Low-carbon capacity optimal configuration of microgrid with hydrogen energy storage under multi-source coupling uncertainties

doi:10.19799/j.cnki.2095-4239.2024.1091

Abstract

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

CLC Number:

TK 01

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.

Figures/Tables 15

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Table 1

Table 2

Fig. 5

Table 3

Table 4

Optimized cost results under different schemes"

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

Table 4

Table 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Table 6

Results of system costs, carbon emissions and electricity purchased under different carbon price levels"

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

Table 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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