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A Comparative Study of the Performances of the LQR Regulator versus the PI Regulator for the Control of a Battery Storage System

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RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2023年第8期16卷 884-894页

作者： Nouri, Achraf Lachheb, Aymen El Amraoui, Lilia Univ Carthage Lab Smart Elect Natl Engn Sch Carthage Carthage Tunisia Univ Carthage ICT Natl Engn Sch Carthage SEICTLR18ES44 Carthage Tunisia

Background: This paper is consecrated to the development of a new approach to control a bidirectional DC-DC converter dedicated to battery storage systems by applying an optimal control based on a linear quadratic regulator (LQR) combined with an artificial neural network (ANN) algorithm. A state representation of the Buck-boost converter is performed. Then the ANN-LQR control strategy is compared to a classical control based on the proportional-integral controller combined with an ANN algorithm. The ANN algorithm generates the reference charging or discharging current based on a comparison between the power generated and the power consumed. In order to obtain an accurate comparison, two identical systems are designed, each consisting of a photovoltaic system optimized by an incremental conductance algorithm (INC) that powers a dynamic load and a backup storage system consisting of a lithium-ion battery. A management and protection algorithm is developed to protect the batteries from overcharge and deep discharge and to manage the load availability on the DC bus. The simulation results show an improvement in the performances of the storage system by the ANN-LQR control compared to the ANN-PI method and an increase in the stability, accuracy, efficiency of the system is observed. Photovoltaic (PV) energy is one of the most promising technologies for combating climate change and meeting the urgent need for green renewable energy and long-term development. PV energy generation has a number of advantages: Solar energy is limitless and available anywhere on the planet. However, photovoltaic energy is intermittent and depends on meteorological conditions;also, the energy consumed is unpredictable. For this reason, a storage system is necessary to overcome these problems. Objective: The objective of this study is to develop an optimal control using a Linear Quadratic Regulator (LQR) combined with a neural network algorithm (ANN) to improve the performance of an electrical

关键词： Linear Quadratic Regulator (LQR) PI regulator ANN algorithm batteries energy storage system incremental conductance algorithm (INC) management and protection algorithm

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