Reliability Index Calculation and Reserve Capacity Optimization Considering Multiple Uncertainties

doi:10.16183/j.cnki.jsjtu.2022.366

Abstract

Abstract:

In power systems with a high proportion of renewable energy, to achieve coordinated optimal scheduling of source and load considering multiple uncertainties is an important issue in power system operation. Therefore, a probabilistic spinning reserve optimization model based on multiple scenarios is constructed. Multiple uncertain factors are considered in the model, such as wind power and solar power forecast errors, load forecast error and unscheduled generator outage. Renewable energy curtailment and load shedding are used as special reserve resources in the day-ahead security-constrained unit commitment (SCUC) to improve the economic operation efficiency. The calculations of reliability indexes, expected energy not served and expected energy curtailment, are simplified, and the inequality constraints related to these two indexes are reduced, which improves the computational performance of the model. The model optimizes the total expected cost considering multiple uncertainties. Case studies based on the IEEE-RTS demonstrate the effectiveness of the proposed model. The numerical results show that the improved calculation method of reliability indexes can effectively reduce the solution time of the SCUC model. The reserve optimization model can realize the dynamic allocation of the spinning reserve capacity of the system and improve economic operation of the system.

Key words: renewable energy, spinning reserve, reliability index, security-constrained unit commitment, cost-benefit analysis

CLC Number:

TM732

YE Lun, OUYANG Xu, YAO Jiangang, YANG Shengjie, YIN Jungang. Reliability Index Calculation and Reserve Capacity Optimization Considering Multiple Uncertainties[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 30-39.

Figures/Tables 9

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Fig.4

Fig.5

Fig.6

Fig.7

References 20

[1]	黄强, 郭怿, 江建华, 等. “双碳”目标下中国清洁电力发展路径[J]. 上海交通大学学报, 2021, 55(12): 1499-1509.
	HUANG Qiang, GUO Yi, JIANG Jianhua, et al. Development pathway of China’s clean electricity under carbon peaking and carbon neutrality goals[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1499-1509.
[2]	康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11.
	KANG Chongqing, YAO Liangzhong. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 2-11.
[3]	ORTEGA-VAZQUEZ M A, KIRSCHEN D S. Estimating the spinning reserve requirements in systems with significant wind power generation penetration[J]. IEEE Transactions on Power System, 2009, 24(1):114-124. doi: 10.1109/TPWRS.2008.2004745 URL
[4]	苏鹏, 刘天琪, 李兴源. 含风电的系统最优旋转备用的确定[J]. 电网技术, 2010, 34(12): 158-162.
	SU Peng, LIU Tianqi, LI Xingyuan. Determination of optimal spinning reserve of power grid containing wind[J]. Power System Technology, 2010, 34(12): 158-162.
[5]	LIU G, TOMSOVIV K. Quantifying spinning reserve in systems with significant wind power penetration[J]. IEEE Transactions on Power System, 2012, 27(4): 2385-2393. doi: 10.1109/TPWRS.2012.2207465 URL
[6]	KHAZALI A, KALANTAR M. Spinning reserve quantification by a stochastic-probabilistic scheme for smart power systems with high wind penetration[J]. Energy Conversion and Management, 2015, 96: 242-257. doi: 10.1016/j.enconman.2015.02.070 URL
[7]	LV J, DING T, BIE Z, et al. A novel linearization variant of reliability costs in the optimal scheduling model[J]. IEEE Transactions on Power System, 2017, 32(5): 4140-4142. doi: 10.1109/TPWRS.2017.2650783 URL
[8]	LIU Y, JIANG C, SHEN J, et al. Cost allocation of spinning reserve based on risk contribution[J]. IEEJ Transactions on Electrical and Electronic Engineering, 2015, 10: 664-673. doi: 10.1002/tee.2015.10.issue-6 URL
[9]	ELA E, MILLIGAN M, KIRBY B. Operating reserves and variable generation[R]. Golden, USA: National Renewable Energy Laboratory, 2011.
[10]	陈厚合, 王杨, 张儒峰, 等. 考虑源荷协调的风电并网系统旋转备用容量优化[J]. 电力自动化设备, 2017, 37(8): 185-192.
	CHEN Houhe, WANG Yang, ZHANG Rufeng, et al. Spinning reserve capacity optimization considering coordination between source and load for power system with wind power[J]. Electric Power Automation Equipment, 2017, 37(8): 185-192.
[11]	黄瀚燕, 周明, 李庚银. 考虑多重不确定性和备用互济的含风电互联电力系统分散协调调度方法[J]. 电网技术, 2019, 42(2): 381-389.
	HUANG Hanyan, ZHOU Ming, LI Gengyin. Coordinated decentralized dispatch of wind-power-integrated multi-area interconnected power systems considering multiple uncertainties and mutual reserve support[J]. Power System Technology, 2019, 42(2): 381-389.
[12]	YANG Y, BAO M, DING Y, et al. Impact of down spinning reserve on operation reliability of power systems[J]. Journal of Modern Power System and Clean Energy, 2020, 8(4): 709-718. doi: 10.35833/MPCE.2019.000110 URL
[13]	刘明涛, 谢俊, 张秋艳, 等. 碳交易环境下含风电电力系统短期生产模拟[J]. 上海交通大学学报, 2021, 55(12): 1598-1607.
	LIU Mingtao, XIE Jun, ZHANG Qiuyan, et al. Short-term production simulation of power system containing wind power under carbon trading environment[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1598-1607.
[14]	崔杨, 张汇泉, 仲悟之, 等. 考虑需求响应的含光热电站可再生能源高渗透率电力系统多源优化调度[J]. 高电压技术, 2020, 26(5): 1499-1509.
	CUI Yang, ZHANG Huiquan, ZHONG Wuzhi, et al. Multi-source optimal scheduling of renewable energy high-permeability power system with CSP plants considering demand response[J]. High Voltage Engineering, 2020, 26(5): 1499-1509.
[15]	林峰, 汪震, 王冠中, 等. 考虑风电降载的电力系统鲁棒备用调度模型[J]. 电力系统自动化, 2018, 42(19): 64-70.
	LIN Feng, WANG Zhen, WANG Guanzhong, et al. Robust reserve scheduling model of electric power system considering WTG de-loading capability[J]. Automation of Electric Power Systems, 2018, 42(19): 64-70.
[16]	FABBRI A, ROMAN T G, ABBAD J R, et al. Assessment of the cost associated with wind generation prediction errors in a liberalized electricity market[J]. IEEE Transactions on Power System, 2005, 20(3): 1440-1446. doi: 10.1109/TPWRS.2005.852148 URL
[17]	ZHAO S, FANG Y, WEI Z. Stochastic optimal dispatch of integrating concentrating solar power plants with wind farms[J]. International Journal of Electrical Power and Energy Systems, 2019, 109: 575-583. doi: 10.1016/j.ijepes.2019.01.043 URL
[18]	BILLINTON R, ALLAN R N. Reliability evaluation of power systems[M]. 2nd ed. New York, USA: Plenum Press, 1996.
[19]	BOUFFARD F, GALIANA F D. An electricity market with a probabilistic spinning reserve criterion[J]. IEEE Transactions on Power System, 2004, 19(1): 300-307. doi: 10.1109/TPWRS.2003.818587 URL
[20]	GRIGG C, WONG P, ALBRECHT P, et al. The IEEE reliability test system — 1996[J]. IEEE Transactions on Power System, 1999, 14(3): 1010-1018. doi: 10.1109/59.780914 URL

求解精度	N_K	I		II		III
求解精度	N_K	E^C /美元	计算时间/s	E^C /美元	计算时间/s	E^C /美元	计算时间/s
10^-3	3	689 421	7.28	689 426	2.30	689 370	1.16
	5	695 448	51.12	695 226	2.81	695 234	1.06
	7	697 071	94.21	697 008	4.68	697 058	1.35
	9	697 487	181.11	697 380	7.05	697 398	1.86
10^-6	3	689 231	23.39	689 231	10.17	689 231	2.38
	5	695 167	181.33	695 167	48.98	695 167	4.21
	7	—	>1 000	696 910	60.94	696 910	5.43
	9	—	>1 000	697 342	80.11	697 342	5.46

备用配置方式	期望成本/ 美元	电能成本/ 美元	启动成本/ 美元	正旋转备用成本/美元	负旋转备用成本/美元	失负荷成本/美元	能源削减成本/美元
方式1	711 785	662 544	9 551	25 446	8 303	5 942	0
方式2	708 351	646 677	7 830	19 202	8 303	26 339	0
方式3	697 058	647 101	7 092	22 889	4 325	14 563	1 088