Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties

Abstract

This paper presents a day-ahead scheduling framework for virtual power plant (VPP) in a joint energy and regulation reserve (RR) markets. The proposed VPP clusters a mix of generation units in term of synchronous distributed generation (SDG) and wind power plant (WPP) as well as storage facilities such as electrical vehicles (EVs) and small pumped storage plant (PSP). It is assumed that VPP provides required RR through its SDG and small PSP based on the delivery request probability of day-ahead market. In order to aggregate EVs, the VPP establishes bilateral incentive contracts with vehicle owners. Moreover, impact of carbon dioxide (CO2) emission of SDG is included by means of penalty cost function. Different uncertain parameters with regard to wind generation, EV owner behaviors, energy and RR market prices and regulation up and down probabilities are considered using a point estimate method (PEM). The case studies are applied to demonstrate the effectiveness of the scheduling model.