陆宝奇, 蒋伟, 杨俊杰, 高崧峻. 基于云储能容量动态分配的微电网系统双层优化模型[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0498
引用本文: 陆宝奇, 蒋伟, 杨俊杰, 高崧峻. 基于云储能容量动态分配的微电网系统双层优化模型[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0498
LU Baoqi, JIANG Wei, YANG Junjie, GAO Songjun. Double-layer Optimization Model for Microgrid System Based on Dynamic Capacity Allocation of CES[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0498
Citation: LU Baoqi, JIANG Wei, YANG Junjie, GAO Songjun. Double-layer Optimization Model for Microgrid System Based on Dynamic Capacity Allocation of CES[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0498

基于云储能容量动态分配的微电网系统双层优化模型

Double-layer Optimization Model for Microgrid System Based on Dynamic Capacity Allocation of CES

  • 摘要: 储能系统(energy storage system,ESS)其本身所具有的可快速充放电能的特性可以解决可再生能源间歇性、不确定性及其就地消纳问题。但由于初期投资造价高、储能容量空置等原因,储能设备无法大规模使用。为了增加储能设备的利用率,减少储能容量空置率的问题,基于传统云储能,提出一种计及需求响应的云储能容量动态分配模型。首先,从云储能租赁服务的本质出发,提出云储能容量动态分配策略并建立模型;而后对接入云储能带有可再生能源的用户进行建模。为了考虑用户和云储能运营商之间的牵制,深入探究其耦合关系,建立双层优化模型。上层以云储能运营商盈利最大为目标函数;下层以用户日运行成本最低为目标函数。仿真结果表明,所提出的储能容量动态分配策略和模型可以增加储能设备的利用率,减少储能容量空置情况,还同时拥有良好的经济性。

     

    Abstract: The rapid charging and discharging capacities of energy storage system (ESS) can effectively address the issue of intermittent and uncertainty of renewable energy and its local consumption. The utilization of energy storage equipment on a large scale is hindered by the high initial investment cost and vacant energy storage capacity, however. In order to increase the utilization rate of energy storage equipment and reduce the vacancy rate of energy storage equipment, a dynamic allocation model of cloud energy storage capacity, which accounts for demand response, was proposed based on traditional cloud energy storage. First, in this paper we proposed a cloud energy storage capacity dynamic allocation strategy and established a model based on the essence of cloud energy storage leasing service. Then, the users accessing the cloud energy storage with renewable energy were modeled. To comprehensively examine the interconnections between users and cloud energy storage operators, as well as deeply explore their coupling relationship, a two-layer optimization model was established. The upper layer takes the maximum profitability of the cloud storage operator as the objective function, while the lower layer takes the lowest daily operating cost of the user as the objective function. The simulation results indicate that the proposed dynamic energy storage capacity allocation strategy and model can increase the utilization rate of energy storage devices, reduce the vacancy of energy storage capacity, and also exhibit a good economy.

     

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