抽蓄电站提供多时间尺度备用的优化策略

doi:10.19799/j.cnki.2095-4239.2021.0410

摘要/Abstract

摘要：

“碳达峰、碳中和”背景下，新能源发电将成为未来电力系统中的主要发电形式。然而，其随机性与波动性增加了电网不同时间尺度上的运行备用需求。抽水蓄能作为成熟的储能技术之一，具有调节速度快、容量大等优势，在电网辅助服务中的作用已备受重视。然而，抽蓄电站在电能量市场与各类辅助服务市场中的运行策略、收益最大化问题还有待深入研究。为此，本工作在电力市场环境下建立了抽蓄电站参与电能量市场与多时间尺度备用市场的优化决策模型，并着重分析了备用补偿价格对其运行策略的影响，为抽蓄电站参与电力市场的运行决策提供了解决方案。算例分析表明：抽蓄电站通过提供备用服务能够明显提高其运行收益；并且，抽蓄电站提供多种备用时的总收益明显高于提供单一备用时的收益。本文算例分析中，提供多种备用的总收益至少提高了44.37%。

关键词: 抽蓄电站, 多时间尺度备用, 电能量市场, 市场策略

Abstract:

In the background of peak carbon emissions and carbon neutrality, renewable energy generation will become the main generation form in future power systems. Simultaneously, randomness and volatility increase the reserve requirement in different time scales. Pumped-storage power station (PSPS), a mature type of energy storage, has the advantages of fast regulation speed and large capacity, and it has increasing importance in the aspect of ancillary services. Trading off the benefits of energy storage in the energy market and the multiple time-scale reserve market to maximize its benefits is an important issue for PSPS waiting to be addressed. In this regard, this paper establishes an optimal decision-making model for PSPS to participate in the energy market and the multiple time-scale reserve market. The impact of reserve compensation prices on the operation strategies is further analyzed. This work provides a solution for PSPS to participate in the electric energy market. Case studies show that the total revenue of PSPS is significantly increased through providing reserve service. The total revenue of PSPS when providing multiple time-scale reserves is higher than that when providing a single reserve service. In the test case, the total revenue of PSPS when providing multiple time-scale reserves is increased by 44.37% at least.

Key words: pumped storage power station, multiple time-scale reserves, energy market, market strategy

中图分类号:

TM 622

余晓鹏, 李晓萌, 张忠, 郝元钊, 李程昊, 陈幸伟, 崔惟, 高泽. 抽蓄电站提供多时间尺度备用的优化策略[J]. 储能科学与技术, 2022, 11(2): 573-582.

Xiaopeng YU, Xiaomeng LI, Zhong ZHANG, Yuanzhao HAO, Chenghao LI, Xingwei CHEN, Wei CUI, Ze GAO. Research on the optimal strategy of pumped-storage power station to provide multiple time-scale reserves[J]. Energy Storage Science and Technology, 2022, 11(2): 573-582.

图/表 13

图1

图2

图3

表1

表2

图4

表3

表4

表5

图5

图6

图7

表6

参考文献 29

1	李晓萌, 张忠, 赵华, 等. 能源互联网背景下电网备用问题探索[J]. 电力建设, 2021, 42(5): 57-68.
	LI X M, ZHANG Z, ZHAO H, et al. Research on reserve services of the power grid under the background of energy Internet[J]. Electric Power Construction, 2021, 42(5): 57-68.
2	郑秀波, 夏春, 林勇, 等. 中国电网运行事故备用标准建议[J]. 电力系统自动化, 2018, 42(1): 151-159.
	ZHENG X B, XIA C, LIN Y, et al. Suggestion on operation contingency reserve standards for power grid of China[J]. Automation of Electric Power Systems, 2018, 42(1): 151-159.
3	赵云丽, 吕泉, 朱全胜, 等. 风电并网后系统备用的相关问题综述[J]. 可再生能源, 2015, 33(4): 565-571.
	ZHAO Y L, LYU Q, ZHU Q S, et al. Overview on issues related to reserve capacity by wind power connected to the grid[J]. Renewable Energy Resources, 2015, 33(4): 565-571.
4	Ancillary services report 2017[R/OL]. Energy UK, 2017[2021-01-01].https://www.‍energy-uk.‍org.‍uk/publication.‍html?‍task=file.download&id=6138.
5	喻洁, 刘云仁, 杨家琪, 等. 美国加州辅助服务市场发展解析及其对我国电力市场的启示[J]. 电网技术, 2019, 43(8): 2711-2717.
	YU J, LIU Y R, YANG J Q, et. Analysis of development of California ancillary service market and its enlightenment to China's power market[J]. Power System Technology, 2019, 43(8): 2711-2717.
6	薛禹胜, 罗运虎, 李碧君, 等. 关于可中断负荷参与系统备用的评述[J]. 电力系统自动化, 2007, 31(10): 1-6.
	XUE Y S, LUO Y H, LI B J, et al. A review of interruptible load participating in system reserve[J]. Automation of Electric Power Systems, 2007, 31(10): 1-6.
7	HAN B, LU S F, XUE F, et al. Day-ahead electric vehicle aggregator bidding strategy using stochastic programming in an uncertain reserve market[J]. IET Generation, Transmission & Distribution, 2019, 13(12): 2517-2525.
8	KONDA S R, PANWAR L K, PANIGRAHI B K, et al. Optimal offering of demand response aggregation company in price-based energy and reserve market participation[J]. IEEE Transactions on Industrial Informatics, 2018, 14(2): 578-587.
9	TANG Z, LIU Y K, WU L, et al. Reserve model of energy storage in day-ahead joint energy and reserve markets: A stochastic UC solution[J]. IEEE Transactions on Smart Grid, 2021, 12(1): 372-382.
10	LIU D N, GAO Y, ZHANG T T, et al. Research on Strategy of distributed energy storage aggregators participating in peak load regulation auxiliary service[J]. IOP Conference Series: Earth and Environmental Science, 2021, 687(1): doi: 10.1088/1755-1315/687/1/012140.
11	VATANDOUST B, AHMADIAN A, GOLKAR M A, et al. Risk-averse optimal bidding of electric vehicles and energy storage aggregator in day-ahead frequency regulation market[J]. IEEE Transactions on Power Systems, 2019, 34(3): 2036-2047.
12	KIM H S, HONG J, CHOI I S. Implementation of distributed autonomous control based battery energy storage system for frequency regulation[J]. Energies, 2021, 14(9): 2672.
13	ABOUZEID S I, GUO Y F, ZHANG H C. Cooperative control framework of the wind turbine generators and the compressed air energy storage system for efficient frequency regulation support[J]. International Journal of Electrical Power & Energy Systems, 2021, 130: doi: 10.1016/j.ijepes.2021.106844.
14	孙中昊, 赵晋泉, 杨余华, 等. 风光水火储多类型电源参与调频市场出清模型[C]//中国电机工程学会电力市场专业委员会2019年学术年会暨全国电力交易机构联盟论坛论文集, 成都, 2019: 343-348.
15	王凯丰, 谢丽蓉, 乔颖, 等. 电池储能提高电力系统调频性能分析[J]. 电力系统自动化, 2021, 1-13.
	WANG K F, XIE L R, QIAO Y, et al. Analysis on frequency modulation performance of power system improved by battery energy storage[J]. Automation of Electric Power Systems, 2021: 1-13.
16	刘英培, 周素文, 梁海平, 等. 光储直流配电网灵活虚拟惯性控制策略[J]. 电力自动化设备, 2021, 41(5): 107-113.
	LIU Y P, ZHOU S W, LIANG H P, et al. Flexible virtual inertial control strategy of photovoltaic-energy storage DC distribution network[J]. Electric Power Automation Equipment, 2021, 41(5): 107-113.
17	孙东磊, 郑志杰, 马逸然, 等. 储能与AGC机组协同的鲁棒调度[J]. 电力自动化设备, 2021, 41(6): 142-149.
	SUN D L, ZHENG Z J, MA Y R, et al. Robust dispatching of energy storage coordinated with AGC units[J]. Electric Power Automation Equipment, 2021, 41(6): 142-149.
18	刘敦楠, 李鹏飞, 葛睿, 等. 考虑可调控负荷和储能的区域互联备用优化模型[J]. 电力建设, 2019, 40(12): 22-29.
	LIU D N, LI P F, GE R, et al. Optimization model of regional interconnection reserve considering adjustable load and energy storage[J]. Electric Power Construction, 2019, 40(12): 22-29.
19	刘志谱, 李欣然, 刘小龙, 等. 基于风险量化的综合能源系统电储能事故备用容量优化利用研究[J]. 中国电机工程学报, 2021, 41(8): 2641-2651.
	LIU Z P, LI X R, LIU X L, et al. Research on optimal utilization of battery energy storage emergency reserve capacity in integrated energy system based on risk quantification[J]. Proceedings of the CSEE, 2021, 41(8): 2641-2651.
20	刘小龙, 李欣然, 刘志谱, 等. 基于风险量化与需求侧响应的综合能源系统储能事故备用优化利用[J]. 电工技术学报, 2021, 36(9): 1901-1913.
	LIU X L, LI X R, LIU Z P, et al. Study on the optimal utilization of integrated energy system emergency reserve based on risk quantification and demand side response[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1901-1913.
21	雷长炎, 王琦, 谢东亮, 等. 集中式储能运行备用能力的评估及仿真[J]. 电力工程技术, 2021, 40(3): 15-21.
	LEI C Y, WANG Q, XIE D L, et al. Evaluation and simulation on the reserve capability of centralized energy storage[J]. Electric Power Engineering Technology, 2021, 40(3): 15-21.
22	邓强, 詹红霞, 杨孝华, 等. 直购电背景下利用储能配合旋转备用的风电并网容量优化[J]. 电力建设, 2019, 40(4): 98-109.
	DENG Q, ZHAN H X, YANG X H, et al. Optimization of wind power integration capacity considering spinning reserve with energy storage system in the context of direct power purchase[J]. Electric Power Construction, 2019, 40(4): 98-109.
23	宋天昊, 李柯江, 韩肖清, 等. 储能系统参与多应用场景的协同运行策略[J]. 电力系统自动化, 2021, 45(19): 43-51.
	SONG T H, LI K J, HAN X Q, et al. Coordinated operation strategy of energy storage system participating in multiple application scenarios[J]. Automation of Electric Power Systems, 2021, 45(19): 43-51.
24	梁睿光. 抽水蓄能电站调峰填谷及风电消纳效益研究[D]. 北京: 华北电力大学, 2017.
	LIANG R G. Benefit research of regulating system load and wind power integration for pumped storage station[D]. Beijing: North China Electric Power University, 2017.
25	单华, 王骞, 袁超, 等. 基于Stackelberg博弈模型的抽水蓄能电站调相补偿机制[J]. 电力系统自动化, 2020, 44(3): 139-146.
	SHAN H, WANG Q, YUAN C, et al. Phase modulation compensation mechanism of pumped-storage power station based on stackelberg game model[J]. Automation of Electric Power Systems, 2020, 44(3): 139-146.
26	张经纬, 黄宁馨, 张乔榆, 等. 电力现货市场环境下抽水蓄能日出力曲线优化模型[J]. 广东电力, 2020, 33(6): 28-37.
	ZHANG J W, HUANG N X, ZHANG Q Y, et al. Optimization model for daily output curve of pumped-storage in power spot market environment[J]. Guangdong Electric Power, 2020, 33(6): 28-37.
27	杨宏基, 周明, 张茗洋, 等. 电力市场下抽水蓄能电站运营策略及效益分析[J]. 华北电力大学学报(自然科学版), 2021, 48(6): 71-80.
	YANG H J, ZHOU M, ZHANG M Y, et al. Operational mechanism and cost-benefit analysis of pumped storage plant in power market environment[J]. Journal of North China Electric Power University (Natural Science Edition), 2021, 48(6): 71-80.
28	蒋万枭, 刘继春, 韩晓言, 等. 离网条件下考虑短时间尺度的水光蓄多能互补发电系统备用容量确定方法[J]. 电网技术, 2020, 44(7): 2492-2502.
	JIANG W X, LIU J C, HAN X Y, et al. Reserve optimization for offline multi-energy complementary generation system in short time scale[J]. Power System Technology, 2020, 44(7): 2492-2502.
29	梁子鹏, 陈皓勇, 雷佳, 等. 考虑风电不确定度的风-火-水-气-核-抽水蓄能多源协同旋转备用优化[J]. 电网技术, 2018, 42(7): 2111-2119, 2121.
	LIANG Z P, CHEN H Y, LEI J, et al. A multi-source coordinated spinning reserve model considering wind power uncertainty[J]. Power System Technology, 2018, 42(7): 2111-2119, 2121.

备用补偿价格 /(元/h)	申报备用容量		总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
备用补偿价格 /(元/h)	向上备用容量 /MW	向下备用容量 /MW	总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
0.002	0	0	8357	20	20	0.00	100
0.004	0	0	8357	20	20	0.00	100
0.006	0.8	0	8360	19.15	20	0.01	100
0.008	3	0	8479	17	20	0.05	100
0.010	3	0	8623	17	20	0.05	100
0.012	3	3	8835	17	17	0.05	99.95
0.014	3	3	9123	17	17	0.05	99.95
0.016	3	3	9411	17	17	0.05	99.95
0.018	3	3	9699	17	17	0.05	99.95
0.020	3	3	9987	17	17	0.05	99.95

备用补偿价格 /(元/h)	申报备用容量		总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
备用补偿价格 /(元/h)	向上备用容量 /MW	向下备用容量 /MW	总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
0.0016	0	0	8357	20	20	0	100
0.0032	0	0	8357	20	20	0	100
0.0048	0	0	8357	20	20	0	100
0.0064	2.4	0	8376	18	20	0.40	100
0.0080	4.9	0	8510	15	20	0.82	100
0.0096	10	6.8	8873	10	13	1.67	98.87
0.0112	10	8.6	9559	10	11	1.67	98.56
0.0128	10	10	10324	10	10	1.67	98.33
0.0144	10	10	11092	10	10	1.67	98.33
0.0160	10	10	11860	10	10	1.67	98.33

备用补偿价格 /(元/h)	申报备用容量		总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
备用补偿价格 /(元/h)	向上备用容量 /MW	向下备用容量 /MW	总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
0.0012	0	0	8357	20	20	0	100
0.0024	0	0	8357	20	20	0	100
0.0036	0	0	8357	20	20	0	100
0.0048	0	0	8357	20	20	0	100
0.0060	0.9	0	8359	19	20	1.71	100
0.0072	2.4	0	8420	18	20	4.77	100
0.0084	5.3	0	8558	15	20	10.66	100
0.0096	20	20	9216	0	0	40	60
0.0108	20	20	10368	0	0	40	60
0.0120	20	20	11520	0	0	40	60

备用补偿价格 /(元/h)	申报备用容量		总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
备用补偿价格 /(元/h)	向上备用容量 /MW	向下备用容量 /MW	总收益 /元	最大抽水功率 /MW	最大放电功率 /MW	最小库容状态 /(MW·h)	最大库容状态 /(MW·h)
0.001	0	0	8357	20	20	0	100
0.002	0	0	8357	20	20	0	100
0.003	0	0	8357	20	20	0	100
0.004	0	0	8357	20	20	0	100
0.005	0	0	8357	20	20	0	100
0.006	0.9	0	8359	19	20	1.71	100
0.007	2.4	0	8409	18	20	4.77	100
0.008	4.9	0	8508	15	20	9.80	100
0.009	6.8	0	8653	13	20	13.58	100
0.010	20	20	9600	0	0	40	60

参数	备用1	备用2	备用3	备用4	多种备用并用
补偿价格/(元/h)	0.01	0.008	0.006	0.005	/
最大抽水功率/MW	17	15	19	20	10
最大放电功率/MW	20	20	20	20	10
最小库容状态/(MW·h)	0.005	0.82	1.71	0	21.72
最大库容状态/(MW·h)	99.95	100	100	100	78.28
总收益/元	8623	8510	8359	8357	12340