Strategic Bidding for a Virtual Power Plant in the Day Ahead and Real Time Markets: A Price Taker Robust Optimization Approach
We consider an energy management system that controls a cluster of price responsive demands. Besides these demands, it also manages a wind power plant and an energy storage facility. Demands, wind power plant, and energy storage facility are interconnected within a small size electric energy system equipped with smart grid technology and constitute a virtual power plant that can strategically buy and sell energy in both the day ahead and the real time markets. To this end, we propose a two stage procedure based on robust optimization. In the first stage, the bidding strategy in the day ahead market is decided. In the second stage, and once the actual scheduling in the day ahead market is known, we decide the bidding strategy in the real time market for each hour of the day. We consider that the virtual power plant behaves as a price taker in these markets. Robust optimization is used to deal with uncertainties in wind power production and market prices, which are represented through confidence bounds. Results of a realistic case study are provided to show the applicability of the proposed approach.
IEEE Transactions on Power Systems