Abstract
As the proportion of electric vehicles and distributed power sources connected to the power grid continues to increase, virtual power plants provide new ideas for effectively solving electric vehicles and distributed power sources connected to the grid. Considering that there are obvious uncertainties in the number of dispatchable electric vehicles and the output of distributed power sources, this paper focuses on the multi-objective interval optimization problem of virtual power plants considering the uncertainty of source load. Based on the analysis of the virtual power plant architecture, aiming at the uncertainty of the source load, a multi-objective interval optimization model of the virtual power plant was established using the interval number theory; in order to verify the validity of the established model, a virtual power plant in a certain area was selected as an example for analysis. The results show that the uncertainty of distributed power sources and electric vehicles can be better avoided in the interval optimization process, and the proposed scheme has strong robustness.
Highlights
In recent years, in response to energy crisis and environmental pollution, China has vigorously developed distributed new energy sources and promoted electric vehicles
Due to the strong advantages of distributed new energy and electric vehicles The randomness and volatility of the power grid will have a certain impact on the operation of the power grid [1,2,3,4,5]
Literature [6] constructed a virtual power plant economic optimization scheduling model with electric vehicles, used particle swarm optimization to optimize the output of each component, and analyzed the impact of electric vehicle penetration on the economics of the virtual power plant and the output of each unit
Summary
In response to energy crisis and environmental pollution, China has vigorously developed distributed new energy sources and promoted electric vehicles. Literature [6] constructed a virtual power plant economic optimization scheduling model with electric vehicles, used particle swarm optimization to optimize the output of each component, and analyzed the impact of electric vehicle penetration on the economics of the virtual power plant and the output of each unit. Literature [7] constructed a virtual power plant stochastic scheduling optimization model considering the uncertainty of wind and solar, and analyzed the multi-faceted benefits of. Briefly describe the structure of the virtual power plant and analyze the charging demand for electric vehicles; with the goal of maximizing economic benefits, optimal user comfort, and minimal carbon emissions, combined with interval number theory, establish a virtual power plant interval optimization model; pass The calculation example analysis verifies the rationality of the proposed model, and proposes a virtual power plant optimal scheduling scheme
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