含氢储能的多源联合发电系统调度研究

doi:10.16180/j.cnki.issn1007-7820.2023.02.009

摘要/Abstract

摘要：

风电和光伏发电具有间歇性和随机性,为了降低在多源联合发电系统中的弃风弃光率,采用含氢储能系统和火电机组配合来平滑风电和光电机组出力。文中以系统运行成本最小和弃电惩罚成本最小为目标,以系统功率平衡、火电机组出力和爬坡、热备用、风电和光电出力及储能系统储氢罐容量、电解槽和燃料电池功率等为约束条件构建了多源联合发电系统日前调度模型。通过YALMIP工具箱对模型进行编程,并调用CPLEX对编写的程序进行求解。对含有风电、光电、火电机组以及储能系统的多源联合发电系统进行算例分析,通过对比有无储能系统的弃风弃光量和系统总运行成本,证明了含氢储能系统可以有效降低系统的弃风弃光率,并提高系统的经济性。

关键词: 含氢储能系统, 多源发电系统, 日前调度, 风光出力, 弃风弃光率, 经济调度, YALMIP, CPLEX

Abstract:

Wind power and photovoltaic power generation are intermittent and random. In order to reduce the abandonment rate in the multi-source combined power generation system, the hydrogen-containing energy storage system and the thermal power unit are used to smooth the output of wind power and photovoltaic units. This study aims to minimize the operating cost of the system and the penalty cost of power abandonment. A day-ahead scheduling model of multi-source combined power generation system is constructed with the constraints of system power balance, thermal power unit output and ramping, hot backup, wind power and photovoltaic output, hydrogen storage tank capacity of energy storage system, electrolyzer and fuel cell power. The model is programmed through the YALMIP toolbox, and CPLEX is called to solve the programmed program. A case study of a multi-source combined power generation system containing wind power, photovoltaic, thermal power generation and energy storage systems is carried out. By comparing the amount of abandoned wind and light with or without an energy storage system and the total operating cost of the system, it is proved that the hydrogen-containing energy storage system can effectively reduce the rate of abandoned wind and light and improve the economy of the system.

Key words: hydrogen-containing energy storage system, multi-source power generation system, day-ahead dispatch, wind power and photovoltaic output, abandonment rate of wind and light, economic dispatch, YALMIP, CPLEX

中图分类号:

TP319

郭成威,田书,刘明杭. 含氢储能的多源联合发电系统调度研究[J]. 电子科技, 2023, 36(2): 61-66.

GUO Chengwei,TIAN Shu,LIU Minghang. Research on Dispatching of Multi-Source Combined Power Generation System Containing Hydrogen Energy Storage[J]. Electronic Science and Technology, 2023, 36(2): 61-66.

图/表 11

图1

表1

图2

表2

表3

图3

图4

表4

图5

图6

图7

参考文献 18

[1]	白昱阳, 张俊, 王晓辉, 等. 考虑分布式可再生能源的通证激励机制设计与分散式电力市场研究[J]. 电力建设, 2021, 42(6):29-43. doi: 10.12204/j.issn.1000-7229.2021.06.004
	Bai Yuyang, Zhang Jun, Wang Xiaohui, et al. Research on incentive mechanism design and decentralized power market with consideration of distributed renewable energy[J]. Electric Power Construction, 2021, 42(6):29-43. doi: 10.12204/j.issn.1000-7229.2021.06.004
[2]	马磊, 张超, 钟鸣, 等. 光储气微网优化运行研究[J]. 电气传动, 2021, 51(9):67-74.
	Ma Lei, Zhang Chao, Zhong Ming, et al. Research on economical operation of the micro-grid with photovoltaic and natural gas[J]. Electric Drive, 2021, 51(9):67-74.
[3]	周正威, 郝亚群, 张雪映. 基于需求响应的风电-抽水蓄能系统调度模型[J]. 电子科技, 2019, 32(4):77-80.
	Zhou Zhengwei, Hao Yaqun, Zhang Xueying. A dispatch model for wind power and pumped-storage system based on demand response[J]. Electronic Science and Technology, 2019, 32(4):77-80.
[4]	梁龙基, 张靖, 何宇, 等. 基于博弈论的互联微电网多主体协同优化配置[J]. 电子科技 2021, 34(7):43-49.
	Liang Longji, Zhang Jing, He Yu, et al. Optimal coordination sizing analysis of different entities interconnected microgrids based on game theory[J]. Electronic Science and Technology, 2021, 34(7):43-49.
[5]	刘丹, 刘方. 风光储系统储能容量协调优化[J]. 热力发电, 2021, 50(6):54-59.
	Liu Dan, Liu Fang. Coordination and optimization of energy storagecapacity of wind/PV/storagehybrid systems[J]. Thermal Power Generation, 2021, 50(6):54-59.
[6]	沈琛云, 王明俭, 李晓明. 基于风-光-蓄-火联合发电系统的多目标优化调度[J]. 电网与清洁能源, 2019, 35(11):74-82.
	Shen Chenyun, Wang Mingjian, Li Xiaoming. Multi-objective optimal dispatch based on wind-solar-pumped storage thermal combined power system[J]. Power System and Clean Energy, 2019, 35(11):74-82.
[7]	蒋承刚, 熊国江, 陈锦龙. 基于改进非支配多目标差分进化算法的含风电-小水电电力系统动态环境经济调度[J]. 电力科学与工程, 2021, 37(8):1-9. doi: 10.3969/j.issn.1672-0792.2021.8.001
	Jiang Chenggang, Xiong Guojiang, Chen Jinlong. Dynamic economic emission dispatching of power systems with wind and small hydropower based on improved non-dominated multi-objective differential evolutionary algorithm[J]. Electric Power Science and Engineering, 2021, 37(8):1-9. doi: 10.3969/j.issn.1672-0792.2021.8.001
[8]	田书, 赵哲林, 杜少通. 基于改进多目标差分进化算法的节能优化调度[J]. 武汉大学学报(工学版), 2019, 52(12):1091-1096.
	Tian Shu, Zhao Zhelin, Du Shaotong. Energy-saving optimal scheduling based on improved multi-objective differential evolution algorithm[J]. Engineering Journal of Wuhan University, 2019, 52(12):1091-1096.
[9]	郭骏. 风光储互补微电网的优化调度与能量管理策略研究[J]. 电气工程, 2020, 8(1):36-47. doi: 10.12677/JEE.2020.81005
	Guo Jun. Research on optimal scheduling and energy management strategy of wind-PV-ES complementary micro-grid[J]. Journal of Electrical Engineering, 2020, 8(1):36-47. doi: 10.12677/JEE.2020.81005
[10]	李彦哲, 郭小嘉, 董海鹰, 等. 风/光/储微电网混合储能系统容量优化配置[J]. 电力系统及其自动化学报, 2020, 32(6):123-128.
	Li Yanzhe, Guo Xiaojia, Dong Haiying, et al. Optimal capacity configuration of wind/PV/storage hybrid energy storage system in micro-grid[J]. Proceedings of the CSU-EPSA, 2020, 32(6):123-128.
[11]	黄涛, 许志鹏, 葛乐. 考虑风电出力随机特性的氢储能综合能源系统优化调度[J]. 电器与能效管理技术, 2020(5):72-77.
	Huang Tao, Xu Zhipeng, Ge Le. Optimal scheduling of hydrogen energy storage system considering random characteristics of wind power output[J]. Electrical & Energy Management Technology, 2020(5):72-77.
[12]	李咸善, 杨宇翔. 基于双向电价补偿的含氢储能风电和梯级水电联合优化调度[J]. 电网技术, 2020, 44(9):3297-3306.
	Li Xianshan, Yang Yuxiang. Optimization dispatching for joint operation of hydrogen storage-wind power and cascade hydropower station based on bidirectional electricity price compensation[J]. Power System Technology, 2020, 44(9):3297-3306.
[13]	陈颖毅, 王丽萍, 赵亚威, 等. 考虑弃水电量机会损失的水火电短期联合优化调度[J]. 水电能源科学, 2020, 38(7):65-68.
	Chen Yingyi, Wang Liping, Zhao Yawei, et al. Short-termcoordination optimal of hydrothermal scheduling considering opportunity loss of surplus hydropower[J]. Water Resources and Power, 2020, 38(7):65-68.
[14]	刘志坚, 余莎, 梁宁. 考虑制氢储能参与的互联电力系统优化调度研究[J]. 电力科学与工程, 2020, 36(3):45-51. doi: 1672-0792(2020)03-0045-07
	Liu Zhijian, Yu Sha, Liang Ning. The optimal scheduling with hydrogen energy storage participation for interconnected power system[J]. Electric Power Science and Engineering, 2020, 36(3):45-51. doi: 1672-0792(2020)03-0045-07
[15]	张国斌, 陈玥, 张佳辉, 等. 风-光-水-火-抽蓄联合发电系统日前优化调度研究[J]. 太阳能学报, 2020, 41(8):79-85.
	Zhang Guobin, Chen Yue, Zhang Jiahui, et al. Research on optimization of day-ahead dispatching of wind power-photovoltaic-hydropower-thermal power-pumped storage combined power generation system[J]. Acta Energiae Solaris Sinica, 2020, 41(8):79-85.
[16]	姚海涛. 含氢储的混合储能在风光互补发电系统中容量优化研究[J]. 电气开关, 2020, 58(6):18-22.
	Yao Haitao. Research on capacity optimization of hybrid energy storage with hydrogen storage in a wind-solar hybrid power system[J]. Electric Switchgear, 2020, 58(6):18-22.
[17]	李星雨, 邱晓燕, 史光耀, 等. 考虑虚拟电厂和分时电价的风光火储系统两阶段优化调度策略[J]. 南方电网技术, 2017, 11(6):70-77.
	Li Xingyu, Qiu Xiaoyan, Shi Guangyao, et al. Two-stage optimal dispatching strategy for wind-photovoltaic-coal-energy storage system considering virtual power plant and time-of-use electricity prices[J]. Southern Power System Technology, 2017, 11(6):70-77.
[18]	崔杨, 张家瑞, 仲悟之, 等. 计及电热转换的含储热光热电站与风电系统优化调度[J]. 中国电机工程学报, 2020, 40(20):6482-6494.
	Cui Yang, Zhang Jiarui, Zhong Wuzhi, et al. Optimal scheduling of concentrating solar power plant with thermal energy storage and wind farm considering electric-thermal conversion[J]. Proceedings of the CSEE, 2020, 40(20):6482-6494.

	出力上限 /MW	出力下限 /MW	a_i /元·h^-1	b_i /元·(MWh)^-1	c_i元 /(MW)²·h
G₁	200	50	0.4	150	75
G₂	80	20	1.2	150	350
G₃	50	15	0.4	180	250
G₄	40	12	0.6	100	500
G₅	35	10	1.0	200	167
G₆	30	10	1.0	150	500

时段	电价/元·(kWh)^-1	时段	电价/元·(kWh)^-1
1~7	0.25	8~9	0.45
11~15	0.65	16~18	0.45
19~21	0.65	22~24	0.45

	火电出力成本/万元	弃风弃光惩罚成本/万元	储能系统折旧成本/万元
有储能系统参与	76.48	0.008 9	0.1
无储能系统参与	80.86	6.920 0	0.0