Multiobjective Transmission Expansion Planning considering Multiple Generation Scenarios

Abstract

This paper shows a methodology for solving the Transmission Expansion Planning (TEP) problem when Multiple Generation Scenarios (MGS) are considered. MGS are a result of the market based environment introduced by electricity deregulation. The solution to this problem is carried out by using multiobjective evolutionary strategies for the optimization process, implementing a new hybrid modified NSGA-II/Chu-Beasley algorithm. The proposed methodology is validated using the 6-bus Garver system and the IEEE-24 bus system. The TEP is based on the DC model of the network and non-linear interior point method is used to initialize the population.A set of Pareto optimal expansion plans with different levels of cost and load shedding is found for each system, showing the robustness of the proposed approach.

Flexible Solution Approach for Multistage Transmission Network Expansion Planning with Multiple Generation Scenarios

“…e authors (Rahmani et al 2013) proposed three models for the single-stage TNEP problem considering multiple future generation and demand scenarios and a risk evaluation approach, using the Pareto front of the solutions. In (Correa et al 2014), the authors proposed a hybrid nondominated sorting genetic algorithm II (NSGA-II)/Chu-Beasley algorithm to solve the single-stage multiobjective TNEP problem with multiple generation scenarios. e objective functions of the problem accounted for the investment and load shedding costs.…”