Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid
This addresses the lack of OPF tools for unbalanced multi-phase networks in smart grids, which is an incremental improvement for power system planning.
The paper tackled the problem of designing an Optimal Power Flow (OPF) tool for unbalanced multi-phase distribution networks in smart grids, proposing a new technique based on Particle Swarm optimization that was validated on the IEEE 8500-node benchmark system.
Recently there has been increasing interest in improving smart grids efficiency using computational intelligence. A key challenge in future smart grid is designing Optimal Power Flow tool to solve important planning problems including optimal DG capacities. Although, a number of OPF tools exists for balanced networks there is a lack of research for unbalanced multi-phase distribution networks. In this paper, a new OPF technique has been proposed for the DG capacity planning of a smart grid. During the formulation of the proposed algorithm, multi-phase power distribution system is considered which has unbalanced loadings, voltage control and reactive power compensation devices. The proposed algorithm is built upon a co-simulation framework that optimizes the objective by adapting a constriction factor Particle Swarm optimization. The proposed multi-phase OPF technique is validated using IEEE 8500-node benchmark distribution system.