Abstract:

In the context of new power system, the large-scale integration of distributed energy resources has led to the emergence of distributed energy resource aggregators as new entities in the electricity market. However, market transactions are subject to various uncertainties, such as clearing prices and the output of wind and solar power sources. Therefore, it is necessary to propose an electricity market trading model for distributed resource aggregators that considers risk management, providing trading strategies that balance risk and return for aggregators. Firstly, the market organizational structure was analyzed. Secondly, the risk losses caused by uncertainties were quantified using Conditional Value at Risk (CVaR). A bidding model that considers the uncertainty of clearing prices and a scheduling decision-making model that accounts for the uncertainty of wind and solar power output were proposed, forming a trading strategy for distributed energy resource aggregators to participate in the energy-reserve auxiliary services market. Thirdly, a joint clearing model for the energy-reserve auxiliary services market was constructed. Finally, using actual operational data from the energy and reserve auxiliary services market in a certain region as an example, the proposed electricity market trading model for distributed energy resource aggregators was applied to the bidding and clearing processes of that market. The results show that the proposed method can guide distributed energy resource aggregators in making rational quantity bids and offers, thereby increasing their market participation profits.

Key words: risk management, uncertainty, distributed energy resource aggregator, energy market, reserve auxiliary services market