Hybrid genetic algorithm for multi-objective Transmission Expansion Planning

P. Vilaça, J.P. Tomé Saraiva

IEEE International Energy Conference - ENERGYCON 2016, Leuven (Belgium). 04-08 abril 2016

Summary:

This paper aims to describe a new tool to solve the Transmission Expansion Planning problem (TEP). The Non-Dominative CHA-Climbing Genetic Algorithm uses the standard blocks of Genetic Algorithms (GA) associated with an improvement of the population building block using Constructive Heuristic Algorithms (CHA) and Hill Climbing Method. TEP is a hard optimization problem because it has a non convex search space and integer and nonlinear nature, besides, the difficulty degree can be further increased if it includes more than one objective. In this work, a multi-objective TEP approach is detailed using an AC Optimal Power Flow to generate the set of Pareto solutions using the investment cost and the level of CO ₂ emissions, i.e. two conflicting objectives.

Keywords: Transmission Expansion Planning, Multiobjective approach, Pareto solutions, AC Optimal Power Flow.

DOI: https://doi.org/10.1109/ENERGYCON.2016.7514131

Publication date: April 2016.

Citation:
Vilaça, P., Tomé Saraiva, J.P., Hybrid genetic algorithm for multi-objective Transmission Expansion Planning, IEEE International Energy Conference - ENERGYCON 2016, Leuven (Belgium). 04-08 April 2016.

IIT-16-252C