Self-scheduling approach to coordinating wind power producers with energy storage and demand response

Abstract

The uncertainty of wind energy makes wind power producers (WPPs) incur profit loss due to balancing costs in electricity markets, a phenomenon that restricts their participation in markets. This paper proposes a stochastic bidding strategy based on virtual power plants (VPPs) to increase the profit of WPPs in short-term electricity markets in coordination with energy storage systems (ESSs) and demand response (DR). To implement the stochastic solution strategy, the Kantorovich method is used for scenario generation and reduction. The opti-mization problem is formulated as a Mixed-Integer Linear Programming (MILP) problem. From testing the proposed method for a Spanish WPP, it is inferred that the proposed method en-hances the profit of the VPP compared to previous models.