Optimizing power management for wind energy integration with SVC support using hybrid optimization

Abstract

Recent years have seen a strong push to incorporate a wider variety of renewable sources (RS) into modern power systems. The intermittent nature of these renewable sources presents a vital challenge. Experts and researchers must develop adaptable and robust planning strategies to successfully integrate with security higher levels of wind and solar power into the grid. This research presents a stochastic optimal power flow (SOPF) strategy designed to mitigate the intermittent nature of multiple wind power sources by effectively coordinating them with multiple shunt (SVCs) based on FACTS technology. To accurately solve complex problems with multiple conflicting objective functions, a hybrid method combining the Pelican Optimizer (PO) and Coati Optimization Algorithm (COA) is effectively applied to optimize various objective functions, including total cost, power loss, voltage deviation, margin loading stability and contingencies. The main particularity of the proposed hybrid method, namely POCOA, compared to the standard PO and to the COA is related to its high ability to create flexible balance between exploration and exploitation during search process, which makes the POCOA more accurate to locate the near global solution at a competitive time. The proposed POCOA was validated on unimodal and multimodal benchmark functions, as well as the modified IEEE 30-Bus electric test system. Comparative study with other recent techniques confirmed its high competitive aspect in terms of solution quality and convergence behaviors.