Virtual Bidding Strategy in Spot Electricity Market Based on Carbon Neutrality

Power financial market is an important part of electricity market. In the electricity market, the large gap between real-time price and day-ahead price is usually regarded as the performance of low market efficiency. Therefore, in order to achieve the best social benefits, the optimal bid of virtual traders is particularly significant. However, due to the uncertainty of demand, supply and operating conditions, the day-ahead and real-time wholesale prices are random. To obtain the optimal trading strategy, virtual traders need to use all the historical information to update their bidding strategies. Aiming to the problem of low market efficiency caused by the obvious gap between day-ahead and real-time prices in the power financial market, this paper comes up with a bidding model to deal with the difference and to arbitrage, so as to make the two prices converge and improve the market vitality. In the processing of the model, the goal of this paper is taking the bidders maximize their benefit, regards the solution of the model as solving the classical knapsack problem, and uses dynamic programming to solve the model. Finally, the predicted benefit is evaluated by sharp ratio to verify the feasibility of the algorithm.