Multi-objective transmission expansion planning considering multiple generation scenarios

• Multiple generation scenarios are included in the planning process.
• Pareto optimal expansion plans are obtained for Garver and IEEE 24-bus systems.
• An original multiobjective algorithm solves the problem and performance is shown.
• Variable generation and demand is considered in the simulations.

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 multiple load flow patterns caused by realistic operation of the network, such as market rules, availability of generators, weather conditions or fuel prices. 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 and taking into account variable demand and generation. 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.