Efficient Output Photovoltaic Power Prediction Based on MPPT Fuzzy Logic Technique and Solar Spatio-Temporal Forecasting Approach in a Tropical Insular Region

Fateh Mehazzem (), Maina André and Rudy Calif
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Fateh Mehazzem: Univ Antilles, LaRGE Laboratoire de Recherche en Géosciences et Energies (EA 4539), F-97100 Pointe-à-Pitre, France
Maina André: Univ Antilles, LaRGE Laboratoire de Recherche en Géosciences et Energies (EA 4539), F-97100 Pointe-à-Pitre, France
Rudy Calif: Univ Antilles, LaRGE Laboratoire de Recherche en Géosciences et Energies (EA 4539), F-97100 Pointe-à-Pitre, France

Energies, 2022, vol. 15, issue 22, 1-21

Abstract: Photovoltaic (PV) energy source generation is becoming more and more common with a higher penetration level in the smart grid because of PV energy’s falling production costs. PV energy is intermittent and uncertain due to its dependence on irradiance. To overcome these drawbacks, and to guarantee better smart grid energy management, we need to deal with PV power prediction. The work presented in this paper concerns the study of the performance of the fuzzy MPPT approach to extract a maximum of power from solar panels, associated with PV power estimation based on short time scale irradiance forecasting. It is particularly applied to a case study of a tropical insular region, considering extreme climatic variability. To validate our study with real solar data, measured and predicted irradiance profiles are used to feed the PV system, based on solar forecasting in a tropical insular context. For that, a spatio-temporal autoregressive model (STVAR) is applied. The measurements are collected at three sites located on Guadeloupe island. The high variability of the tropical irradiance profile allows us to test the robustness and stability of the used MPPT algorithms. Solar forecasting associated with the fuzzy MPPT technique allows us to estimate in advance the produced PV power, which is essential for optimal energy management in the case of smart energy production systems. Simulation of the proposed solution is validated under Matlab/Simulink software. The results clearly demonstrate that the proposed solution provides good PV power prediction and better optimization performance: a fast, dynamic response and stable static power output, even when irradiation is rapidly changing.

Keywords: boost converter; MPPT fuzzy; output PV power estimation; PV system; solar forecasting; STVAR model; tropical insular region (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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