含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度

doi:10.11930/j.issn.1004-9649.202303109

中国电力 ›› 2024, Vol. 57 ›› Issue (5): 149-156.DOI: 10.11930/j.issn.1004-9649.202303109

含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度

李江南¹(), 程韧俐¹(), 周保荣²(), 刘稼瑾³(), 毛田², 赵文猛², 王滔², 黄光磊¹, 许银亮³()

1. 深圳供电局有限公司，广东深圳　518000
2. 南方电网科学研究院有限责任公司，广东广州　510663
3. 清华大学深圳国际研究生院，广东深圳　518000

收稿日期:2023-03-27 出版日期:2024-05-28 发布日期:2024-05-16
作者简介:李江南（1987—），男，高级工程师，从事电网调度运行与控制、虚拟电厂、电力现货研究，E-mail：15813895996@163.com
程韧俐（1972—），女，高级工程师（教授级），从事电力系统调度研究，E-mail：2366807010@qq.com
周保荣（1974—），男，高级工程师（教授级），从事电力系统稳定分析研究，E-mail：zhoubr@csg.cn
刘稼瑾（1993—），女，硕士研究生，从事综合能源系统规划运行、电氢能源系统研究，E-mail：liujiaji22@mails.tsinghua.edu.cn
许银亮（1983—），男，通信作者，副教授，从事虚拟电厂、微电网和智能电网的分布式控制等研究，E-mail：xu.yinliang@sz.tsinghua.edu.cn
基金资助:
中国南方电网有限责任公司科技项目（SZKJXM20220036/09000020220301030901283）。

Stochastic Optimal of Integrated Energy System in Low-Carbon Parks Considering Carbon Capture Storage and Power to Hydrogen

Jiangnan LI¹(), Renli CHENG¹(), Baorong ZHOU²(), Jiajin LIU³(), Tian MAO², Wenmeng ZHAO², Tao WANG², Guanglei HUANG¹, Yinliang XU³()

1. Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518000, China
2. China Southern Power Grid Science Research Institute Co., Ltd., Guangzhou 510663, China
3. Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518000, China

Received:2023-03-27 Online:2024-05-28 Published:2024-05-16
Supported by:
This work is supported by Science and Technology Project of China Southern Power Grid Corporation (No.SZKJXM20220036/09000020220301030901283).

摘要/Abstract

摘要：

针对工业园区的零碳转型需求，建立了一种“新能源发电+氢储能”与“火电+碳捕集”的多能互补技术组合。系统考虑将氢能直接售卖给氢能汽车获益以达成经济性目标，将氢能汽车减排量加入碳交易以实现低碳性目标。通过可再生能源渗透率、弃风弃光率及氢能汽车减排量3个指标来量化系统的低碳效益。考虑风光出力不确定性，基于蒙特卡洛算法对风光曲线进行场景生成，基于概率距离削减法削减至4个典型场景，然后采用随机优化方法分析典型日运行成本。结果表明：该系统既能增加风光新能源的消纳、降低碳排放，又能降低系统日运行成本，验证了零碳园区转型的可行性。

关键词: 电转氢, 碳捕集, 随机优化, 综合能源系统

Abstract:

In response to the needs of zero-carbon transformation in industrial parks, a multi-energy complementary technology combination of "new energy power generation + hydrogen energy storage" and "thermal power + carbon capture" has been established. Considering add the corresponding emission reduction of hydrogen vehicles to carbon trading and the direct sale of hydrogen energy to hydrogen vehicles, the system aims to achieve optimal economy and low-carbon performance. Besides, the system quantifies low-carbon benefits through the consumption rate of renewable energy, new energy abandonment rate and emission reduction of hydrogen vehicles. The results show that the system can not only increase the consumption of wind and solar new energy, reduce carbon emissions, but also reduce operational costs. The system can verify the feasibility of the transformation of the zero-carbon park.

Key words: power to hydrogen, carbon capture, stochastic optimization, integrated energy system

李江南, 程韧俐, 周保荣, 刘稼瑾, 毛田, 赵文猛, 王滔, 黄光磊, 许银亮. 含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度[J]. 中国电力, 2024, 57(5): 149-156.

Jiangnan LI, Renli CHENG, Baorong ZHOU, Jiajin LIU, Tian MAO, Wenmeng ZHAO, Tao WANG, Guanglei HUANG, Yinliang XU. Stochastic Optimal of Integrated Energy System in Low-Carbon Parks Considering Carbon Capture Storage and Power to Hydrogen[J]. Electric Power, 2024, 57(5): 149-156.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202303109

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图/表 11

图 1 含碳捕集和电转氢的低碳综合能源系统框架

Fig.1 P2H-CCS low carbon integrated system framework

表 1 系统参数

Table 1 System parameters

参数	取值	参数	取值
燃气轮机功率/kW	1500	燃气轮机碳排放强度/ (kg·(kW·h)^–1)	0.4
电解槽功率/kW	1000	电网购电碳排放强度/ (kg·(kW·h)^–1)	0.8
碳捕集固定功率/kW	200	园区碳配额系数/(kg·(kW·h)^–1)	0.3
风机装机容量/kW	7000	园区向电网最大售电量/(kW·h)	1000
光伏装机容量/kW	5000	氢价/(元·kg^–1)	60
燃气轮机效率/%	40	碳价/(元·t^–1)	60
电解槽效率/%	85	电制氢运行系数/(元·(kW·h)^–1)	0.3
碳捕集效率/%	90	弃风弃光系数/(元·(kW·h)^–1)	0.6

图 2 典型日预测负荷风电及光伏输出

Fig.2 Forecast output of load wind and solar in typical day

表 2 不同场景的成本组成

Table 2 Cost composition in different scenarios 单位：元

场景	设备运行成本	碳交易成本	电网交互成本	弃风弃光成本	售氢利润	总运行成本
1	51899	289	–1739	6066	0	56515
2	53063	251	–541	5867	0	58640
3	58230	46	661	2098	12490	48545

表 3 不同场景的碳排放组成

Table 3 Carbon emission composition in different scenarios 单位：kg

场景	燃气轮机碳排放量	电网购电碳排放量	园区碳配额量	碳捕集吸收碳量	氢能汽车减碳量	总碳排放量
1	7152	3030	5364	0	0	4818
2	8559	3903	6419	1852	0	4191
3	9772	3956	7329	1738	3887	774

图 3 不同场景的不同时刻的弃风弃光率

Fig.3 Abandon rate of wind and solar in different scenarios

图 4 含碳捕集及电制氢设备园区的电功率平衡图

Fig.4 Electric power balance diagram of P2H-CCS park

图 5 可再生能源渗透率敏感性分析

Fig.5 Renewable energy penetration rate sensitivity analysis

表 4 一天内不同场景的弃风弃光量占比

Table 4 The proportion of abandoned wind and solar in different scenes in a day

场景		1		2		3
弃风弃光量占比/%		9.3		8.9		3.2

图 6 不同氢价对总成本和碳减排影响分析

Fig.6 The impact of different hydrogen on the total cost and carbon emission

图 7 不同碳价对总碳排放量和碳交易利润影响分析

Fig.7 The impact of different carbon prices on carbon emission and trading profits

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含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度

Stochastic Optimal of Integrated Energy System in Low-Carbon Parks Considering Carbon Capture Storage and Power to Hydrogen

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含碳捕集及电转氢设备的低碳园区综合能源系统随机优化调度

Stochastic Optimal of Integrated Energy System in Low-Carbon Parks Considering Carbon Capture Storage and Power to Hydrogen

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