Multi-objective transmission expansion planning with allocation of fixed series compensation under uncertainties

Abstract

Summary Integration of wind resources into the power systems has increased the technical and financial concerns in transmission expansion planning. In this paper, a stochastic structure is demonstrated for transmission expansion planning with allocation of fixed series compensation under wind and load uncertainties. Fixed series compensations have the ability to increase the transfer capacity of transmission lines. However, their significance benefit for transmission expansion planning is their higher effectiveness in power dispatching, which results in lower investment costs, compared with planning without fixed series compensations. The proposed planning model simultaneously optimizes targets such as the investment cost, the congestion cost, and the expected energy not supplied in each stage. The presented planning model is a complicated nonlinear optimizing problem. For introducing group of nondominated optimal solutions, multi-objective gray wolf optimizer algorithm based on probabilistic optimal power flow is used. Then, fuzzy approach is used to lead to the best response. For demonstrating the feasibility and susceptibilities of the proposed algorithm, the planning methodology has been illustrated on the IEEE 24-bus and Colombian test systems. The results acquired from the simulations monitor capability of the proposed structure in order to satisfy various planning indices.