Expansion planning of a price-maker virtual power plant in energy and reserve markets

Abstract

This paper addresses the expansion planning problem of a virtual power plant considering the possibility of building new assets such as conventional, renewable, and energy storage units. The VPP is modeled as a price-maker player that strategically participates in energy and reserve markets by altering the prices of these markets to its own benefit. The VPP includes flexible demands, conventional and renewable generating units, and energy storage units. Variabilities in renewable production levels are modeled using a modified clustering K-medoids method, while the uncertain reserve request coefficients are represented using a set of scenarios. The present problem is formulated as a two-stage stochastic bi-level model, where the upper-level problem represents the expected profit of the VPP to be maximized by building new assets, while the lower-level problems model the clearing of the energy and reserve electricity markets for different market conditions, which aim to maximize the social welfare and reduce the cost of the ancillary systems, respectively, and determine the market prices of both markets. The stochastic bi-level model is converted to a single-level mixed-integer linear programming problem by replacing the lower-level problems by their Karush-Kuhn–Tucker optimality conditions and by applying exact linearization techniques. Numerical results show that considering the VPP as a price-maker player influences its expansion decisions and allows the VPP to increase its profit up to 108.8% in comparison with a price-taker behavior. Also, the numerical results indicate that the participation in the reserve market increases a 26.76% the expected profit achieved by the VPP.