power plants harvest clean solar energy and convert it to electricity, which will be one of the most promising alternatives to the power industry in the context of a low-carbon society. Due to its low power density, the traditional deployment of PV systems on land or inland rivers requires much space. Therefore, industries are increasingly interested in expanding offshore Floating PhotoVoltaics (FPV) to oceans, where FPV has less influence on the marine environment and does not occupy precious space for land resources and human activities. This study performs a hydrodynamics-based structural response analysis for a novel FPV system in OpenFOAM. The wave-proof FPV platform is newly designed for this work, which integrated breakwater technologies to sustain the system’s survivability in harsh ocean-wave environments. Firstly, the rational mooring types for FPVs installed close to the island are studied considering seabed effects. Subsequently, extensive parametric studies have been conducted to determine a rational design strategy for the mitigation of wave impact. Several potential effects of the proposed platforms on the hydrodynamics in a coastal sea are evaluated for the first time.

Potential benefits and risks of solar photovoltaic power plants on arid and semi-arid ecosystems: an assessment of soil microbial and plant communities.

Exponential increase in photovoltaic installations arouses concerns regarding the impacts of large-scale solar power plants on dryland ecosystems. While the effects of photovoltaic panels on soil moisture content and plant biomass in arid ecosystems have been recognized, little is known about their influence on soil microbial communities. Here, we employed a combination of quantitative PCR, high-throughput sequencing, and soil property analysis to investigate the responses of soil microbial communities to solar panel installation. We also report on the responses of plant communities within the same solar farm. Our findings showed that soil microbial communities responded differently to the shading and precipitation-alternation effects of the photovoltaic panels in an arid ecosystem. By redirecting rainwater to the lower side, photovoltaic panels stimulated vegetation biomass and soil total organic carbon content in the middle and in front of the panels, positively contributing to carbon storage. The shade provided by the panels promoted the co-occurrence of soil microbes but inhibited the abundance of 16S rRNA gene in the soil. Increase in precipitation reduced 18S rRNA gene abundance, whereas decrease in precipitation led to decline in plant aboveground biomass, soil prokaryotic community alpha diversity, and dehydrogenase activity under the panels. These findings highlight the crucial role of precipitation in maintaining plant and soil microbial diversities in dryland ecosystems and are essential for estimating the potential risks of large-scale solar power plants on local and global climate change in the long term.

Large, grid-connected solar photovoltaic power plants renewable energy

As an essential part of renewable energy, the solar photovoltaic technic grows rapidly with two main types: off-grid and grid-connected systems. This paper focuses on grid-connected solar photovoltaic power plants and introduces the main physical principles of solar photovoltaics. Typical components of solar photovoltaic power plants are also presented, along with their functions. The extraordinary environmental impact and the relatively low and decreasing cost of grid-connected solar photovoltaics reflect its excellent development potential. Compared with other energy, grid-connected solar photovoltaics provides an alternative to conventional fossil fuel generation. With the improvement of silicon purification technology and the working efficiency of solar batteries, the scale of grid-connected solar photovoltaics power plants will be further expanded.

Characterization and mapping of photovoltaic solar power plants by Landsat imagery and random forest: A case study in Gansu Province, China

Numbers and sizes of photovoltaic solar power plants have grown unprecedentedly over the last few years in China, which aims to achieve a carbon emission peak by 2030 and carbon neutrality by 2060. Thus, timely and accurate monitoring of photovoltaic solar power plants is crucial to the design and management of renewable electricity systems in China. Random forest algorithm has been used to map photovoltaic solar power plants at multiple scales, however, it always causes several salt-and-pepper noises, limiting its application at larger spatial scales. Here we first develop a photovoltaic solar power plant mapping method through integrating time series Landsat imagery, random forest, and morphological characteristics. Then we apply this method in Gansu Province, which has abundant solar and wind energy resources and provide large amounts of potential lands for photovoltaic development, and generate the annual photovoltaic maps from 2015 to 2020. We further analyze the spatial-temporal dynamics of sizes and areas of photovoltaic solar power plants and major land cover conversion of expansive photovoltaic regions. Finally, we discuss the reliability, uncertainties, implications, and future development of our improved methods. We find our photovoltaic mapping method can remove most of salt-and-pepper noises effectively, and the resultant maps in Gansu for 2020 have very high accuracies with user's and producer's accuracies of 97.57% and 99.22%, respectively. There are 165.29 km2 photovoltaic solar power plants in Gansu for 2020, and most of which are located in the northwestern Gansu. In addition, the photovoltaic with patch size > 1 km2 and ≤ 2 km2 (53.4 km2, 32.3%) has largest patch number (39, 15.7%). The improved photovoltaic mapping methods and further analysis in this study provide critical information for accurate and automatic classification of photovoltaic solar power plants in the future, as well as the environmental and sustainable development of solar energy in China.

Overcoming the Fluctuating Curve from PV Power Generation by Modelling the Integration of Hydrogen Energy Storage Into Electricity Microgrid

Java Madura Bali (Jamali) system is the Indonesian largest grid, which contributes approximately 61%, with the Coal Thermal dominates by 59% and followed by the New Renewable Energy (NRE) of 9%. Solar Photovoltaic Power Plants (SPP) contribute only 1% from the NRE itself. Low voltage customers (TR) are approximately 61% with the residential contribute approximately 42%. The rates of the national SAIDI is 12.72 hours/subscriber/year and the national SAIFI is 9.25 times per subscriber/year. There is some challenge in regulating voltage in area with high penetration of solar PV, case of voltage fluctuation in response to the fluctuating of solar irradiance, as well as other factors such as load transient. This voltage fluctuation is proportional to the amount of current generated by the PV system and also proportional to the solar irradiance.Hydrogen energy storage (HES) is an alternative to NRE-based energy storage technology. Integrating solar PV with hydrogen energy storage and optimisation device may mitigate PV-driven voltage fluctuation, preventing excessive reserve power flow on the grid. The hydrogen energy storage system can cover variation of the loads at the nearby solar PV system in the microgrid and the ability to manage those loads, as mentioned in the energy management system. Integrating the HES within Solar PV system can improve the curve shape, improve system reliability and voltage stability, especially in the Residential Microgrid. Also may build the opportunities to earn new revenues from wholesale electricity markets, enhancing the reliability rate and competitive monetary value.

Assessing the viability of a grid-connected PV power plant in Mubi, Adamawa State, Nigeria

This paper is based on a techno-economic analysis and the environmental impact of a proposed 1 MW solar photovoltaic (PV) power plant at the main campus of the Federal Polytechnic Mubi (FPM) in north-eastern Nigeria. A photovoltaic power plant converts solar radiation into electricity that can be used as a source of electrical power to meet the daily energy requirements of homes, equipment, and all tertiary institutions. RETScreen Expert software was used to evaluate the techno-economic and environmental sustainability of installing a grid-connected PV power plant. The research results revealed that with an annual solar radiation of 5.74 kWh/m2/day, the maximum annual energy production was estimated to be 1,550.98 MWh. It was discovered that the maximum energy production in March was 146.89 MWh. The project’s profitability and economic sustainability were determined with a good internal rate of return (IRR) of 11.9% and a positive net present value (NPV) of $681,164. The proposed PV power plant has a simple payback period of 11.4 years. The maximum greenhouse gas (GHG) emission reduction is 670.9 tCO2, equivalent to 61.7 ha of forest-absorbing carbon emissions.

Performance analysis of a 50 kW grid-tied PV system on energy productivity in a technical institution building and mitigation method to improve the low power factor problem

A 50-kW grid-interactive solar photovoltaic (SPV) power plant was installed on the rooftop of the Government College of Engineering Kannur (GCEK) in Kerala, India (11◦59′9″N, 75◦22′55″E) on 28th May 2018. The plant was funded by an initial capital investment of ₹36 Lakh, including a subsidy of ₹16 Lakh from the Ministry of New and Renewable Energy (MNRE) of the Government of India. The plant has been operating smoothly, with an average energy production of 150 kWh per day. However, a review of the monthly electricity bills of the institution showed that the interconnection of the PV plant has resulted in a power factor penalty of approximately ₹3.5 Lakh for a period of 3 years. This prompted further analysis to identify the cause of the low power factor. The goal of this work is to study and analyze the 50-kW solar plant, focusing on the reasons for the low power factor and suggesting methods to improve the power factor of the GCEK power system. This type of analysis will be useful while designing a SPV power plant for a technical institution in a country like India with similar load profile.

Model predictive control of a microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV systems

This paper presents a new energy management system (EMS) based on model predictive control (MPC) for a microgrid with solar photovoltaic (PV) power plants and a quasi-Z-source cascaded H-bridge multilevel inverter that integrates an energy storage system (ES-qZS-CHBMLI). The system comprises three modules, each with a PV power plant, quasi-impedance network, battery energy storage system (BESS), and voltage source inverter (VSI). Traditional EMS methods focus on distributing the power among the BESSs to balance their state of charge (SOC), operating in charging or discharging mode. The proposed MPC-EMS carries out a multi-objective control for an ES-qZS-CHBMLI topology, which allows an optimized BESS power distribution while meeting the system operator requirements. It prioritizes the charge of the BESS with the lowest SOC and the discharge of the BESS with the highest SOC. Thus, both modes can coexist simultaneously, while ensuring decoupled power control. The MPC-EMS proposed herein is compared with a proportional sharing algorithm based on SOC (SOC-EMS) that pursues the same objectives. The simulation results show an improvement in the control of the power delivered to the grid. The Integral Time Absolute Error, ITAE, achieved with the MPC-EMS for the active and reactive power is 20 % and 4 %, respectively, lower than that obtained with the SOC-EMS. A 1,3 % higher charge for the BESS with the lowest SOC is also registered. Furthermore, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is implemented to validate the simulation results.

Large-scale green hydrogen production via alkaline water electrolysis using solar and wind energy

The study provided a precise technique for comparing wind and solar solutions for large-scale production of green hydrogen. A one-year experimental dataset depicting the wind speed and solar irradiance with a precision of 1 min. The carbon footprint study was conducted, and indicators were applied and evaluated for the purpose of standardising the performance assessment technique for renewable-based hydrogen production systems, such as the electrolyser capacity fulfilled by wind turbines and solar photovoltaic power plants. On the basis of the considered capacities of 2.5 for wind turbines and solar photovoltaics for cost estimating findings, the obtained optimum electrolyser capacity can match the energy produced by the wind turbine power plant, which is 1.5 MW, which can produce hydrogen at a rate of about 11,963 kg/year at 8.87$/kg, and the obtained optimum electrolyser capacity can match the energy produced by the solar photovoltaics power plant, which is 2.0 MW, which can produce hydrogen at a rate of about 94,432 kg/year at 6.33 $/kg. Further, the polynomial relation between hydrogen production and electrolyser capacity has been destroyed. The method used is easily adaptable for testing large-scale applications such as industrial plants, as well as any hydrogen requirements and environmental conditions.