With the promulgation of relevant policies, virtual power plant market transactions are facing major adjustments, in order to promote the smooth entry of virtual power plants into market-oriented transactions and improve the economic benefits of virtual power plants, this paper proposes a virtual power plant market transaction model. The traditional virtual power plant resources are mathematically modeled, blockchain technology is introduced to build a decentralized trading framework, and fuzzy neural networks are combined to predict the power load of the virtual power plant. Then the decision-making model of virtual power plant participation in spot market trading is constructed by using two-stage stochastic planning theory with the goal of maximizing expected return. The results show that the prediction effect of the fuzzy logic-based virtual power plant market trading model is 2.925% higher than that of the traditional BP algorithm model, and its accuracy and stability are significantly improved. In addition, the distributed energy storage aggregated by the virtual power plant as well as the dynamic demand response rate is fast, the regulation is flexible, the short-time power throughput capability is strong, and it can accurately track the FM instructions. The cumulative FM capacity and FM mileage provided by the virtual power plant account for 84% and 99% of the total FM capacity demand in the system, respectively, making it highly competitive in the FM market. And under the premise of balancing riskiness and profitability, the bidding scheme of virtual power plant derived in this paper is more effective.
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