Contribution to the Optimization of Electrical Network Energy using Metaheuristic Methods in the Presence of FACTS Systems and Renewable Energies

Contribution to the Optimization of Electrical Network Energy using Metaheuristic Methods in the Presence of FACTS Systems and Renewable Energies = Contribution à l’optimisation de l’énergie des réseaux électriques par les méthodes métaheuristiques en présence des systèmes FACTS et des énergies renouvelables

In this thesis, we presented a strategy to improve the efficiency of the electrical network by combining a Flexible AC transmission system (FACTS) with renewable energy sources, such as wind and solar power. This endeavour addresses a substantial challenge that necessitates meticulous planning for the optimal operation of the system. To address this challenge, we employed an Optimal Power Flow (OPF) approach utilizing the Spider Wasp Optimizer (SWO) algorithm. Our objective was to effectively address various network-related issues, including minimizing power losses, reducing fuel costs and environmental emissions, and optimizing voltage levels. Furthermore, to tackle multi-objective problems, we expanded the algorithm to a multi-objective algorithm (Multi-Objective Spider Wasp (MOSWO) algorithm) and carefully validated its performance using both mathematical and geometric functions. When compared to existing solutions in the literature, our findings indisputably illustrate the superior performance of both single- and multi-objective algorithms. On the other hand, in the economic integration of renewable energy, with or without the determination of appropriate placements and values of Static Var Compensators (SVCs), our main objective is to minimize overall generation costs through efficient scheduling of thermal, wind, and solar units. The SWO algorithm results unmistakably demonstrate that identifying optimal locations and values for FACTS devices in conjunction with wind turbines and solar panels significantly improves system performance from both a technical and economic standpoint, all while adhering to the imposed operational constraints.