Simulation Strategy of Bidding Behavior for Electricity Retailers in Direct Transactions

In the medium and long-term electricity direct transactions, electricity retailers account for most of the demand-side market. Study the bidding behavior of electricity retailers is of great significance for evaluation of market model and trading rules. The article analyzes the main factors that affect the bidding behavior of electricity sales companies from three aspects: the market environment, market rules, and the electricity supplier’s own factors. Based on this, comprehensive consideration of the asset background, operating objectives, retail contracts and other factors of the power retail company, an agency bidding model was established, which covering three types of typical power retail companies, including expansion, stability, conservativeness and price acceptance. And the RE-learning algorithm is used to optimize the bidding strategy. Finally, the bidding model is verified by a simulation example.