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With the rapid development of renewable energy and the continuous growth of new loads, VPP has become an important form of smart grid and energy internet due to its flexible and effective management of distributed energy. During the operation of Virtual power plant, there is a game relationship between the system operator and VPP, and they are in a non-complete information environment. However, most of the current game optimization modeling is under the condition of complete information, and the game model based on complete information cannot solve this problem. This article focuses on the VPP cluster trading problem based on non-complete information game theory, constructs a Bayesian game model for multiple VPPs with multiple subjects under the master-slave game framework by introducing the Bayesian concept to optimize the cluster transactions within VPPs, and verifies the effectiveness of the model through simulation experiments. The experimental results show that the multi-VPP multi-subject Bayesian game model established in the study can guarantee the privacy of each subject and effectively reduce PAR, thus ensuring the security and stability of the VPP network and reducing cost expenditures, which has practicality in actual VPP cluster transactions. [ABSTRACT FROM AUTHOR]

Studying the grid integration of renewable energy power generation is crucial for achieving the goal of carbon neutrality since it may have a significant influence on the secure and reliable functioning of the power system. In order to solve the problem of deviation impact caused by renewable energy fluctuations and the optimal scheduling of VPP (Virtual Power Plant), the study divides the internal aggregation unit of the virtual power plant into two parts to model. One part is the source equipment, including wind power generation equipment, gas turbine, gas boiler and waste heat boiler. And the other part is the generalized Energy storage, including electric vehicles, air conditioners and alternative response loads. Ultimately, a generalized energy storage-based virtual power plant operation optimization model is developed under multi-market coordination of electricity-gas-heat-carbon. According to the study's findings, adding more power-to-gas technology boosts revenue in the carbon trading market by 25.24 percent. The energy market's revenue is equal to that in the absence of a carbon trading market, and the income of the natural gas market increases by $ 32.96. The income of the carbon trading market is $ 181.51, and the final operating cost is reduced by $ 180.80, a drop of 7.81%. To sum up, the suggested approach may more effectively achieve the best distribution of different energy sources, increase the dependability of VPP operation, and make it more low-carbon. [ABSTRACT FROM AUTHOR]