Management And Optimization Of The Integration Of Renewable Energy Sources In Distribution Power Systems

Résumé: In recent years, the integration of Renewable Energy Sources (RESs) into distribution networks has significantly increased due to technological, financial, and ecological considerations. However, challenges arise from the inherent fluctuations in the output powers of RESs, particularly photovoltaic and wind turbine generators. This uncertainty necessitates careful planning, considering load demand, energy pricing, and RESs output power variability. This thesis proposes effective methodologies for determining optimal RESs sizes and locations under both probabilistic and deterministic conditions, utilizing sophisticated optimization techniques such as the Modified Walrus Optimization Algorithm (MWaOA) and the Standard Walrus Optimization Algorithm (WaOA). Objective functions include improving voltage profiles, reducing total power loss, minimizing costs, and enhancing system stability. The likelihood of wind speed, solar irradiation, load demand, temperature, and network pricing is estimated using the Weibull Probability Distribution Function (WPDF) and the normal PDF, while Monte Carlo simulation techniques capture system uncertainty. Simulation results demonstrate that optimal RESs allocation can lead to reduced overall costs, minimized power losses, improved voltage profiles, and enhanced system stability. Additionally, the superiority of MWaOA over WaOA in resolving RESs allocation problems is confirmed in both deterministic and probabilistic scenarios.

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