The Optimal Operation and Revenue Allocation Method of Virtual Power Plant Considering Carbon Trading

As the capability of a Virtual power plant (VPP) to aggregate large amounts of distributed energy resources (DER) increases. There is a corresponding increase in the quest by researchers to optimize and improve the system's operation, thereby increasing its overall efficiency. This study conducts an economic operation of VPP in the spot and carbon trading markets, considering the uncertainties in renewable power sources such as wind and photovoltaic (PV) sources, carbon emission rights, and electricity trading. The proposed bidding strategy of the VPP is based on the conditional value at risk (CVAR) framework. It uses a three-stage stochastic optimization model with respect to carbon emission and electricity trading in an ancillary market. The first stage is the day-ahead market trading, the second is the adjustment market trading, and the last is the balancing market trading. The GAMS optimization solver has been employed to solve the proposed bidding strategy model. Finally, we analyze the effectiveness of the proposed bidding strategy on a VPP considering carbon-electricity integration market trading.