Optimal Bidding Strategy of Load Aggregators for the Auxiliary Service Market of Peak Shaving and Valley Filling

China’s existing methods of regulating and adjusting resources are difficult to achieve optimal allocation of resources. Load aggregators can participate in market operations by integrating dispersed adjustable resources to increase the flexibility of resource scheduling. In order to encourage load aggregators to participate in peak-shaving and valley-filling services in the power auxiliary service market, this paper develops an optimal bidding strategy model to optimize the bidding curve of load aggregators. Since there is a deviation between the actual daily electricity consumption in the market and the bid amount in the day-ahead market, the power deviation is additionally considered by this paper. Due to the bidding curves of other entities in the market are unknown, this paper proposes a random optimization method using Monte Carlo simulation. The results show that under different market environments, load aggregators can benefit by optimizing their bidding curves, and a loose market environment can stimulate their enthusiasm for participation.