区域电力系统中储能机组容量配置研究

耿志浩; 徐玉杰; 沈昊天; 周学志; 陈海生

doi:10.19799/j.cnki.2095-4239.2026.0216

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区域电力系统中储能机组容量配置研究

储能系统与工程 | 更新时间：2026-08-26

- 区域电力系统中储能机组容量配置研究
- Capacity configuration optimization for energy storage systems in regional power systems
- 储能科学与技术 2026年15卷第8期页码：3203-3218
- 作者机构：
  
  1.中国科学院工程热物理研究所，北京 100190
  2.中国科学院大学，北京 101408
  3.长时规模储能重点实验室（中国科学院），北京 100190
  4.压缩空气储能北京市重点实验室，北京 100190
  5.中科南京未来能源系统研究院，江苏南京 211135
- 作者简介：
  
  耿志浩（2000—），男，硕士研究生，主要研究方向为储能机组调度优化，E-mail：gengzhihao@iet.cn；
  徐玉杰，研究员，主要研究方向为压缩空气储能、储能与分布式系统等，E-mail：xuyujie@iet.cn。
- 基金信息：
  
  中国科学院与美国联邦科研机构合作项目(117GJHZ2023009MI);呼和浩特市基础研究和应用基础研究科技计划项目(2024-科技突围-高新-1)
- DOI：10.19799/j.cnki.2095-4239.2026.0216
  中图分类号： TM 732
- 收稿：2026-03-18，
  
  修回：2026-05-22，
  
  网络首发：2026-08-26，
  
  纸质出版：2026-08-28
- 稿件说明：
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耿志浩, 徐玉杰, 沈昊天, 等. 区域电力系统中储能机组容量配置研究[J]. 储能科学与技术, 2026, 15(8): 3203-3218.

GENG Zhihao, XU Yujie, SHEN Haotian, et al. Capacity configuration optimization for energy storage systems in regional power systems[J]. Energy Storage Science and Technology, 2026, 15(8): 3203-3218.
耿志浩, 徐玉杰, 沈昊天, 等. 区域电力系统中储能机组容量配置研究[J]. 储能科学与技术, 2026, 15(8): 3203-3218. DOI： 10.19799/j.cnki.2095-4239.2026.0216.

GENG Zhihao, XU Yujie, SHEN Haotian, et al. Capacity configuration optimization for energy storage systems in regional power systems[J]. Energy Storage Science and Technology, 2026, 15(8): 3203-3218. DOI： 10.19799/j.cnki.2095-4239.2026.0216.

摘要

储能是实现可再生能源大规模消纳和构建新型电力系统的关键支撑技术，但储能技术在电力系统中的容量配置及调度运行仍是目前要解决的关键问题。因此，本研究首先构建了以系统总经济成本最小为优化目标的储能双层容量配置模型，并建立了年时间尺度优化调度模型；其次在不同可再生能源渗透率场景下，开展储能机组的最优容量配置；最后开展了电力系统年时段尺度的优化调度。研究结果表明：随着可再生能源渗透率从25.3%提高到57.6%，抽水蓄能、压缩空气储能和锂电池储能的最优配置容量均显著提升；锂电池储能占比由47.0%下降到28.6%，电力系统更加依赖于长时储能的能量搬移与削峰填谷能力；储能机组优化调度全年情景下，抽水蓄能机组额定功率运行小时数更多，运行时段也更加集中，而压缩空气储能机组变工况运行情况更加明显。该研究为未来高比例可再生能源电力系统的储能容量优化配置与经济运行调度提供了参考。

Abstract

Energy storage is a key enabling technology for large-scale renewable energy integration and new-type power system development. However

the optimal sizing and operational scheduling of energy storage units in power systems remain critical challenges. This study establishes a two-layer energy storage capacity configuration model to minimize total system economic cost and develops an annual-scale optimal dispatch model. Subsequently

optimal storage capacities are determined under different renewable penetration scenarios

followed by annual-scale power system dispatch. The results indicate that as renewable penetration increases from 25.3% to 57.6%

the optimal capacities of pumped hydro storage

compressed air energy storage

and lithium-ion batteries all increase considerably. The lithium-ion storage share falls from 47.0% to 28.6%

indicating a growing reliance on long-duration storage for energy shifting and peak-valley load balancing. Throughout the year

pumped hydro storage units operate closer to their rated capacity for more hours and during more concentrated periods

whereas compressed air energy storage units exhibit more variable operational patterns. This study provides a reference for optimal energy storage capacity planning and economically efficient dispatch in future high-renewable power systems.

关键词

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references

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