Day-Ahead Scheduling for Virtual Power Plant to Participate in Iranian Energy Market Based on Fischer Black Pricing Model

A precise bidding model must be established to determine how virtual power plants (VPPs) participate in the energy market. The primary purpose of these models is to maximize profits from the perspective of the electricity market and consider the virtual power plant as a participant in the market. The main goal of this paper is to present a scheme for bidding a VPP before entering the next-day competitive power market. For this purpose, the objective function as the VPP’s profit maximization is defined according to the Fischer Black pricing model and solved utilizing the Mixed-Integer Nonlinear Programming (MINLP) method. Forecasting the hourly electricity prices for the next day will also be performed using the conventional linear regression method. The purpose of bidding is to maximize the profits of the virtual power plant, and the VPP is recognized as an individual participant in the next-day competitive power market. A hospital connected to the Shahid Mirhaj 63-kV substation in Semnan province, Iran, is selected as the case study with known hourly electricity prices and load data. The associated numerical results confirm the validity of the proposed pricing scheme.