Citation: | LI Wensheng, WEI Jia, CAO Yongji, et al. A Quantitative Assessment Method for Power System Flexibility Based on Probabilistic Optimal Power Flow[J]. Modern Electric Power, 2024, 41(5): 832-843. DOI: 10.19725/j.cnki.1007-2322.2022.0429 |
Given its fluctuation and stochasticity, renewable energy generation’s high proportion to connect poses challenges to the flexibility of the power system. For that reason, a quantitative assessment method of power system flexibility based on probabilistic optimal power flow was proposed. Firstly, the flexible resource models of the power system were constructed. Historical data was processed to generate scenarios by using the k-means method, and the probabilistic models of wind power, photovoltaic power, and load fluctuation were constructed considering the time correlation based on the Markov chain model and the Copula function. Secondly, associating economic costs with system flexibility, quantitative assessment indicators that take into account the operational economy were established considering system flexibility margin expectations, vacancy expectations, and probability of deficiencies. Thirdly, the probabilistic optimal power flow model with flexibility resources was constructed, and the system state and index were estimated by the Monte Carlo simulation method and tracking center trajectory interior point method. Finally, analyzing the case of the IEEE RTS-24 system show that the appropriate allocation of renewable energy and energy storage systems could improve system flexibility and operating economy.
[1] |
张恒旭, 曹永吉, 张怡, 等. 电力系统频率动态行为衍变与分析方法需求综述[J]. 山东大学学报(工学版), 2021, 51(5): 42−52.
ZHANG Hengxu, CAO Yongji, ZHANG Yi, et al. Review of frequency dynamic behavior evolution and analysis method requirements of pow er system [J]. Journal of Shandong University (Engineering Science), 2021, 51(5): 42−52.(in Chinese).
|
[2] |
ZHAO Jinye, ZHENG Tongxin, LITVINOV Eugene. A unified framework for defining and measuring flexibility in power system[J]. IEEE Transactions on Power Systems, 2016, 31(1): 339−347. doi: 10.1109/TPWRS.2015.2390038
|
[3] |
LANNOYE E, FLYN D, O'MALLEY M, Transmission, variable generation, and power system flexibility[J]. IEEE Transactions on Power Systems, 2015, 30(1): 57-66.
|
[4] |
曹永吉, 张恒旭, 施啸寒, 等. 规模化分布式能源参与大电网安全稳定控制的机制初探[J]. 电力系统自动化, 2021, 45(18): 1−8.
CAO Yongji, ZHANG Hengxu, SHI Xiaohan, et al. Preliminary study on participation mechanism of large-scale distributed energy resource in security and stability control of large power grid[J]. Automation of Electric Power Systems, 2021, 45(18): 1−8(in Chinese).
|
[5] |
IEA. Empowering variable renewables-options for flexible electricity systems[R]. Paris, France: International Energy Agency, 2008.
|
[6] |
NERC. Special report: accommodating high levels of variable generation[R]. Princeton, American: North American Electric Reliability Corporation, 2008.
|
[7] |
NERC. Special report: flexibility requirements and potential metrics for variable generation: implications for system planning studies[R]. Princeton, American: North American Electric Reliability Corporation, 2010.
|
[8] |
鲁宗相, 李海波, 乔颖. 含高比例可再生能源电力系统灵活性规划及挑战[J]. 电力系统自动化, 2016, 40(13): 147−158.
LU Zongxiang, LI Haibo, QIAO Ying. Power system flexibility planning and challenges considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2016, 40(13): 147−158(in Chinese).
|
[9] |
肖定垚, 王承民, 曾平良, 等. 电力系统灵活性及其评价综述[J]. 电网技术, 2014, 38(6): 1569−1576.
XIAO Dingyao, WANG Chengmin, ZENG Pingliang, et al. A survey on power system flexibility and its evaluations[J]. Power System Technology, 2014, 38(6): 1569−1576(in Chinese).
|
[10] |
施涛, 朱凌志, 于若英. 电力系统灵活性评价研究综述[J]. 电力系统保护与控制, 2016, 44(5): 146−154.
SHI Tao, ZHU Lingzhi, YU Ruoying. Overview on power system flexibility evaluation[J]. Power System Protection and Control, 2016, 44(5): 146−154(in Chinese).
|
[11] |
马汝祥, 姚康宁, 邵林, 等. 考虑场景聚类的配电网运行灵活性评价[J]. 电力需求侧管理, 2021, 23(3): 86−91.
MA Ruxiang, YAO Kangning, SHAO Lin, et al. Operational flexibility evaluation of distribution network considering scenario clustering[J]. Power Demand Side Management, 2021, 23(3): 86−91(in Chinese).
|
[12] |
陈垚煜, 江全元, 周自强, 等. 考虑典型场景的配电网调控方案灵活性评估方法[J]. 电力建设, 2014, 40(7): 34−40.
CHEN Yaoyu, JIANG Quanyuan, ZHOU Ziqiang, et al. An evaluation method on the flexibility of regulation methods in distribution network considering typical scene sets[J]. Electric Power Construction, 2014, 40(7): 34−40(in Chinese).
|
[13] |
鲁宗相, 李海波, 乔颖. 高比例可再生能源并网的电力系统灵活性评价与平衡机理[J]. 中国电机工程学报, 2017, 37(1): 9−20.
LU Zongxiang, LI Haibo, QIAO Ying. Flexibility Evaluation and supply/demand balance principle of power system with high-penetration renewable electricity[J]. Proceedings of the CSEE, 2017, 37(1): 9−20(in Chinese).
|
[14] |
周光东, 周明, 孙黎滢, 等. 含波动性电源的电力系统运行灵活性评价方法研究[J]. 电网技术, 2019, 43(6): 2139−2146.
ZHOU Guangdong, ZHOU Ming, SUN Liying, et al. Research on operational flexibility evaluation approach of power system with variable sources[J]. Power System Technology, 2019, 43(6): 2139−2146(in Chinese).
|
[15] |
白帆, 陈红坤, 陈磊, 等. 基于确定型评价指标的电力系统调度灵活性研究[J]. 电力系统保护与控制, 2020, 48(10): 52−60.
BAI Fan, CHEN Hongkun, CHEN Lei, et al. Research on dispatching flexibility of power system based on deterministic evaluation index[J]. Power System Protection and Control, 2020, 48(10): 52−60(in Chinese).
|
[16] |
詹勋淞, 管霖, 卓映君, 等. 基于形态学分解的大规模风光并网电力系统多时间尺度灵活性评估[J]. 电网技术, 2019, 43(11): 3890−3901.
ZHAN Xunsong, GUAN Lin, ZHUO Yingjun, et al. Multi-scale flexibility evaluation of large-scale hybrid wind and solar grid-connected power system based on multi-scale morphology[J]. Power System Technology, 2019, 43(11): 3890−3901(in Chinese).
|
[17] |
GLAZUNOVA A, SEMSHIKOV E, NEGNEVITSKY M. Real-time flexibility assessment for power systems with high wind energy penetration[J]. Mathematics, 2021, 9(17): 1-16. doi: 10.3390/math9172056
|
[18] |
赵龙, 李文升, 曹永吉, 等. 计及源荷匹配特性的新能源可信容量评估方法[J]. 现代电力, 2023, 40(5): 687-695
ZHAO Long, LI Wensheng, CAO Yongji, et al. Renewable energy credible capacity assessment method considering source-load matching characteristics[J]. Modern Electric Power, 2023, 40(5): 687-695(in Chinese).
|
[19] |
赵书强, 金天然, 李志伟, 等. 考虑时空相关性的多风电场出力场景生成方法[J]. 电网技术, 2019, 43(11): 3997−4004.
ZHAO Shuqiang, JIN Tianran, LI Zhiwei, et al. Wind power scenario generation for multiple wind farms considering temporal and spatial correlations [J]. Power System Technology, 2019, 43(11): 3997−4004(in Chinese).
|
[20] |
魏联滨, 王伟臣, 李慧, 等. 基于AP聚类和鲁棒优化的电网规划灵活性评估[J]. 电力系统及其自动化学报, 2020, 32(3): 99−106.
WEI Lianbin, WANG Weichen, LI Hui, et al. Evaluation on grid planning flexibility based on affinity propagation clustering and robust optimization[J]. Proceedings of the CSU-EPSA, 2020, 32(3): 99−106(in Chinese).
|
[21] |
袁振华, 刘晓明, 杨金叶, 等. 风-光可再生能源场站群分层分区并网规划方法[J]. 现代电力, 2023, 40(5): 660-668.
YUAN Zhenhua, LIU Xiaoming, YANG Jinye et al. Planning method for layered and partitioned integration of wind-solar renewable energy clusters[J]. Modern Electric Power, 2023, 40(5): 660-668(in Chinese).
|
[22] |
赵书强, 要金铭, 李志伟. 基于改进K-means聚类和SBR算法的风电场景缩减方法研究[J]. 电网技术, 2021, 45(10): 3947−3954.
ZHAO Shuqiang, YAO Jinming, LI Zhiwei. Wind power scenario reduction based on improved k-means clustering and SBR algorithm[J]. Power System Technology, 2021, 45(10): 3947−3954(in Chinese).
|
[23] |
王俊, 李霞, 周昔东, 等. 基于VMD和LSTM的超短期风速预测[J]. 电力系统保护与控制, 2020, 48(11): 45−52.
WANG Jun, LI Xia, ZHOU Xidong, et al. Ultra-short-term wind speed prediction based on VMD-LSTM[J]. Power System Protection and Control, 2020, 48(11): 45−52(in Chinese).
|