Optimal Dispatch of Integrated Energy System Considering Operational Risks in the Presence of Energy Storage

Yunhui SHI; Chuangxin GUO

doi:10.12096/j.2096-4528.pgt.19142

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Optimal Dispatch of Integrated Energy System Considering Operational Risks in the Presence of Energy Storage

Key Technologies for Ubiquitous Power Internet of Things and Integrated | 更新时间：2025-07-04

- Optimal Dispatch of Integrated Energy System Considering Operational Risks in the Presence of Energy Storage
- Power Generation Technology Vol. 41, Issue 1, Pages: 56-63(2020)
- 作者机构：
  
  浙江大学电气工程学院, 浙江省杭州市 310027
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(51877190)
- DOI：10.12096/j.2096-4528.pgt.19142
  CLC： TM715
- Received：21 September 2019，
  
  Published：29 February 2020
- 稿件说明：
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Yunhui SHI, Chuangxin GUO. Optimal Dispatch of Integrated Energy System Considering Operational Risks in the Presence of Energy Storage[J]. Power Generation Technology, 2020, 41(1): 56-63.
DOI：

Yunhui SHI, Chuangxin GUO. Optimal Dispatch of Integrated Energy System Considering Operational Risks in the Presence of Energy Storage[J]. Power Generation Technology, 2020, 41(1): 56-63. DOI： 10.12096/j.2096-4528.pgt.19142.

摘要

为解决综合能源系统（integrated energy system，IES）中供需双侧不确定因素对运行调度带来的风险问题，提出了一种考虑运行风险的含储能IES优化调度模型。在目标函数中，用设备调整费用、失负荷惩罚费用和弃风弃光惩罚费用来量化系统运行风险。在约束条件中，区分了电能和热能的时间尺度差异，并计及储能的时间耦合性，建立了储能多时段耦合约束。然后提出了一种基于Benders分解的算法进行求解。最后通过算例分析了置信水平、储能功率及容量对IES运行费用及运行风险的影响。

Abstract

In order to solve the risk problem brought by uncertainties of supply and demand in integrated energy system (IES)

an optimal dispatch model of IES with energy storage considering operational risk was proposed. In the objective function

the cost of equipment adjustment

penalty for loss of load and penalty for curtailment of wind and solar power was used to quantify the operational risk of the IES. In the constraints

the time-scale differences between electric energy and thermal energy were distinguished

and the multi-period coupling constraints of energy storage were established considering the time coupling of energy storage. Then an algorithm based on Benders decomposition was proposed to solve the problem. Finally

an example was given to analyze the influence of confidence level

energy storage power and capacity on IES operation cost and operational risk.

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