Optimum Energy Management of the Price-Maker Virtual Power Plant Including Electric Vehicles

Abstract

The optimal energy management of a price-maker (PM) virtual power plant (VPP) that trades in the energy market (EM) and reserve markets (RMs) is the topic of this paper. The VPP sets prices in the EM and RMs and evaluates its offerings one day in advance to heighten its profit. It consists of an electric vehicle fleet, a wind farm, traditional generators, fixed energy storage, and flexible loads. A bi-level model is used to formulate the PM VPP's energy management challenge. The second level problem's objective is to clear the markets while taking the participants' social welfare in to consideration, whereas the first level problem's objective is to heighten the expected profit of the VPP. The bi-level model is converted to a single-level model by replacing the Karush-Kuhn-Tucker (KKT) conditions. The results of this study demonstrate that VPP may significantly boost its profit by setting market prices. The consideration of electric vehicles (EVs) in VPP also increases the profit of the VPP and improves energy management.