Optimizing Virtual Power Plant Performance through Three-Phase Power Flow Analysis and TCAS Algorithm

Virtual power plants (VPPs) have gained significant attention in recent years as a promising solution for optimizing the operation of power systems. VPPs allow for the integration and coordination of Distributed Energy Resources (DERs), such as renewable energy sources, to provide grid support and stabilize the power supply. This paper presents a VPP that utilizes a three-phase power flow analysis for its modeling. This approach allows for an accurate representation of the power flow in the VPP, considering the dynamic nature of the power system. In addition to the three-phase power flow analysis, the authors propose a tabu continuous ant colony search (TCACS) to optimize the operation of the VPP, which combines tabu search and ant colony optimization to find near-optimal solutions for complex optimization problems. It uses a tabu list to guide the search towards promising solutions while avoiding getting stuck in local minima. The performance of the proposed VPP has been evaluated through simulation studies, and the results show that it is effective at minimizing power loss and improving the stability of the power system. The proposed VPP can be a valuable tool for utilities to manage their power generation and distribution, particularly in the context of increasing renewable energy integration.