This paper presents a planning tool for optimizing the day-ahead scheduling and real-time operation of a generic energy storage system (ESS) combined with wind power in a short-term power market. The inherent uncertainty in wind forecasts, spot market prices and expected costs of balancing power are taken into account. The planning problem is formulated as a multi-stage stochastic quadratic optimization problem. The planning tool is tested through a general case study. A generic ESS is operated in combination with wind power in a hydro-thermal power market, with wind data from Mid-Norway and market data from Western Denmark, spanning a total of 3 weeks. The value of combined operation is quantified for different storage sizes and costs of balancing power. Main results show that with present market prices in Denmark West it is cost effective to reduce only a small amount of the wind power imbalances. Although the total operating revenue is increased, all commercial ESS technologies are challenged by high annual costs making them for most cases uneconomical for day-today trading in Western Denmark.
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