Hybrid NSGA III/dual simplex approach to generation and transmission maintenance scheduling

•Solving the Generation and Transmission Maintenance Scheduling (GTMS) problem.•Hybrid NSGA III/Dual Simplex approach to GTMS problem in a market environment.•Tackling the GTMS problem as mixed-integer, multi-objective optimization problem.•Non-Dominated solutions of the GTMS problem with conflicting objective functions.•Effect of maintenance schedule solutions on network constraints and electricity prices. The generation and transmission maintenance scheduling (GTMS) problem presents generation (GENCOs) and transmission (TRANSCO) companies scheduling their facilities for maintenance to maximize their profits, while the independent system operator (ISO) pushes for maintenance schedules (MS) that guarantees system reliability and minimizes operation cost. Inherently, GTMS is a high-dimensional, non-linear, non-convex, multi-objective optimization problem that contains conflicting objectives related to different participants in the market. This paper develops a hybrid model to tackle the GTMS problem in a deregulated market environment by combining in a novel way the non-dominated sorting genetic algorithm III (NSGA III) and the Dual-Simplex (DS) techniques. The model manages to minimize the total system operational cost and keep high system adequacy, both aspects of interest for the independent system operator (ISO), while increasing the profits of GENCOs. The approach used matches accepted industry maintenance practices with cutting-edge optimization techniques developed in academia. The model, tested in the IEEE-RTS 24 bus test network, delivers a set of feasible MS solutions that address the conflicting relationships between the GENCOs and the ISO in the market, displays a degree of coordination among generation and transmission MS and their impact on electricity prices. Finally, it allows the ISO to use this set to identify the best using the technique for ordering preferences according to the similarity to an ideal solution (TOPSIS) decision-making tool.