Optimal unit maintenance scheduling of a power prouducer under price uncertainty

This paper presents a day-based stochastic unit maintenance scheduling (UMS) model for a power producer in a pool-based power market. Its objective is to maximize the producer´s benefit over the entire scheduling periods, with emphasis on potential risk associated with the fluctuating electricity prices. In the proposed model, the producer´s potential benefit is analyzed in detail, mainly including the expected energy-selling profits in energy market and maintenance cost in each period. In order to evaluate the related risk resulted from the uncertain energy prices, a framework for the Latin Hypercube Sampling Monte Carlo simulation (LHS-MC) is adopted, which outperforms the ordinary Monte Carlo method. Then, the proposed stochastic UMS formulation can be solved using a combination of genetic algorithms and linear programmings. Finally, numerical examples on a four-unit producer are utilized to demonstrate the usefulness of the proposed scheme. Simulation results suggest that the uncertain market prices may lead to high risk on producer´s outage planning and should be considered in producer´s maintenance scheduling.