Document Type : Research article

Authors

1 Iran University of Science and Technology (IUST), Tehran, Iran

2 Young Researcher and Elite Club, Hamedan Branch, Islamic Azad University, Hamedan, Iran

3 Young Researcher and Elite Club, Borujerd Branch, Islamic Azad University, Borujerd, Iran

4 Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.

5 Department of Electrical Engineering, IT and Cybernetic, University of South-Eastern Norway, 3918 Porsgrunn, Norway

Abstract

The paper presents a new framework for planning strategies for virtual power plants (VPPs) and energy storage markets. By definition, a VPP is a series of small-scale generation units along with the covered load and network that is managed by a specific utility. Distributed generation technologies considered in this work are combined heat and power, gas production, and electrochemical storage units. Energy prices in the wholesale and retail markets and the required storage and period are specified parameters. The wholesale price of energy and the forecasted demand are uncertain. For mathematical modeling of the participation planning problem, a non-equilibrium model is used. To solve the optimization problem, the genetic algorithm has been adopted. Uncertainties include wholesale price and demand forecasts in the area covered by the VPP, where log-normal and normal probability distribution functions are used for their modeling, respectively. For implementing the uncertainties, the Monte-Carlo simulation was adopted. Simulation results show that the presented framework is a powerful tool for biddings of the VPPs in the market and their interaction with the consumer market with the capability of load interruption.

Graphical Abstract

A Virtual Power Station Strategy for Storage and Energy Markets Considering Load Response and Uncertainty of Market Price

Keywords