综合智慧能源系统中抽水蓄能电站两部制电价研究

doi:10.3969/j.issn.2097-0706.2022.07.002

综合智慧能源 ›› 2022, Vol. 44 ›› Issue (7): 10-18.doi: 10.3969/j.issn.2097-0706.2022.07.002

综合智慧能源系统中抽水蓄能电站两部制电价研究

李华^a^,^b(), 郑洪纬^a^,^b(), 周博文^a^,^b^,^*(), 李广地^a^,^b(), 杨波^a^,^b()

a.信息科学与工程学院,东北大学,沈阳 110819
b.辽宁省综合能源优化与安全运行重点实验室,东北大学,沈阳 110819

收稿日期:2022-04-03 修回日期:2022-06-03 出版日期:2022-07-25 发布日期:2022-07-19
通讯作者: 周博文
作者简介:李华（1966）,女,副教授,博士,从事电力系统分析、能源电力规划等方面的研究, lihua@ise.neu.edu.cn;
郑洪纬（1998）,男,在读硕士研究生,从事新能源优化调度、电力交易等方面的研究, 1668689249@qq.com;
李广地（1989）,男,讲师,博士,从事新能源发电、电力电子技术等方面的研究, liguangdi@ise.neu.edu.cn;
杨波（1976）,男,高级工程师,从事新能源、物联网、电气控制等方面的研究, yangbo@ise.neu.edu.cn。
基金资助:
国家自然科学基金项目(61703081);中央高校基本科研业务费专项资金项目(N2104014);广东省基础与应用基础研究基金项目(2021A1515110778)

Two-part tariff for pumped storage power plants in an integrated intelligent energy system

LI Hua^a^,^b(), ZHENG Hongwei^a^,^b(), ZHOU Bowen^a^,^b^,^*(), LI Guangdi^a^,^b(), YANG Bo^a^,^b()

a. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
b. Key Laboratory of Integrated Energy Optimization and Secure Operation of Liaoning Province, Northeastern University, Shenyang 110819, China

Received:2022-04-03 Revised:2022-06-03 Online:2022-07-25 Published:2022-07-19
Contact: ZHOU Bowen

摘要/Abstract

摘要：

作为最成熟的储能形式,抽水蓄能是未来综合智慧能源系统支撑“碳达峰、碳中和”目标实现的重要组成部分,但缺乏合理的电价制定策略是制约其发展的重要因素。针对该问题,研究了综合智慧能源系统中,可再生能源与抽水蓄能联合运行场景下,抽水蓄能的两部制电价机制。根据经营期定价法确定抽水蓄能容量电价,考虑“抽水蓄能+可再生能源”的经济性优势,建立抽水蓄能与风电联合优化调度模型,以引入抽水蓄能后的系统总成本减少量和抽水成本为目标函数,得到抽水蓄能的合理抽发策略,再以价格需求关系和补偿变动成本为原则分别制定抽水蓄能电站抽水时段和发电时段的电量电价。最后通过算例仿真分析了抽水蓄能电站对实现系统低碳运行的作用以及电站抽水成本对电价的影响,验证了抽水蓄能两部制电价制定策略的有效性。

关键词: 碳中和, 抽水蓄能电站, 综合智慧能源, 可再生能源, 两部制电价, 风电消纳, 低碳运行

Abstract:

As the most mature form of energy storage, pumped storage will be an important supportive technique for integrated intelligent energy systems to achieve carbon peaking and carbon neutrality. But the development of the technique is hampered by the lack of a proper pricing strategy. In response to this problem, the two-part tariff strategy for pumped storage power plants which operate in corporation with an integrated intelligent energy system is proposed. According to the operation pricing strategy, the tariff is determined by the capacity of a pumped storage power plant. In view of the economic advantages of "pumped storage + renewable energy", an optimal dispatch model for the combination of pumped storage and wind power is established. Taking the reduction of total cost and pumped storage cost of the combined system as the objective functions, a rational pumping strategy for the installed pumped storage power plant is carried out. And the tariffs in water pumping stage and in power generation stage of the power plant are figured out according to the relationship of demand and price and variable cost compensation principle, respectively. The effect of integrating a pumped storage power plant in an integrated intelligent system on the low-carbon operation and electric price of the combined system is verified by a case, which proves the effectiveness of the two-part tariff strategy of pumped storage power plants.

Key words: carbon neutrality, pumped storage power plant, integrated intelligent energy, renewable energy, two-part tariffs, wind power consumption, low -carbon operation

中图分类号:

TK019：TK02

李华, 郑洪纬, 周博文, 李广地, 杨波. 综合智慧能源系统中抽水蓄能电站两部制电价研究[J]. 综合智慧能源, 2022, 44(7): 10-18.

LI Hua, ZHENG Hongwei, ZHOU Bowen, LI Guangdi, YANG Bo. Two-part tariff for pumped storage power plants in an integrated intelligent energy system[J]. Integrated Intelligent Energy, 2022, 44(7): 10-18.

图/表 8

图1

图2

图3

图4

表1

表2

图5

图6

参考文献 22

[1]	张金平, 周强, 王定美, 等. “双碳”目标下新型电力系统发展路径研究[J]. 华电技术, 2021, 43(12):46-51.
	ZHANG Jinping, ZHOU Qiang, WANG Dingmei, et al. Research on the development path of new power system to achieve carbon peaking and carbon neutrality[J]. Huadian Technology, 2021, 43(12):46-51.
[2]	王松岑, 来小康, 程时杰. 大规模储能技术在电力系统中的应用前景分析[J]. 电力系统自动化, 2013, 37(1):3-8.
	WANG Songcen, LAI Xiaokang, CHENG Shijie. An analysis of the application prospects of large-scale energy storage technology in power systems[J]. Automation of Electric Power Systems, 2013, 37(1):3-8.
[3]	童家麟, 洪庆, 吕洪坤, 等. 电源侧储能技术发展现状及应用前景综述[J]. 华电技术, 2021, 43(7): 17-23.
	TONG Jialin, HONG Qing, LYU Hongkun, et al. Development status and application prospect of power side energy storage technology[J]. Huadian Technology, 2021, 43(7): 17-23.
[4]	尤培培. 两部制电价反映抽水蓄能多元价值[N]. 中国能源报,2021-05-17(004).
[5]	孙伟卿, 裴亮, 向威, 等. 电力系统中储能的系统价值评估方法[J]. 电力系统自动化, 2019, 43(8):47-55.
	SUN Weiqing, PEI Liang, XIANG Wei, et al. Evaluation method of system value for energy storage in power system[J]. Automation of Electric Power Systems, 2019, 43(8):47-55.
[6]	张晴, 李欣然, 杨明, 等. 净效益最大的平抑风电功率波动的混合储能容量配置方法[J]. 电工技术学报, 2016, 31(14):40-48.
	ZHANG Qing, LI Xinran, YANG Ming, et al. Capacity determination of hybrid energy storage system for smoothing wind power fluctuations with maximum net benefit[J]. Transactions of China Electrotechnical Society, 2016, 31(14):40-48.
[7]	李建林, 马会萌, 惠东. 储能技术融合分布式可再生能源的现状及发展趋势[J]. 电工技术学报, 2016, 31(14):1-10.
	LI Jianlin, MA Huimeng, HUI Dong. Present development condition and trends of energy storage technology in the integration of distributed renewable energy[J]. Transactions of China Electrical Technology, 2016, 31(14):1-10.
[8]	舒康安, 张昌, 艾小猛, 等. 基于分段电价的跨区风电消纳[J]. 电工技术学报, 2017, 32(S1):39-49.
	SHU Kang'an, ZHANG Chang, AI Xiaomeng, et al. Cross-region wind power consumption based on segmented tariff[J]. Transactions of China Electrical Technology, 2017, 32(S1):39-49.
[9]	YE L, ZHANG C, XUE H, et al. Study of assessment on capability of wind power accommodation in regional power grids[J]. Renewable Energy, 2018, 133:647-662. doi: 10.1016/j.renene.2018.10.042
[10]	尹硕, 郭兴五, 燕景, 等. 考虑高渗透率和碳排放约束的园区综合能源系统优化运行研究[J]. 华电技术, 2021, 43(4): 1-7.
	YIN Shuo, GUO Xingwu, YAN Jing, et al. Study on optimized operation on integrated energy system in parks with high permeability and carbon emission constraints[J]. Huadian Technology, 2021, 43(4): 1-7.
[11]	LUO Yanhong, NIE Qiubo, YANG Dongsheng, et al. Robust optimal operation of active distribution network based on minimum confidence interval of distributed energy Beta distribution[J]. Journal of Modern Power Systems and Clean Energy, 2021, 9(2):423-430. doi: 10.35833/MPCE.2020.000198
[12]	王煜东. 面向新能源消纳的发电侧两部制电价机制设计[D]. 银川: 宁夏大学, 2020.
[13]	KHANI H, FARAG H E Z. Joint arbitrage and operating reserve scheduling of energy storage through optimal adaptive allocation of the state of charge[J]. IEEE Transactions on Sustainable Energy, 2019, 10(4):1705-1717. doi: 10.1109/TSTE.2018.2869882
[14]	ZHANG Y X, XU Y, YANG H M, et al. Optimal whole-life-cycle planning of battery energy storage for multifunctional services in power systems[J]. IEEE Transactions on Sustainable Energy, 2020, 11(4):2077-2086. doi: 10.1109/TSTE.2019.2942066
[15]	ABDELTAWAB H, MOHAMED A R I. Mobile energy storage sizing and allocation for multi-services in power distribution systems[J]. IEEE Access, 2019, 7:176613-176623. doi: 10.1109/ACCESS.2019.2957243
[16]	冯力勇, 张云. 考虑电池能效的电网侧电化学储能电站最优功率控制策略研究[J]. 华电技术, 2020, 42(4): 37-41.
	FENG Liyong, ZHANG Yun. Optimal power control strategy of grid-side electrochemical energy storage stations considering battery energy efficiency[J]. Huadian Technology, 2020, 42(4): 37-41.
[17]	LUO Yanhong, ZHANG Xinwen, YANG Dongsheng, et al. Emission trading based optimal scheduling strategy of energy hub with energy storage and integrated electric vehicles[J]. Journal of Modern Power Systems and Clean Energy, 2020, 8(2): 267-275. doi: 10.35833/MPCE.2019.000144
[18]	管馨, 陈涛, 高赐威. 适应风电参与电力市场的需求侧储能负荷运行优化研究[J]. 综合智慧能源, 2022, 44(2): 35-41. doi: 10.3969/j.issn.2097-0706.2022.02.006
	GUAN Xin, CHEN Tao, GAO Ciwei. Study on optimal operation of the demand-side energy storage system for wind power participating in electricity market[J]. Integrated Intelligent Energy, 2022, 44(2): 35-41. doi: 10.3969/j.issn.2097-0706.2022.02.006
[19]	武昭原, 周明, 姚尚润, 等. 基于合作博弈论的风储联合参与现货市场优化运行策略[J]. 电网技术, 2019, 43(8):2815-2824.
	WU Zhaoyuan, ZHOU Ming, YAO Shangrun, et al. Optimization operation strategy of wind-storage coalition in spot market based on cooperative game theory[J]. Power System Technology, 2019, 43(8):2815-2824.
[20]	张粒子, 丛野, 陶文斌, 等. 面向电力现货市场的专项工程两部制输电价格优化模型[J]. 电力系统自动化, 2020, 44(23):90-98.
	ZHANG Lizi, CONG Ye, TAO Wenbin, et al. Optimization model of two-part transmission price for dedicated project oriented to power spot market[J]. Automation of Electric Power Systems, 2020, 44(23):90-98.
[21]	ANTWEILER W. A two-part feed-in-tariff for intermittent electricity generation[J]. Energy Economics, 2017, 65:458-470. doi: 10.1016/j.eneco.2017.05.010
[22]	国家发展和改革委员会. 国家发展改革委关于进一步完善抽水蓄能价格形成机制的意见[EB/OL].(2021-04-30)[2022-03-28]. https://www.ndrc.gov.cn/xxgk/zcfb/tz/202105/t20210507_1279341.html?code=&state=123.

时段	抽水成本/万元	电价/[元·(MW·h)^-1]
时段	抽水成本/万元	电量电价	容量电价
00:00—01:00	5.74	462.81	146.83
01:00—02:00	12.39	445.94
02:00—03:00	11.91	428.73
03:00—04:00	11.54	415.36
04:00—05:00	11.95	430.12
05:00—06:00	11.87	427.33
06:00—07:00	12.22	439.97
07:00—08:00	—	466.75
08:00—09:00	12.49	631.88
09:00—10:00	—	649.14
10:00—11:00	—	605.40
11:00—12:00	—	487.90
12:00—13:00	—	491.37
13:00—14:00	7.96	540.79
14:00—15:00	11.18	624.76
15:00—16:00	—	650.30
16:00—17:00	—	644.39
17:00—18:00	—	713.29
18:00—19:00	—	783.35
19:00—20:00	—	769.25
20:00—21:00	—	706.03
21:00—22:00	—	653.93
22:00—23:00	—	617.25
23:00—24:00	—	508.82

算例场景	抽水蓄能机组	风电机组	火电机组（负荷率）	两部制电价来源
1	×	√	√（100%）	—
2	√	×	√（100%）	抽水蓄能
3	√	√	√（100%）	抽水蓄能+风电
4	√	√	√（80%）	抽水蓄能+风电

综合智慧能源系统中抽水蓄能电站两部制电价研究

Two-part tariff for pumped storage power plants in an integrated intelligent energy system

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 22

相关文章 15

编辑推荐

Metrics

本文评价

[1]	高明, 陈家豪, 王丽晓, 唐武琛, 王智东, 张紫凡, 马海霞, 冯瑞珏, 周长鹏. 考虑光伏不确定性因素的电力系统概率潮流三点估计法[J]. 综合智慧能源, 2022, 44(9): 1-10.
[2]	钟鹏元, 杨晓宏, 寇建玉. 含储氢结构的园区综合能源系统优化配置研究[J]. 综合智慧能源, 2022, 44(9): 11-19.
[3]	韩世旺, 赵颖, 张兴宇, 玄承博, 赵田田, 侯绪凯, 刘倩倩. 面向碳中和的新型电力系统氢储能调峰技术研究[J]. 综合智慧能源, 2022, 44(9): 20-26.
[4]	江婷, 赵雅姣. 基于燃气分布式的综合能源系统碳减排分析[J]. 综合智慧能源, 2022, 44(9): 27-32.
[5]	张旭, 张浩浩, 顾吉浩. 室温空间特性差异性分析及抽样推断方法研究[J]. 综合智慧能源, 2022, 44(9): 51-58.
[6]	姜曙, 刘芳芳, 刘媛媛, 陈启召, 连丽, 任梦楠. “地热能+”在工程实践中的综合梯级应用[J]. 综合智慧能源, 2022, 44(9): 59-64.
[7]	余果, 吴军, 夏热, 陈逸珲, 郭子辉, 黄文鑫. 构网型变流器技术的发展现状与趋势研究[J]. 综合智慧能源, 2022, 44(9): 65-70.
[8]	唐琦雯, 沈琪, 祝俊, 苏宜靖. 浙江调频辅助服务市场机制设计及运营实践[J]. 综合智慧能源, 2022, 44(9): 71-77.
[9]	韩倩雯, 张琨, 陈晓阳, 朱腾龙. La/Ni共掺杂SrTi_0.35Fe_0.65O_3-_δ对称电极用于SOEC共电解H₂O/CO₂研究[J]. 综合智慧能源, 2022, 44(8): 43-47.
[10]	杨莹, 张雁祥, 闫牧夫. 中低温固体氧化物燃料电池电解质制备方法研究进展[J]. 综合智慧能源, 2022, 44(8): 50-57.
[11]	陈晗钰, 周晓亮, 刘立敏, 钱欣源, 王宙, 何非凡, 绳阳. 质子导体固体电解池电解水制氢研究进展[J]. 综合智慧能源, 2022, 44(8): 75-85.
[12]	王盛, 谈健, 史文博, 邹风华, 陈光, 王林钰, 惠红勋, 郭磊. 英国新型电力系统建设经验以及对我国省级电网发展启示[J]. 综合智慧能源, 2022, 44(7): 19-32.
[13]	冶兆年, 赵长禄, 王永真, 韩恺, 刘超凡, 韩俊涛. 基于纳什议价的共享储能能源互联网络双目标优化[J]. 综合智慧能源, 2022, 44(7): 40-48.
[14]	张荣权, 李刚强, 卜思齐, 刘芳, 朱玉祥. 基于自适应学习率萤火虫算法的多能源系统联合优化调度[J]. 综合智慧能源, 2022, 44(7): 49-57.
[15]	郭祚刚, 袁智勇, 徐敏, 雷金勇, 李朋岳, 谈赢杰. 多能互补综合能源系统混合能流计算方法及算例[J]. 综合智慧能源, 2022, 44(7): 58-65.