An Energy Optimization Management Model for Electric Vehicle Clusters Adapting to Multiple Scenarios

At present, research on regulation strategies for electric vehicles is mainly based on the interests of the vehicle and power grid. On the power grid side, factors such as load variance, load peak valley difference, and grid overload are generally considered, while on the user side, factors such as user charging costs and regulatory profits are considered. However, the consideration of load fluctuations on the power grid side is generally based on load variance as the calculation indicator
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Although the strategy optimization goal can be achieved, there is still room for further improvement. Moreover, the universality research at the user level only considers the charging cost of users, or only considers single factors such as subsidy benefits, which cannot balance the multiple benefits of users. Therefore, this article proposes a load fluctuation rate index that jointly considers the standard deviation and mean of the load as the upper optimization objective; And propose a lower level optimization goal that considers the comprehensive satisfaction of user charging duration and charging cost. This optimizes and solves the energy regulation strategy of cluster electric vehicles.