多能互补发电系统电/热储能容量双层优化配置方法

doi:10.11930/j.issn.1004-9649.202403093

中国电力 ›› 2025, Vol. 58 ›› Issue (3): 55-64.DOI: 10.11930/j.issn.1004-9649.202403093

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多能互补发电系统电/热储能容量双层优化配置方法

李湃¹(), 卢慧¹(), 李驰¹(), 杜洪博²

1. 可再生能源并网全国重点实验室（中国电力科学研究院有限公司），北京　100192
2. 国科优化（北京）科技有限公司，北京　100089

收稿日期:2024-03-22 出版日期:2025-03-28 发布日期:2025-03-26
作者简介:
李湃（1988），男，通信作者，博士，高级工程师（教授级），从事新能源调度运行技术研究，E-mail：lipai@epri.sgcc.com.cn
卢慧（1993），女，博士，工程师，从事新能源调度运行技术研究，E-mail：luhui@epri.sgcc.com.cn
李驰（1990），男，高级工程师，从事新能源调度运行技术研究，E-mail：lichi@epri.sgcc.com.cn
基金资助:
中国电力科学研究院有限公司研究开发项目（融合深度学习与最优化决策算法的灵活资源优化规划方法研究，NY83-21-006）。

Bi-level Capacity Optimization for Battery/Thermal Energy Storage System in Multi-energy Complementary Power Generation System

Pai LI¹(), Hui LU¹(), Chi LI¹(), Hongbo DU²

1. State Key Laboratory of Renewable Energy Grid-Integration (China Electric Power Research Institute), Beijing 100192, China
2. Guo Ke Optimization Technology Ltd., Beijing 100089, China

Received:2024-03-22 Online:2025-03-28 Published:2025-03-26
Supported by:
This work is supported by Research and Development Project of China Electric Power Research Institute (Research on Flexible Resource Optimization Planning Method Integrating Deep Learning and Optimization Decision Algorithm, No.NY83-21-006).

摘要/Abstract

摘要：

多能互补发电系统能够充分发挥风光热储等资源的互补优势，提高能源利用效率，对构建低碳新型电力系统具有重要意义。协调配置多能互补发电系统中电/热储能容量有助于降低系统投资成本，提升新能源利用率和供电支撑能力。针对含风电/光伏/光热/储能的多能互补发电系统开展研究，建立了多能互补发电系统电/热储能容量双层协调优化模型。上层模型以系统年净收益最大为优化目标，优化电/热储能的容量；下层优化模型以系统供电缺额最小为目标，考虑系统可靠供电能力、风电/光伏/光热/储能运行、新能源利用率等约束，优化系统的发电运行状态。为求解双层协调优化模型，提出了模型非线性约束的线性化方法，以及基于值函数和分支定界相结合的启发式算法，能够实现模型的高效快速求解。基于典型的多能互补发电系统算例开展仿真测试，结果验证了所提双层优化配置模型及算法的有效性。

关键词: 多能互补发电系统, 电/热储能, 容量配置, 双层模型, 启发式算法

Abstract:

Multi-energy complementary power generation system can fully utilize the complementary advantages of wind-PV-thermal-battery sources and improve energy efficiency. It is of great significance for the construction of low-carbon new power system. Capacity coordinated optimization of battery/thermal energy storage in multi-energy complementary power generation system can reduce the investment costs of power system, and improve the utilization rate of renewable energy and continuous power supply. In this paper, multi-energy complementary power generation system with wind-PV-thermal-battery sources is studied, and a bi-level capacity coordinated optimization model of this system is established. The upper-level model optimizes the capacity of battery/thermal energy storage with the maximum annual net income of this system. The lower-level model optimizes the power shortage in this system, and optimize the generation operation status of this system by considering the constraints such as continuous power supply, wind-PV-thermal-battery sources operation, utilization rate of renewable energy, etc. To solve this bi-level model, a linearization method for nonlinear constraints model is proposed, and a heuristic algorithm based on the combination of value function and branch-bound is designed to obtain the efficient solution. Based on a typical example of multi-energy complementary power generation system, the experimental results verify the effectiveness of the proposed bi-level model and algorithm.

Key words: multi-energy complementary power generation system, battery/thermal energy storage, capacity optimization, bi-level, heuristic algorithm

李湃, 卢慧, 李驰, 杜洪博. 多能互补发电系统电/热储能容量双层优化配置方法[J]. 中国电力, 2025, 58(3): 55-64.

Pai LI, Hui LU, Chi LI, Hongbo DU. Bi-level Capacity Optimization for Battery/Thermal Energy Storage System in Multi-energy Complementary Power Generation System[J]. Electric Power, 2025, 58(3): 55-64.

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图/表 11

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参数名称		数值
风电场单位装机投资成本/(万元∙MW^–1)		600
光伏电站单位装机投资成本/(万元∙MW^–1)		450
储能电站单位装机投资成本/(万元∙MW^–1)		50
储能电站单位容量投资成本/(万元∙(MW∙h)^–1)		200
光热电站单位装机投资成本/(万元∙MW^–1)		3000
储热装置单位容量投资成本/(万元∙(MW∙h)^–1)		30
风电和光伏最大弃电率/%		5
储能电站充电效率		0.94
储能电站放电效率		0.94
光热电站的热-电转换效率		2.4
光热电站的储热效率		0.98
光热电站的放热效率		0.98

参数名称		数值
风电场单位装机投资成本/(万元∙MW^–1)		600
光伏电站单位装机投资成本/(万元∙MW^–1)		450
储能电站单位装机投资成本/(万元∙MW^–1)		50
储能电站单位容量投资成本/(万元∙(MW∙h)^–1)		200
光热电站单位装机投资成本/(万元∙MW^–1)		3000
储热装置单位容量投资成本/(万元∙(MW∙h)^–1)		30
风电和光伏最大弃电率/%		5
储能电站充电效率		0.94
储能电站放电效率		0.94
光热电站的热-电转换效率		2.4
光热电站的储热效率		0.98
光热电站的放热效率		0.98

参数		优化结果
系统年净收益/万元		79963
储能装机容量/MW		291
储能电池容量/(MW∙h)		582
储能电池时长/h		2
光热储热容量/(MW∙h)		6820
储热时长/h		5.7
系统供电缺额/(MW∙h)		393.0
风电利用率/%		95.7
光伏利用率/%		96.6

参数		优化结果
系统年净收益/万元		79963
储能装机容量/MW		291
储能电池容量/(MW∙h)		582
储能电池时长/h		2
光热储热容量/(MW∙h)		6820
储热时长/h		5.7
系统供电缺额/(MW∙h)		393.0
风电利用率/%		95.7
光伏利用率/%		96.6

方法	系统年净收益/万元	系统供电缺额/(MW∙h)	计算耗时/s
所提方法	79963	393.0	8.1
HPR问题最优解	79964	1916.3	0.1

多能互补发电系统电/热储能容量双层优化配置方法

Bi-level Capacity Optimization for Battery/Thermal Energy Storage System in Multi-energy Complementary Power Generation System

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图/表 11

参考文献 30

相关文章 15

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Metrics

参数	优化风光装机	固定风光装机
系统年净收益/万元	99009	79963
风电装机容量/MW	3421	2000
光伏装机容量/MW	579	2000
储能装机容量/MW	332	291
储能电池容量/(MW∙h)	664	582
光热储热容量/(MW∙h)	6312	6820
储热时长/h	5.3	5.7
系统供电缺额/(MW∙h)	1095	393
风电利用率/%	99.5	95.7
光伏利用率/%	95.5	96.6
新能源利用率/%	99.0	96.1

参数	场景1	场景2（基础场景）	场景3
系统年净收益/万元	81849	79963	64174
储能装机容量/MW	98	291	1181
储能电池容量/(MW∙h)	196	582	2362
光热储热容量/(MW∙h)	6820	6820	6820
储热时长/h	5.7	5.7	5.7
供电缺额量/(MW∙h)	0	393	2433
供电缺额时长/h	0	61	243

参数	0.001	0.005	0.01 （基础场景）	0.02	0.05
系统年净收益/万元	79884	79919	79963	80051	80314
储能装机容量/MW	299.1	295.5	291	282	255
储能电池容量/(MW∙h)	598.2	591	582	564	510
储能电池时长/h	2	2	2	2	2
光热储热容量/(MW∙h)	6820	6820	6820	6820	6820
光热储热时长/h	5.7	5.7	5.7	5.7	5.7
系统供电缺额/(MW∙h)	27.4	136.9	393.0	907.6	2451.6

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多能互补发电系统电/热储能容量双层优化配置方法

Bi-level Capacity Optimization for Battery/Thermal Energy Storage System in Multi-energy Complementary Power Generation System

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