多源耦合不确定性下含电氢储能的微电网低碳容量优化配置研究

doi:10.19799/j.cnki.2095-4239.2024.1091

摘要/Abstract

摘要：

在全球能源转型的背景下，微电网作为一种灵活的分布式资源有效集成方案，对于能源系统的可持续发展显得至关重要。微电网不仅能够提升电力系统的灵活性和可靠性，还为实现低碳经济目标提供切实可行的途径。本文以提高微电网的运行经济性、稳定性和低碳性为目标，旨在考虑多源耦合的不确定性环境下，探索含电氢储能的微电网低碳经济优化配置方案。具体而言，首先在分析微电网中各单元运行特性的基础上，应用场景生成和基于改进的K-means聚类算法，构建风电、光伏发电及电力负荷的典型场景集来处理不确定性问题。然后，以综合成本最小化为微电网上层容量优化的目标，以系统总运行成本的最小化为下层运行优化的目标。同时引入阶梯碳交易机制，建立微电网双层优化配置的模型。最终，结合改进的乌燕鸥算法和混合整数线性规划方法求解所建立的双层优化模型，进而确定微电网的最优容量配置。通过基于华中地区某地年气象和负荷数据的算例分析，验证了所提方法的有效性与优越性。

关键词: 微电网, 氢储能, 配置优化, 双层优化, 不确定性建模

Abstract:

Against the backdrop of global energy transition, the microgrid, as a flexible and effective integration solution for distributed renewable energy, is crucial for the sustainable development of energy systems. The microgrid can not only improve the flexibility and reliability of the power system, but also provide a practical way to achieve the goal of low-carbon economy. This paper aims to improve the economic efficiency, stability, and low-carbon characteristics of microgrid operation, focusing on the optimal double-layer configuration of a microgrid with electricity-hydrogen energy storage under multi-source coupling uncertainties. Specifically, based on analyzing the operation characteristics of various units in the microgrid, the study utilizes scenario generation and the improved K-means clustering algorithm to construct typical scenario sets for wind power, photovoltaic output, and power load to address uncertainty issues. Furthermore, considering the carbon trading mechanism, a double-layer optimization configuration model is proposed for the microgrid, with the objective of minimizing overall costs in the upper layer and minimizing total operation costs of the system in the lower layer. Finally, the double-layer optimization model is solved by combining an improved shearwater algorithm and mixed-integer linear programming method, and then the optimal capacity configuration of the microgrid is determined. The effectiveness and superiority of the proposed method are verified by an example analysis based on annual meteorological and load data in a certain area of central China.

Key words: microgrid, hydrogen energy storage, configuration optimization, two-layer optimization, uncertainty modeling

中图分类号:

TK 01

李明, 尹文良, 李勇康, 孙晨业, 陈佳佳. 多源耦合不确定性下含电氢储能的微电网低碳容量优化配置研究[J]. 储能科学与技术, 2025, 14(5): 1969-1981.

Ming LI, Wenliang YIN, Yongkang LI, Chenye SUN, Jiajia CHEN. Low-carbon capacity optimal configuration of microgrid with hydrogen energy storage under multi-source coupling uncertainties[J]. Energy Storage Science and Technology, 2025, 14(5): 1969-1981.

图/表 15

图1

图2

图3

图4

表1

表2

图5

表3

表4

不同方案下优化成本结果"

方案	C_in/万元	C_fuel/万元	C_ex/万元	C_dump/万元	$C C O 2$ /万元	C_u/万元
1	19436.19	73.92	107.30	29.20	0	20229.68
2	20079.47	46.83	78.71	46.36	0	20853.75
3	25045.85	39.69	86.18	49.45	1.52	25929.57
4	26059.04	10.85	71.64	51.99	18.11	26923.31

表4

表5

图6

图7

图8

图9

表6

不同碳价水平下系统成本、碳排放量与购电量"

τ/(元/kg)	$C C O 2$ /万元	C_u/万元	系统碳排放量 /吨	系统购电量 /MWh
低等(0.134)	9.10	26988.35	684.95	1030.82
中等(0.402)	27.35	27007.13	490.80	709.78
高等(1.34)	90.26	27066.76	355.21	558.60

表6

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分布式电源	安装费用/(元/kW或元/kW·h)	寿命/a
风力发电机	12000	20
光伏电池	8800	25
柴油发电机	1500	20
蓄电池	2100	10
电解槽	2000	15
燃料电池	14000	10
储氢罐	450	20

类型	时间	购电价格/(元/ kW·h)	售电价格/(元/kW·h)
谷时	0:00—6:00	0.45	0.28
谷时	22:00—24:00	0.45	0.28

平时	12:00—18:00	0.73	0.53

峰时	6:00—12:00	1.21	0.72
峰时	18:00—22:00	1.21	0.72

方案	WT/kW	PV/kW	DE/kW	BAT/kWh	EL/kW	FC/kW	HT/kWh
1	337	400	80	618	89	80	981
2	369	401	45	580	96	84	1069
3	365	412	36	935	114	129	1149
4	392	446	12	1032	131	180	1386

方案	购电量/MWh	售电量/MWh	碳排放量/吨
1	1332.64	31.85	1144.73
2	970.34	86.29	807.04
3	1079.07	62.77	850.58
4	915.51	178.74	607.20

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