Transmission expansion planning considering the impact of distributed generation

Abstract

Distributed Generation (DG) is a very important alternative to the traditional approach of centralized generation and plays a major role not only in electric distribution systems but also in transmission systems. The incidence of DG in the electrical system (sub-transmission and/or distribution) could defer the addition of new transmission circuits and reduce transmission network losses, representing potential economical savings. This paper studies the economic impact of DG on the Transmission Expansion Planning (TEP) problem including also the cost of transmission network losses. A long-term deterministic static transmission expansion planning using the mathematical AC model is presented. DG is modeled as the summation of each type of small-scale generation technology concentrated in the load node. The proposed TEP approach provides information on the optimal combination of transmission circuits and DG in load nodes. The problem, formulated using the AC model, corresponds to a full non convex, non-linear mixed-integer programming (MINLP) problem. Performance comparisons between Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), to solve the problem, are shown. Garver 6 - bus and IEEE 24 - bus test systems are used to evaluate this TEP approach.