Differential Evolution algorithm based Double Integral Sliding Mode Control for Maximum Power Point Tracking of a standalone photovoltaic system

Abstract

The purpose of this study is to develop a robust control strategy based on the Sliding Mode Control (SMC) method and its advanced form of Double Integral Sliding Mode Control (DISMC) enhanced by a Differential Evolution (DE) algorithm. This approach focuses on offering a strong and effective method to adjust the controller parameters to minimize the tracking error between the PV output voltage and the reference. The DE algorithm uses initialization, mutation, crossover, and selection phases to accurately find the optimal controller coefficients for effectively implementing the control strategy of DISMC. The present paper highlights the superior performance of DE-DISMC compared to other controllers optimized with conventional methods, demonstrating its ability to provide the highest stability, accuracy, and efficiency to optimize the Maximum Power Point Tracking (MPPT) process. Using real climatic data from Errachidia city which is located in the south-east of Morocco, this work illustrates DE-DISMC’s ability to maintain the PV system’s peak performance in the face of varying environmental conditions, and the Lyapunov analysis confirms the system’s stability. The results of this study are evaluated using various statistical and analytical metrics, including response time, magnitude of chattering, steady-state error, and efficiency. The findings highlight the high performance of the proposed DE-DISMC controller, especially under real climatic test conditions, achieving a response time of 1.1 ms, which is 58% faster than DE-ISMC and 89% than DE-CSMC, along with a negligible chattering magnitude of $2.8\times 10^{-6}\text{V}$. It also demonstrates strong resilience and effectiveness, reaching a minimal steady-state error of 0.00014 V and a high efficiency of 99.99%. This balance makes DE-DISMC a reliable control solution, especially in changing environmental conditions.