Optimal generation maintenance scheduling considering financial return and unexpected failure of distributed generation
Autor: | Nopbhorn Leeprechanon, Panit Prukpanit, Phisan Kaewprapha |
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Rok vydání: | 2021 |
Předmět: |
TK1001-1841
Production of electric energy or power. Powerplants. Central stations Distribution or transmission of electric power Operations research Control and Systems Engineering business.industry Computer science Distributed generation Scheduling (production processes) Energy Engineering and Power Technology TK3001-3521 Electrical and Electronic Engineering business |
Zdroj: | IET Generation, Transmission & Distribution, Vol 15, Iss 12, Pp 1787-1797 (2021) |
ISSN: | 1751-8695 1751-8687 |
Popis: | Generation maintenance scheduling (GMS) is an important factor that can improve the reliability of power systems and decrease revenue achieved by generation companies (GenCos). Several GMS models, therefore, are based on these two crucial values. Nonetheless, there is no GMS problem that simultaneously considers unexpected failure of distributed generator (DG), financial return of GenCo, and reserve of system. This paper proposes the GMS model based on a global criterion approach to compromise functions that maximise the GenCo’s annual return and probability that no DG fails unexpectedly. The system reserve (SR) is considered as a reliability constraint, while surplus reserve is exchanged with the main grid. To support alternative energy sources that have uncertain outputs and ensure continuous operation of DG, short‐term GMS model including power from wind farm, photovoltaic system, energy system storage, and demand response (DR) is also run by adding the SR and inconstant cost of DR. Effectiveness of the proposed model is examined using the IEEE 6 and IEEE 18‐bus test systems. Results show that not only the proposed model provides a better GMS solution for the GenCo, resulting in appropriate values of the two objectives, but also alternative energy sources are useful for the short‐term GMS. |
Databáze: | OpenAIRE |
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