Affiliations: [a] School of Information Engineering, Nanchang University, Nanchang, Jiangxi, China | [b] Beijing Key Laboratory of Demand Side Multi-Energy Carriers Optimization and Interaction Technique, China Electric Power Research Institute, Beijing, China | [c] State Grid Beijing Electric Power Company, Beijing, China
Correspondence:
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Corresponding author: Xuan Wen, School of Information Engineering, Nanchang University, Nanchang 330031, China. E-mail: [email protected].
Abstract: 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.
Keywords: Virtual power plant, cogeneration of electricity, heat and gas, generalized energy storage, column constraint generation, low carbon, dispatch optimization
