计及惯量响应与一次调频参数优化的新能源基地构网型储能规划

doi:10.11930/j.issn.1004-9649.202411092

中国电力 ›› 2025, Vol. 58 ›› Issue (7): 147-161.DOI: 10.11930/j.issn.1004-9649.202411092

计及惯量响应与一次调频参数优化的新能源基地构网型储能规划

谭玲玲¹(), 张文龙¹, 康志豪¹, 叶平峰²(), 高业豪³(), 张玉敏³

1. 山东电力工程咨询院有限公司，山东济南　250013
2. 山东科技大学储能技术学院，山东青岛　266590
3. 山东科技大学电气与自动化工程学院，山东青岛　266590

收稿日期:2024-11-28 发布日期:2025-07-30 出版日期:2025-07-28
作者简介:
谭玲玲（1979），女，本科，高级工程师（教授级），从事电力系统及其自动化技术研究，E-mail：tanlingling@sdepci.com
叶平峰（1988），男，博士，通信作者，讲师，硕士生导师，从事电力系统运行与控制技术研究，E-mail：ypfinput@163.com
高业豪（2001），男，硕士研究生，从事电力系统运行与控制技术研究，E-mail：202383080151@sdust.edu.cn
基金资助:
国家自然科学基金青年基金资助项目（52107111）。

Grid-Forming Storage Planning for Renewable Energy Bases Considering the Co-optimization of Inertia Response and Primary Frequency Regulation Parameters

TAN Lingling¹(), ZHANG Wenlong¹, KANG Zhihao¹, YE Pingfeng²(), GAO Yehao³(), ZHANG Yumin³

1. Shandong Electric Power Engineering Consulting Institute Co., Ltd., Jinan 250013, China
2. College of Energy Storage Technology, Shandong University of Science and Technology, Qingdao 266590, China
3. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China

Received:2024-11-28 Online:2025-07-30 Published:2025-07-28
Supported by:
This work is supported by National Natural Science Foundation of China (No.52107111).

摘要/Abstract

摘要：

偏远新能源基地缺乏常规电源支撑，频率安全问题突出，配置构网型储能可有效提升其频率稳定性。但固定的频率支撑参数无法充分发挥构网型储能的频率支撑能力，导致维持频率稳定所需的配置容量增加。为此，以新能源基地频率安全为基础，提出了计及惯量响应与一次调频参数优化的构网型储能双层优化配置方法。上层以经济性最优为目标，考虑新能源直流外送典型场景下的运行约束，得出构网型储能配置方案；下层针对预想功率扰动，以多频率安全指标最优为目标，优化储能惯量响应与一次调频参数，在充分发挥构网型储能频率支撑能力条件下校验配置方案的频率稳定性。最后，以西北地区的历史数据为典型场景，验证了所提优化配置方法的有效性。

关键词: 新能源基地, 构网型储能, 频率安全, 频率响应, 虚拟惯量

Abstract:

Remote renewable energy bases often lack conventional power sources for support, leading to prominent frequency stability issues. The deployment of grid-forming energy storage systems can effectively enhance frequency stability. However, fixed frequency support parameter settings fail to fully utilize the frequency regulation capability of grid-forming energy storage, resulting in increased configuration requirements to maintain frequency stability. To address this, a bi-level optimization configuration method for grid-forming energy storage is proposed, based on frequency security in renewable energy bases, which considers the optimization of inertia response and primary frequency regulation parameters. The upper-level optimization aims for economic optimality, deriving the grid-forming energy storage configuration scheme while accounting for operational constraints under typical scenarios of renewable energy HVDC transmission. The lower-level optimization targets multiple frequency security metrics under anticipated power disturbances, optimizing the inertia response and primary frequency regulation parameters of the energy storage system. This ensures the frequency stability of the configuration scheme while maximizing the frequency support capability of grid-forming energy storage. Finally, the effectiveness of the proposed optimization method is validated using historical data from a typical scenario in Northwest China.

Key words: renewable energy base, grid-forming energy storage, frequency security, frequency response, virtual inertia

谭玲玲, 张文龙, 康志豪, 叶平峰, 高业豪, 张玉敏. 计及惯量响应与一次调频参数优化的新能源基地构网型储能规划[J]. 中国电力, 2025, 58(7): 147-161.

TAN Lingling, ZHANG Wenlong, KANG Zhihao, YE Pingfeng, GAO Yehao, ZHANG Yumin. Grid-Forming Storage Planning for Renewable Energy Bases Considering the Co-optimization of Inertia Response and Primary Frequency Regulation Parameters[J]. Electric Power, 2025, 58(7): 147-161.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202411092

https://www.electricpower.com.cn/CN/Y2025/V58/I7/147

图/表 18

图 1 典型直流外送结构

Fig.1 The typical DC outgoing delivery

图 2 新能源基地惯量与频率响应过程

Fig.2 Inertia and frequency response process of new energy base

图 3 新能源基地频率响应控制模型

Fig.3 Frequency response control model of new energy base

图 4 新能源基地储能优化配置与频率响应模型求解流程

Fig.4 Model solution flow of energy storage optimal configuration and frequency response of new energy base

表 1 考虑惯量支撑模拟运行优化的相关控制参数

Table 1 The relevant control parameters of the simulation operation optimization considering inertia support

参数名称		数值
基于惯量支撑的一阶惯性时间常数/s		0.5
基于一次调频的一阶惯性时间常数/s		5.5
风机一次调频系数		20
阻尼系数		100
最大频率偏差/Hz		0.5
稳态频率偏差/Hz		0.2
系统允许的最大频率变化率/(Hz·s^–1)		1
调频死区/Hz		0.03
跟网型风电场延时/s		0.1
基准频率/Hz		50

图 5 风电出力曲线

Fig.5 Wind power output curve

图 6 光伏出力曲线

Fig.6 PV output curve

图 7 新能源基地惯量需求

Fig.7 Inertia demand for new energy bases

表 2 储能配置规划结果

Table 2 Energy storage configuration planning results

参数		数值
额定功率/MW		1190.6
规划容量/(MW·h)		2335.5
日均投资成本/元		155071.9
日均维护成本/元		23812.2
日均运行成本/元		475421.8

表 3 新能源基地典型场景运行成本结果分析

Table 3 Analysis of the operating cost results of typical scenarios of new energy bases 单位：万元

典型场景	弃风弃光成本	风电备用成本	弱交流系统支撑功率成本	总运行成本
1	36.0670	32.957	7.099	76.125
2	22.5670	33.781	8.096	65.255
3	1.9058	44.845	7.915	47.542
4	0	42.566	16.967	59.534

图 8 新能源基地运行曲线

Fig.8 The operation curve of the new energy base

图 9 新能源基地频率曲线

Fig.9 Frequency curve of new energy base

表 4 最小时段数对储能配置的影响

Table 4 The impact of the minimum number of periods on the energy storage configuration

最小时段数/h	爬坡能力/ (MW·h^–1)	储能配置
最小时段数/h	爬坡能力/ (MW·h^–1)	额定容量/(MW·h)	额定功率/MW
6	1200	2660.1	1163.6
4		1521.7	672.3
2		1516.5	669.5

表 5 爬坡能力对储能配置的影响

Table 5 The impact of ramp-up capacity on energy storage configuration

最小时段数/h	爬坡能力/ (MW·h^–1)	储能配置
最小时段数/h	爬坡能力/ (MW·h^–1)	额定容量/(MW·h)	额定功率/MW
4	1200	1521.7	672.3
	1500	1467.9	651.5
	1800	741.0	634.1

图 10 新能源基地频率曲线

Fig.10 Frequency curve of new energy base

图 11 新能源基地频率曲线

Fig.11 Frequency curve of new energy base

表 6 参数优化对储能配置的影响

Table 6 The impact of parameter optimization on energy storage configuration

方案	容量/(MW·h)	功率/MW
1	2432.4	1237.9
2	2335.5	1190.6

图 12 适应度曲线

Fig.12 Fitness Curve

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计及惯量响应与一次调频参数优化的新能源基地构网型储能规划

Grid-Forming Storage Planning for Renewable Energy Bases Considering the Co-optimization of Inertia Response and Primary Frequency Regulation Parameters

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计及惯量响应与一次调频参数优化的新能源基地构网型储能规划

Grid-Forming Storage Planning for Renewable Energy Bases Considering the Co-optimization of Inertia Response and Primary Frequency Regulation Parameters

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