Control and Implementation of an Energy Management Strategy for a PV–Wind–Battery Microgrid Based on an Intelligent Prediction Algorithm of Energy Production

Sameh Mahjoub, Larbi Chrifi-Alaoui (), Saïd Drid and Nabil Derbel
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Sameh Mahjoub: Laboratory of Innovative Technology (LTI, UR-UPJV 3899), University of Picardie Jules Verne, 80000 Amiens, France
Larbi Chrifi-Alaoui: Laboratory of Innovative Technology (LTI, UR-UPJV 3899), University of Picardie Jules Verne, 80000 Amiens, France
Saïd Drid: L.S.P.I.E Laboratory, Electrical Engineering Department, Batna 2, Batna 05000, Algeria
Nabil Derbel: National Engineering School of Sfax, Sfax 3038, Tunisia

Energies, 2023, vol. 16, issue 4, 1-26

Abstract: This paper describes an energy management strategy for a DC microgrid that utilizes a hybrid renewable energy system (HRES) composed of a photovoltaic (PV) module, a wind turbine based on a permanent magnetic synchronous generator (PMSG), and a battery energy storage system (BESS). The strategy is designed to provide a flexible and reliable system architecture that ensures continuous power supply to loads under all conditions. The control scheme is based on the generation of reference source currents and the management of power flux. To optimize the supply–demand balance and ensure optimal power sharing, the strategy employs artificial intelligence algorithms that use previous data, constantly updated forecasts (such as weather forecasts and local production data), and other factors to control all system components in an optimal manner. A double-input single-output DC–DC converter is used to extract the maximum power point tracking (MPPT) from each source. This allows the converter to still transfer power from one source to another even if one of the sources is unable to generate power. In this HRES configuration, all the sources are connected in parallel through the common DC–DC converter. The strategy also includes a long short-term memory (LSTM) network-based forecasting approach to predict the available energy production and the battery state of charge (SOC). The system is tested using Matlab/Simulink and validated experimentally in a laboratory setting.

Keywords: double-input single-output converter; energy management; experimental validation; hybrid renewable energy system (HRES); prediction (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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