Multi-objective optimisation of generation maintenance scheduling in restructured power systems based on global criterion method

• Main Authors: Omid Sadeghian, Arman Oshnoei, Saman Nikkhah, Behnam Mohammadi-Ivatloo
• Format: Article
• Language: English
• Published: Wiley 2019-01-01
• Series: IET Smart Grid
• Subjects: linear programming; Pareto optimisation; cost reduction; power generation scheduling; integer programming; maintenance engineering; power markets; nonlinear programming; power generation reliability; scheduling; search problems; optimisation; generation maintenance scheduling; restructured power systems; global criterion method; important scheduling problems; maintenance time interval; generation unit; multiobjective-GMS; global criterion approach; MO-GMS model; maintenance intervals; generation company; system reserve; independent system operator standpoint; optimal maintenance weeks; IEEE 118-bus test systems; multiobjective model; multiobjective optimisation
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2018.0140

Generation maintenance scheduling (GMS) is one of the most important scheduling problems in the restructured power systems. The maintenance time interval of generation units is the crucial factor of GMS for an operation lifespan of generation units, particularly within the smart grid which needs high reliability. Accordingly, this study proposes a multi-objective-GMS (MO-GMS) optimisation model for maintenance scheduling of generation units based on the global criterion approach, adopting a suitable compromise function. The proposed MO-GMS model determines the maintenance intervals, aims to maximise both the generation company's (GenCo's) financial returns from selling electricity and the system reserve at every time interval from the independent system operator (ISO) standpoint. This method searches the optimal maintenance weeks for each generation unit, considering the objectives of both GenCo and ISO, simultaneously. The proposed MO-GMS model is formulated as a mixed-integer non-linear programming problem and examined on the IEEE 24-bus and IEEE 118-bus test systems. The success of the proposed multi-objective model is validated by comparing the obtained results with intelligent optimisation algorithms.