Seasonal Performance of Solar Power Plants in the Sahel Region: A Study in Senegal, West Africa

The main objective of this study is to evaluate the seasonal performance of 20 MW solar power plants in Senegal. The analysis revealed notable seasonal variations in the performance of all stations. The most significant yields are recorded in spring, autumn and winter, with values ranging from 5 to 7.51 kWh/kWp/day for the reference yield and 4.02 to 7.58 kWh/kWp/day for the final yield. These fluctuations are associated with intense solar activity during the dry season and clear skies, indicating peak production. Conversely, minimum values are recorded during the rainy season from June to September, with a final yield of 3.86 kWh/kW/day due to dust, clouds and high temperatures. The performance ratio analysis shows seasonal dynamics throughout the year with rates ranging from 77.40% to 95.79%, reinforcing reliability and optimal utilization of installed capacity. The results of the capacity factor vary significantly, with March, April, May, and sometimes October standing out as periods of optimal performance, with 16% for Kahone, 16% for Bokhol, 18% for Malicounda and 23% for Sakal. Total losses from solar power plants show similar seasonal trends standing out for high loss levels from June to July, reaching up to 3.35 kWh/kWp/day in June. However, using solar trackers at Sakal has increased production by up to 25%, demonstrating the operational stability of this innovative technology compared with the plants fixed panel. Finally, comparing these results with international studies confirms the outstanding efficiency of Senegalese solar power plants, other installations around the world.

Efficiency Analysis of Grid-connected Photovoltaic Power Plants

Analysis of photovoltaic power plant(PVPP)operations is important to both investors and users and to producers of equipment,researchers and designers as well.This paper presents the analysis of the year-long operations of the group PVPPs in Serbia connected to the distribution network which was carried out through specific indicators such as electric power generation,power,capacity factors,specific yield,losses,period of cost effectiveness of the investment,etc.Special attention has been paid to the influence of the azimuth and tilt of the photovoltaic modules on the performances of PVPPs.Results obtained through the year-long extensive measurements were compared to expected yields of PVPPs on the basis of the Climate SAF PVGIS application.The results of the analysis indicate that available software applications cannot always provide a good enough forecast of expected electric power production since they cannot always assess well enough the effects of the surrounding facilities on operations of a PVPP.In addition,it has been found that the correlation between losses of annual achieved specific yield of a PVPP and the azimuth is represented by a polynomial of the second degree,whereas the correlation between losses of the annual achieved specific yield of a PVPP and the tilt is represented by an exponential function.

Investment risk evaluation of inland floating photovoltaic power plants in China using the HFLTS-TFN method

Inland floating photovoltaic power plants(IFPPPs)are the key to making full use of water advantages to develop solar resources in the future.Identifying the investment risk is an important prerequisite for promoting the projects on a large scale.This paper proposes a model to assess the investment risk of IFPPPs in China.First,this paper identifies the investment risk factors and establishes an evaluation indicator system from four aspects.Second,the indicator data are collected and described by adopting hesitant fuzzy linguistic term sets and triangular fuzzy numbers to ensure soundness and completeness.Third,a weighted method combining the best-worst method and the entropy method are utilized to determine the indicator weights under the consideration of the impact of subjective preferences and objective fairness.Fourth,the results show that the overall risk level of China’s IFPPPs is‘medium low’.Fifth,sensitivity analysis and comparative analysis are implemented to examine the stability of the evaluation results.Finally,this paper also provides some risk-response strategies for the development of China’s IFPPPs from economy,society,technology and environment.

Research on Clustering Equivalent Modeling of Large-Scale Photovoltaic Power Plants

There are dozens or hundreds of grid-connected inverters for large-scale photovoltaic power plants.In order to facilitate the study of the impact that large-scale photovoltaic power plants have on the power system while avoiding the need to establish a detailed model for each inverter,it is necessary to establish the equivalent model of large-scale photovoltaic power plants.Power generation units of the same type are combined by K-means clustering algorithm to reduce the simulation scale in number.According to the actual data of Shenmu large-scale grid-connected photovoltaic power station,employing RT-LAB software is used to conduct simulation verification and error analysis.The simulation results verify the proposed clustering equivalent modeling method is effective and can accurately track photovoltaic power station’s dynamic characteristics.

Analysis and field test on reactive capability of photovoltaic power plants based on clusters of inverters

With the increasing capacity of photovoltaic(PV)power plants connected to power systems, PV plants are often required to have some reactive power control capabilities to participate in reactive power regulation. Reactive power regulation of grid-connected PV inverters can be achieved using different control strategies. In this paper, the reactive power capability of inverters and the technical requirement of PV plants are analyzed. The reactive power capability of a 30 MW PV plant is evaluated against relevant technical standards using a new testing method proposed in this paper.

Study of the Impact of Grid Disconnections on the Production of a Photovoltaic Solar Power Plant: Case of Diamniadio Power Plant

Today, renewable energy projects connected to the interconnected network, with powers of the order of tens of megawatts, are more and more numerous in sub-Saharan Africa. And financing these investments requires a reliable amortization schedule. In the context of photovoltaic systems connected to the interconnected electricity grid, the quintessence of damping is the amount of energy injected into the grid. Thus it is fundamental to know the parameters of this network and their variation. This paper presents an evaluation of the impact of power grid disturbances on the performance of a solar PV plant under real conditions. The CICAD photovoltaic solar plant, connected to the Senelec distribution network, with an installed capacity of 2 MWp is the study setting. An energy audit of the plant is carried out. Then the percentage of each loss is determined: voltage drops, module degradation, inverter efficiency. The duration of each disconnection is measured and recorded daily. The corresponding quantity of lost energy is thus calculated from meteorological data (irradiation, temperature, wind speed, illumination) recorded by the measurement unit in one-minute steps. The observation period is three months. The total duration of disconnections related to the instability of the electrical network during the study period is 46.7 hours. The amount of energy lost is estimated at 22.6 MWh. This represents 2.4% of the actual calculated production.

Study on the Energy Dispatch Strategy of PV Power Plant

Now the energy efficiency of the PV power plant is low.For this case,this paper presents a PV power plant energy scheduling strategy.It includes new grid scheme and scheduling algorithm.Through the establishment of PV power station network model and the method of computer simulation of its scheduling algorithm,this paper describes its realization way,and then proves that the scheduling strat egy is correct and the effectiveness of improving energy conversion rate.At the same time,the PV power station scheduling strategy aslo re duces the environmental pollution,and alleviates the energy crisis and environmental crisis.

Smart component monitoring system increases the efficiency of photovoltaic plants

Due to the increasing expansion of renewable energy,especially the widespread installation of solar power plants worldwide,to better exploit and increase the efficiency and quality of power generation,we need to closely monitor the performance of important components of the plant.In this study,using an innovative smart monitoring system and electronic sensors,we monitored compo-nents such as power in photovoltaic(PV)arrays in real time,including the phenomenon of hot spots as an example of power loss in PV panels.Detection of hot spots is very difficult to deal with in a large power plant.The results also demonstrated smart monitoring that increased detection speed and increased the efficiency rate per supervisory technician by≤36% compared with the previous ef-ficiency rate,which was 10% per technical staff,and increased the quality of the operation of each solar power plant.In this paper,meteorological data were coordinated with research data to validate the research.Furthermore,to compare the results of using the smart monitoring method with the conventional observation method,a complete diagram of a 5-kW solar system in MATLAB■2018 was simulated and output diagrams were presented.Finally,to provide a comprehensive validation,our research results were com-pared with technical data obtained from a local 5-kW solar power plant located in Sari,Iran(36°33ʹ48″N,53°03ʹ36″E)with an average annual irradiation of 1490 kWh/m^(2).When the simulation results and research are analysed,it is clear that the smart and real-time monitoring approach brings various benefits to solar power plants.