考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法

doi:10.11930/j.issn.1004-9649.202505077

中国电力 ›› 2026, Vol. 59 ›› Issue (1): 33-43.DOI: 10.11930/j.issn.1004-9649.202505077

• 考虑分布式虚拟储能聚合的综合能源系统规划、运行和交易的关键技术 • 上一篇下一篇

考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法

王辉东¹(), 倪琳娜²(), 芦鹏飞¹(), 程颖²(), 吴英俊³()

1. 国网浙江省电力有限公司，浙江杭州　310016
2. 国网浙江省电力有限公司营销服务中心，浙江杭州　310016
3. 河海大学电气与动力工程学院，江苏南京　211100

收稿日期:2025-05-27 修回日期:2025-12-28 发布日期:2026-01-13 出版日期:2026-01-28
作者简介:
王辉东（1974），男，硕士，高级工程师，从事电力负荷管理研究，E-mail：huidongwang@163.com
倪琳娜（1985），女，博士，高级工程师，从事电力负荷管理研究，E-mail：nilinna918@qq.com
芦鹏飞（1993），男，硕士，高级工程师，从事电力负荷管理研究，E-mail：845293350@qq.com
程颖（1987），女，硕士，高级工程师，从事电力负荷管理研究，E-mail：chengying@qq.com
吴英俊（1985），男，通信作者，副教授，从事电力需求侧运行分析与优化研究，E-mail：yingjunwu@hotmail.com
基金资助:
国网浙江省电力有限公司科技项目（B311YF24000W）。

Multi index fusion reliability evaluation method for virtual power plants considering the dynamic characteristics of energy storage

WANG Huidong¹(), NI Linna²(), LU Pengfei¹(), CHENG Ying²(), WU Yingjun³()

1. State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310016, China
2. State Grid Zhejiang Electric Power Co., Ltd., Marketing Service Center, Hangzhou 310016, China
3. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China

Received:2025-05-27 Revised:2025-12-28 Online:2026-01-13 Published:2026-01-28
Supported by:
This work is supported by Science and Technology Project of State Grid Zhejiang Electric Power Co., Ltd. (No.B311YF24000W).

摘要/Abstract

摘要：

虚拟电厂（virtual power plant，VPP）作为聚合“源-储-荷”多元资源的核心枢纽，其可靠性评估对电力系统稳定运行与可再生能源消纳至关重要。当前评估方法存在两点局限：1）采用静态储能模型，难以反映设备动态特性；2）评估指标无法量化供电过程中的功率输出稳定性。为此，提出一种考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法。首先，基于储能设备在充放电过程中的容量衰减与效率退化特性，构建动态储能模型；其次，整合风电、光伏、可调负荷及电网交易等多元能源，构建体现“源-储-荷”协同运行的虚拟电厂模型；最后，围绕供电稳定性与可再生能源消纳效率，提出平均输出功率稳定性（mean VPP export，MVPPE）和可再生能源未利用量（expected renewable energy not used，ERENU）指标，融合传统电力不足概率、期望缺供电量，建立考虑储能动态特性的虚拟电厂可靠性评估体系。仿真结果表明，该方法较传统静态储能模型可使MVPPE提升14.5%、ERENU降低88.7%，能更真实反映虚拟电厂的可靠性水平，为其规划、运行与优化提供科学依据。

关键词: 虚拟电厂, 动态储能, 可靠性评估

Abstract:

As a core hub for aggregating multi-source "generation-storage-load" resources, the reliability assessment of Virtual Power Plants (VPPs) is crucial for the stable operation of power systems and the absorption of renewable energy. Current assessment methods have two limitations: first, they adopt static energy storage models, which struggle to reflect the dynamic characteristics of devices; second, the evaluation indicators fail to quantify the power output stability during the power supply process. To address this, a multi-indicator integrated reliability assessment method for virtual power plants considering the dynamic characteristics of energy storage is proposed. Firstly, a dynamic energy storage model is constructed based on the capacity degradation and efficiency deterioration characteristics of energy storage devices during charging and discharging processes. Secondly, multiple energy sources such as wind power, photovoltaic power, adjustable loads, and grid transactions are integrated to build a virtual power plant model that reflects the collaborative operation of "generation-storage-load". Finally, focusing on power supply stability and renewable energy absorption efficiency, two indicators—Mean VPP Export Power Stability (MVPPE) and Expected Renewable Energy Not Used (ERENU)—are proposed. Combined with traditional indicators including Loss of Load Probability (LOLP) and Expected Energy Not Supplied (EENS), a reliability assessment system for virtual power plants considering the dynamic characteristics of energy storage is established. Simulation results show that compared with the traditional static energy storage model, this method increases MVPPE by 14.5% and reduces ERENU by 88.7%, which can more truly reflect the reliability level of VPPs and provide a scientific basis for their planning, operation, and optimization.

Key words: virtual power plant, dynamic energy storage, reliability assessment

王辉东, 倪琳娜, 芦鹏飞, 程颖, 吴英俊. 考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法[J]. 中国电力, 2026, 59(1): 33-43.

WANG Huidong, NI Linna, LU Pengfei, CHENG Ying, WU Yingjun. Multi index fusion reliability evaluation method for virtual power plants considering the dynamic characteristics of energy storage[J]. Electric Power, 2026, 59(1): 33-43.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202505077

https://www.electricpower.com.cn/CN/Y2026/V59/I1/33

图/表 11

图 1 虚拟电厂的构成

Fig.1 Composition of Virtual Power Plant

图 2 风速、辐照度及负荷数据

Fig.2 Wind speed, irradiance and load data

图 3 不同虚拟电厂模型下的调度成本

Fig.3 Scheduling costs under different virtual power plant models

图 4 不同虚拟电厂模型下的调度结果对比

Fig.4 Comparison of indicators under different virtual power plant models

表 1 3种模型可靠性评估的结果

Table 1 Results of reliability evaluation for three models 单位：kW·h

指标	δ_MVPPE	δ_ERENU	δ_LOLP	δ_EENS
方案1	486.250	1 677.860	0.125	670.250
方案2	570.280	113.530	0	0
方案3	556.670	190.110	0	0

图 5 储能容量衰减过程

Fig.5 Energy storage capacity decay process

图 6 储能设备充放电效率随循环次数的变化过程

Fig.6 The variation process of charging and discharging efficiency of energy storage equipment with the number of cycles

表 2 不同循环次数下的虚拟电厂评估数据

Table 2 Evaluation data of virtual power plants under different cycle times

循环次数	成本/元	δ_MVPPE/(kW·h)	δ_ERENU/(kW·h)
1000	9 500.91	569.95	123.48
1500	9 575.29	557.54	128.96
2000	9 825.94	557.08	166.60
2500	10 141.32	556.11	189.01
3000	10 214.94	552.77	191.33
3500	10 244.81	552.37	231.04
4000	10 268.40	549.29	243.10
4500	10 497.04	548.02	288.76
5000	10 731.71	546.48	288.89
5500	10 755.15	545.82	312.01

图 7 不同循环次数对应的储能状态变化

Fig.7 Changes in energy storage state corresponding to different cycle times

图 8 不同模型下的可靠性评估结果

Fig.8 Reliability evaluation results under different models

图 9 储能衰减系数灵敏度分析

Fig.9 Sensitivity analysis of energy storage attenuation coefficient

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考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法

Multi index fusion reliability evaluation method for virtual power plants considering the dynamic characteristics of energy storage

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考虑储能动态特性的虚拟电厂多指标融合可靠性评估方法

Multi index fusion reliability evaluation method for virtual power plants considering the dynamic characteristics of energy storage

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