A proactive strategy for virtual power plants including multiple private owners equipped with energy storages

Abstract

This paper presents a novel framework for the optimal operation strategy of a virtual power plant (VPP) comprises a set of various stakeholders such as renewable energy sources, distributed energy resources with private owners, and flexible loads in day-ahead and real-time energy markets. In order to model the strategic behavior of private owners within the VPP geographic location, a proactive stochastic bi-level model is developed, where the upper level assigns to minimize expected operation cost of the technical VPP and the lower level associates with maximizing the private owner's profits. Note that, the uncertainty set encompasses the real-time energy market price as well as renewables power production. Afterward, the proposed bi-level model is converted to a mixed-integer linear programming problem through Karush–Kuhn–Tucker optimality conditions along with strong duality theory. Moreover, the impacts of implementation of three different pricing schemes including fix pricing, time of use, and real-time pricing on the market trading strategy of VPP and also its interactions with private owners is investigated through comparative case studies. The obtained results demonstrate that the proposed approach could allow both VPP aggregator and private owners to take the advantages of the market conditions.