基于分布鲁棒优化的广义共享储能容量配置方法

Capacity Allocation Method for Generalized Shared Energy Storage Based on Distributionally Robust Optimization

共享储能通过储能资源的复用,能有效应对高成本和利用率低的难题。迅速发展的需求侧资源在共享储能中具有潜在应用,但其不确定性问题亟待解决。文中引入了电动汽车和温控负荷的虚拟储能模型,结合实体储能,建立了考虑不确定性的广义共享储能模型和相应的优化算法,以确定实体储能的最佳容量配置。共享储能运营商根据用户需求,实现多类型储能的优化配置,并设计虚拟储能持有者的满意度补偿,以保障其用户体验和经济利益。此外,采用Wasserstein距离描述电动汽车和温控负荷的不确定性,并结合基于风险价值的分布鲁棒机会约束算法进行求解。算例结果表明,采用广义共享储能模型和分布鲁棒机会优化算法,能够充分考虑不确定性,有效降低用户的能源消费成本和运营商的储能配置成本。

Shared energy storage addresses the challenges of high cost and low utilization through the reuse of energy storage resources.Furthermore,rapidly developing demand-side resources have the potential to be applied in the shared energy storage,but the issue of their uncertainty requires urgent resolution.A virtual energy storage model for electric vehicles and thermal control loads is introduced,integrated with the physical energy storage,this model is employed to construct a comprehensive shared energy storage model that takes uncertainties into consideration,along with the corresponding optimization algorithms to determine the optimal capacity configuration of the physical energy storage.Shared energy storage operators optimize the configuration of multiple types of energy storages based on user demands and design the satisfaction compensation for virtual energy storage holders to safeguard their user experience and economic interests.Additionally,the Wasserstein distance is used to characterize the uncertainty associated with electric vehicles and temperature-controlled loads,in conjunction with the utilization of a risk-valuebased distributionally robust chance-constrained algorithm for optimization.The results of the case study demonstrate that the utilization of the generalized shared energy storage model and the distributionally robust optimization algorithm allow for a comprehensive consideration of uncertainty,leading to a substantial reduction in energy consumption costs for users and energy storage configuration costs for operators.