Abstract

In recent years, because of the shortage of fossil fuels and their consequent price increase, along with the environmental pollution associated with these types of fuel, the use of renewable energy resources has increased considerably. Moreover, regarding the technical and economic benefits of the use of distributed energy resources (DERs), these resources play an important role in the electricity market. Virtual power plants (VPPs) are decentralized energy management systems that participate as independent units in the electricity market by collecting the capacity of distributed energy resources, including distributed generation units, storages, and interruptible loads. In this paper, the VPPs collect DERs and use them to participate in the power retail market and assist in meeting the forecasted demand of the distribution network. The main goal is optimal pricing of produced energy of VPPs for long-term Bi–level negotiations with the utility. To reach the goal, two different conditions are considered. In the first mode, there is no competition among VPPs over offering price to utility and cooperation in providing load. In this mode, the total benefit of VPPs is optimized, and they offer their prices to utilities based on energy market prices in upstream networks. In the second state, the competition among VPPs is modeled by using game theory. Then, the optimization is done separately for all VPPs, and the criterion for offering the price for each VPP is the energy market price in upstream networks and also the suggested prices of neighboring VPPs. In both modes, the utility, as the only owner and operator of the distribution network, evaluates the suggested energy price of VPPs with the benefit obtained from the dispatch of these power plants and decides on the amount and the time that it must dispatch from distributed generation units of these power plants. The results show that, by applying the proposed method in the competition mode, the profit of both utility and VPPs has enhanced.

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