Optimal Operation Method of Electric-Hydrogen Hybrid Energy Storage Microgrid System Based on Typical Commercial Operation Mode

doi:10.12096/j.2096-4528.pgt.23173

Abstract

Abstract:

Objectives Aiming at the low-carbon transformation of micro-grid, an optimal scheduling method for electric-hydrogen hybrid energy storage micro-grid was proposed to address the scheduling challenges under different business models. Methods Firstly, a mathematical model of micro-grid with electro-hydrogen hybrid energy storage was developed. Based on two typical business models of multi-party cooperative energy supply and multi-party independent energy supply were analyzed. Based on these models, the corresponding multi-objective optimization scheduling models and these constraints were constructed. Then, the non-dominated sorting genetic algorithm II (NSGA-II) was introduced, which was combined with variance crowding distance method and normal distribution crossover operator to improve optimization efficiency and solution accuracy. Finally, the simulation experiments were conducted using an operational electro-hydrogen hybrid energy storage micro-grid system in a southeastern coastal area to validate the effectiveness of the proposed method. Results Compared with before optimization, the economy of the multi-party cooperative energy supply business model is improved by about 4.1%, the wind-solar energy abandon rate is reduced by about 19%, and the annual carbon emission is reduced by about 47.42 t. Conclusions The multi-party cooperative energy supply business model aligns better with the current power market conditions of China’s, and the optimized system performance is significantly enhanced. This study demonstrates that the proposed optimization scheduling method effectively supports the low-carbon transition of electro-hydrogen hybrid energy storage micro-grid under various business models.

Key words: microgrid, power system, renewable energy, energy storage system, reversible conversion of electric hydrogen, typical business model, non-dominated sorting genetic algorithm II (NSGA-II), multi-objective optimization algorithm

CLC Number:

TK 01

Wen LI, Fanpeng BU, Xiaotong ZHANG, Chuangdong YANG, Jing ZHANG. Optimal Operation Method of Electric-Hydrogen Hybrid Energy Storage Microgrid System Based on Typical Commercial Operation Mode[J]. Power Generation Technology, 2024, 45(6): 1186-1200.

Figures/Tables 14

References 33

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测试函数	指标	本文算法	NSGA-II算法	多目标浣熊算法	多目标粒子群算法
ZDT1	平均值	0.013 9	0.031 5	0.023 4	0.036 7
	标准差	0.001 7	0.005 0	0.003 6	0.006 2
	IGD	0.012 9	0.023 0	0.022 3	0.028 9
	Spacing	0.025 4	0.078 9	0.039 8	0.083 5
ZDT2	平均值	0.014 3	0.021 2	0.019 6	0.023 5
	标准差	0.001 9	0.004 8	0.005 2	0.007 3
	IGD	0.010 8	0.024 0	0.018 9	0.028 7
	Spacing	0.034 7	0.063 8	0.037 8	0.059 3
ZDT3	平均值	0.014 8	0.027 5	0.018 7	0.027 9
	标准差	0.001 2	0.006 4	0.004 9	0.008 4
	IGD	0.010 7	0.023 1	0.017 9	0.027 1
	Spacing	0.042 0	0.072 9	0.063 9	0.084 5
ZDT6	平均值	0.015 7	0.027 4	0.024 7	0.032 5
	标准差	0.001 5	0.004 6	0.003 5	0.005 9
	IGD	0.012 7	0.021 8	0.023 7	0.029 3
	Spacing	0.028 6	0.066 7	0.051 8	0.080 6

测试函数	指标	本文算法	NSGA-II算法	多目标浣熊算法	多目标粒子群算法
ZDT1	平均值	0.013 9	0.031 5	0.023 4	0.036 7
	标准差	0.001 7	0.005 0	0.003 6	0.006 2
	IGD	0.012 9	0.023 0	0.022 3	0.028 9
	Spacing	0.025 4	0.078 9	0.039 8	0.083 5
ZDT2	平均值	0.014 3	0.021 2	0.019 6	0.023 5
	标准差	0.001 9	0.004 8	0.005 2	0.007 3
	IGD	0.010 8	0.024 0	0.018 9	0.028 7
	Spacing	0.034 7	0.063 8	0.037 8	0.059 3
ZDT3	平均值	0.014 8	0.027 5	0.018 7	0.027 9
	标准差	0.001 2	0.006 4	0.004 9	0.008 4
	IGD	0.010 7	0.023 1	0.017 9	0.027 1
	Spacing	0.042 0	0.072 9	0.063 9	0.084 5
ZDT6	平均值	0.015 7	0.027 4	0.024 7	0.032 5
	标准差	0.001 5	0.004 6	0.003 5	0.005 9
	IGD	0.012 7	0.021 8	0.023 7	0.029 3
	Spacing	0.028 6	0.066 7	0.051 8	0.080 6

电源结构	经济总成本/元	弃风率/%	弃光率/%	碳减排量/kg
含风光	5 869.056	11	7	618.77
含光伏	6 665.060	0	4	164.81
含风电	6 206.484	8	0	474.59
无新能源	7 041.481	0	0	0

电源结构	经济总成本/元	弃风率/%	弃光率/%	碳减排量/kg
含风光	5 869.056	11	7	618.77
含光伏	6 665.060	0	4	164.81
含风电	6 206.484	8	0	474.59
无新能源	7 041.481	0	0	0

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