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Profit-maximization generation maintenance scheduling through bi-level programming

P. Mazidi, Y. Tohidi, A. Ramos, M.A. Sanz-Bobi

European Journal of Operational Research Vol. 264, nº. 3, pp. 1045 - 1057

Resumen:
This paper addresses the generation maintenance scheduling (GMS) dilemma in a deregulated power system. At first, under a centralized cost minimization framework, a GMS is formulated and set as the benchmark (cost-minimization GMS). Then, the cost-minimization is changed into a profit-maximization problem of generation companies (GENCOs) and the GMS is developed as a bi-level optimization. Karush-Kuhn-Tucker conditions are applied to transform the bi-level into a single-level mixed-integer linear problem and subsequently, Nash equilibrium is obtained as the final solution for the GMS under a deregulated market (profit-maximization GMS). Moreover, to incorporate reliability and economic regulatory constraints, two rescheduling signals (incentive and penalty) are considered as coordination processes among GENCOs and independent system operators. These signals are based on energy-not-supplied and operation cost, and ensure that the result of profit-maximization GMS is in the given reliability and social cost limits, respectively. These limits are obtained from the cost-minimization GMS. Lastly, the model is evaluated on a test system. The results demonstrate applicability and challenges in GMS problems.


Palabras Clave: Maintenance, Scheduling, OR in Energy, Coordination Process, Deregulated Power System


Índice de impacto JCR y cuartil WoS: 3,806 - Q1 (2018); 6,000 - Q1 (2023)

Referencia DOI: DOI icon https://doi.org/10.1016/j.ejor.2017.07.008

Publicado en papel: Febrero 2018.

Publicado on-line: Julio 2017.



Cita:
P. Mazidi, Y. Tohidi, A. Ramos, M.A. Sanz-Bobi, Profit-maximization generation maintenance scheduling through bi-level programming. European Journal of Operational Research. Vol. 264, nº. 3, pp. 1045 - 1057, Febrero 2018. [Online: Julio 2017]


    Líneas de investigación:
  • *Planificación Táctica a Medio Plazo
  • *Análisis de Estrategia a Largo Plazo
  • *Modelado, Simulación y Optimización

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