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.