Capacity optimization configuration of wind-solar complementary electricity-alcohol cogeneration system

doi:10.3969/j.issn.2097-0706.2023.12.009

Abstract

Abstract:

In order to advance the application of clean energy in multiple fields and achieve the "dual carbon" target， a wind-solar complementary electricity-alcohol cogeneration system has been proposed. A capacity optimal allocation model for the wind-solar system is established subject to pursue the maximum annual revenue of the electricity-alcohol cogeneration system. Taking the historical data from a wind-solar-hydrogen production base in Inner Mongolia as an example，energy analysis and economic analysis are carried out on the proposed cogeneration system by simulation. The new cogeneration system proposed above can utilize the storage capacity of hydrogen energy after taking optimized configuration and collaborative schedule of wind and solar capacity， ensuring continuous and stable running of methanol synthesis equipment at its minimum load rate of 40% or above. The results show that when the photovoltaic capacity is 25.4 MW， and the wind power capacity is 74.6 MW， the system integrating electricity generation system with alcohol generation system can boost the renewable energy accommodation capacity with a 2.9% decrease in renewable energy curtailment rate. Meanwhile， the annual net income of the new system is 17.73 million yuan， 6.6% higher than that of the system without alcohol generation system. The research provides a feasible technical roadmap for the multi-energy complementation system， with decent economic and environmental benefits.

Key words: electricity-alcohol cogeneration, multi-energy complementary system, optimized configuration, hydrogen production from water electrolysis, collaborative schedule, "dual carbon" target, clean energy

CLC Number:

TK019

YANG Zhengjun, LIANG Shixing, XU Gang, LIU Wenyi, WANG Ying, CUI Jianwei. Capacity optimization configuration of wind-solar complementary electricity-alcohol cogeneration system[J]. Integrated Intelligent Energy, 2023, 45(12): 71-78.

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设备	单位投资成本	运维成本占投资成本比例/%
光伏发电机组	3 800 元/kW	1
风力发电机组	4 800 元/kW	2
甲醇合成设备	18 700 元/kg	2
电解槽	3 000 元/kW	2
储氢罐	2 000 元/kg	1

设备	项目	数值
甲醇合成设备	转化效率/%	95
	单位产量电耗/(kW·h·kg^-1)	0.2
	功率范围/%	40~100
电解槽	单位产量电耗/(kW·h·kg^-1)	49.0
	能量效率/%	80
	功率范围/%	0~100
储氢罐	容量配置范围/t	0~30
储氢罐	充放效率/%	98
模型约束	净上网最大比例/%	20
模型约束	最大允许弃电比例/%	15

季节	时段	购电价格	售电价格
大风季	高峰时段（17:00—21:00）	0.68	0.30
	平时段（04:00—10:00,15:00— 17:00, 21:00-24:00）	0.52
	低谷时段（0:00—04:00, 10:00—15:00)	0.34
小风季	尖峰时段（18:00—20:00）	0.77
	高峰时段（05:00—7:00,17:00— 18:00, 20:00—21:00）	0.68
	平时段（07:00—10:00,15:00— 17:00, 21:00—次日05:00）	0.52
	低谷时段（10:00—15:00）	0.34

参数	情景1	情景2	情景3
光伏容量/MW	100.0	0	25.4
风电容量/MW	0	100.0	74.6
电解槽容量/MW	28.4	31.9	29.7
甲醇设备容量/（t·d^-1）	33.4	66.9	66.2
储氢罐容量/t	3.9	4.4	2.9
电解槽利用小时数	3 756	5 916	6 146
甲醇设备利用小时数	7 781	6 974	6 809
弃电率/%	10.8	8.8	2.9