Taking the typical industrial users of Zhejiang Province as the research object

the potential for participating in the demand response of industrial cluster loads is analyzed

and a demand response model has been established. Considering the uncertainty of the aggregate participation in the electrical energy market and the peak adjustment assist service market

including the probability of winning bids

calling calls

calling probability and shortage possibilities

Bayesian neural network is used to predict

a bidding strategy model for aggregates is established to participate in the joint market

and the purchase of the park in the spot market in each period of time is obtained.Through the minimum cost of electricity purchase and maximum demand response income

the power purchase volume of the park in the spot market in each period is obtained. Important references for the formulation of industrial cluster load aggregates to participate in the power market can be provided

selecting the bidding time and capacity

and considering how to minimize the risk of power shortage and maximize the total profit.