Joint bidding game model for multiple offshore wind farms based on monthly electricity data adaptive pseudo augmentation
In order to mitigate the electricity risk faced by offshore wind power when participating in the medium and long-term electricity market due to its stochastic nature,a joint bidding game model for multi-ple offshore wind farms based on monthly electricity data adaptive pseudo augmentation is proposed.Considering the impact of spatial correlation of monthly electricity for multiple offshore wind farms on joint bidding strategy,the generative adversarial network with adaptive pseudo augmentation mechanism is used to simulate the monthly electricity prediction error scenario of multiple offshore wind farms,which enhances the diversity of small sample and reduce the overfitting phenomenon of generative adversarial network.Ai-ming at the problem that the coalition revenue function does not meet the superadditivity caused by the consideration of spatial correlation and cooperation cost,the concept of optimal coalition structure is intro-duced to obtain the coalition division mode with the maximum total revenue,and the concepts of parallel processing and effective optimal coalition structure are used to improve the solving algorithm,which im-proves the execution efficiency.Considering that the Shapley value method cannot reflect the true contribu-tion and importance of members,the A-T solution in graph cooperative game is introduced to improve the allocation scheme when allocating coalition benefit,which avoids the problem that the coalition benefit not satisfying the superadditivity participates in the allocation.The superiority of the proposed model and me-thod and the rationality of the benefit distribution scheme are verified by the example simulative results.
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