Robust unit commitment problem with demand response and wind energy

Currently, both demand response (DR) strategy and renewable energy have been adopted to improve power generation efficiency and reduce greenhouse gas emission. However, the uncertainty and intermittent generation pattern in wind farms and the complexity of demand side management pose huge challenges. In this paper, we analytically investigate how to integrate DR and wind energy with fossil fuel generators to (i) minimize power generation cost; and (2) fully take advantage of the wind energy with the managed demand to reduce greenhouse emission. We first build a two-stage robust unit commitment (UC) model to obtain day-ahead generator schedules where wind uncertainty is captured by a polytopic uncertainty set. Then, we extend our model to include DR strategy such that both price levels and generator schedules will be derived for the next day. For these two challenging models, we derive their mathematical properties and develop a novel solution method. Our computational study on an IEEE 118-bus system with 36 units shows that robust UC models can fully make use of wind generation with less generation cost. Also, the developed algorithm is computationally superior to classical Benders decomposition method.