Determination of the Performance Scores of a Photovoltaic Power Plant Connected to the Grid: The Zagtouli Photovoltaic Power Plant in Burkina-Faso

Photovoltaic solar energy is still in its infancy in Burkina Faso, despite the country’s high solar potential. The electricity grid is experiencing an increase in demand for energy, creating a shortfall in supply. The Zagtouli photovoltaic solar power plant in Burkina Faso is the first milestone in the development of renewable photovoltaic energy, with a rated output of 33.6 Megawatts peak, to strengthen the electricity grid by reducing hydrocarbon consumption. The aim of this work is to evaluate the performance of the plant by proposing a performance score for the Zagtouli plant, which should provide a basis for assessing the performance of a power plant. To meet the objectives, we collected data for three consecutive years of production, from 2019 to 2021. From this data, we used the method based on the calculation of the performance indicators specified by the International Energy Agency (IEA) and described in the standardised norms IEC (International Electrotechnical Commission) CEI61724, and we also carried out a performance classification using the K-Means method. It is clear that with the results obtained for the PR performance index (over 70%), the installation can be classified as one of the best-performing systems. It also emerges that various losses (temperatures on the panels, cabling, partial shading, spectral losses, dirt, and unexpected inverter failures) have a negative impact on the installation’s energy production.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.

Choice of the Best Production Prediction Model for the Zagtouli Solar Power Plant in Burkina-Faso

In this paper, we present a study on the prediction of the power produced by the 33 MWp photovoltaic power plant at Zagtouli in Burkina-Faso, as a function of climatic factors. We identified models in the literature, namely the Benchmark, input/output, Marion, Cristo-fri, Kroposki, Jones-Underwood and Hatziargyriou prediction models, which depend exclusively on environmental parameters. We then compared our linear model with these seven mathematical models in order to determine the most optimal prediction model. Our results show that the Hatziargyriou model is better in terms of accuracy for power prediction.

Evaluation of the Performance of Lithium-Ion Accumulators for Photovoltaic Energy Storage

In a context of climate change exacerbated by the increasing scarcity of fossil fuels, renewable energies, in particular photovoltaic solar energy, offer a promising alternative. Solar energy is non-polluting, globally available and the most widely distributed resource on Earth. However, the intermittency of this energy source considerably limits its expansion. To solve this problem, storage techniques are being used, in particular, electrochemical storage using lithium-ion batteries. In this article, we will evaluate the performance of lithium-ion batteries when integrated into a photovoltaic grid. To do this, modelling and simulation of a photovoltaic system connected to a lithium-ion battery storage system will be carried out using MATLAB/Simulink software. A diagnostic of the energy consumption of the Kaya Polytechnic University Centre will be carried out, and the data will then be used in the simulator to observe the behaviour of the PV-Lion system. The results obtained indicate that lithium-ion batteries can effectively meet the centre’s energy demand. In addition, it was observed that lithium-ion batteries perform better under high energy demand than the other battery technologies studied. Successive storage systems with the same capacity but different battery technologies were compared. It was found that these storage systems can handle a maximum power of 4 × 105 W for lead-acid batteries, 6.5 × 105 W for nickel-cadmium batteries, 8.5 × 105 W for nickel-metal-hydride batteries, and more than 10 × 105 W for lithium-ion technology.