New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Ant Colony Optimization

Abstract

Solar energy is extremely reliant on climatic conditions, and fluctuates irregularly, forcing the integration of Photovoltaics PV into power grids problematic. A new paradigm for the energy supply chain is developed, leading to the development of microgrids, in order to enhance the design of power infrastructure and the effective deployment of decentralized and renewable energy sources. Intelligence should be added at all levels of the grid, acting across a variety of periods. This article presents new research tools and methodology to assist utility engineers in studying the grid's potential effect from these new power sources. A revolutionary PV solar system control method is proposed in this research, and the approach is an innovative Maximum Power Point Tracking (MPPT) technique for solar systems, which is based on adding a complicated function. This function tracks the Maximum Power Point (MPP) in PV systems by determining the duty cycle of the DC-DC converter in any environment and the load scenario. In this regard, designing an appropriate controller capable of reducing Power stress inside the PV System is essential. In this paper, the Proportional Integral (PI) controller has been used in conjunction with a metaheuristic approach called Ant Colony Optimization (ACO) in order to manage and stabilize the MPP of the power produced by the PV system. Then, utilizing the five multi-objective performances of Integrated Squared Error (ISE), Integrated Absolute Error (IAE), Integrated Time Absolute Error (ITAE), Integrated Time Squared Error (ITSE), and the Mean Squared Error (MSE), the ACO method has been used to determine the optimal parameters (Kp, Ki) (ITSE). The simulation results demonstrate a strong performance in monitoring the required MPP with the disrupted PV system.