Unit Commitment with Energy Storage Considering Operation Flexibility at Sub-hourly Time-scales

被引：0
|
作者：
Zhang L. [1 ]
Yang J. [2 ]
Jian X. [1 ]
Zhang F. [1 ]
Han X. [1 ]
机构：
[1] Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University), Jinan
[2] State Grid Qingdao Electric Power Company, Qingdao
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2018年 / 42卷 / 16期
基金：
中国国家自然科学基金;
关键词：
Energy storage; Operational flexibility; Sub-hourly time-scale; Unit commitment (UC);
D O I：
10.7500/AEPS20170930007
中图分类号：
学科分类号：
摘要：
The integration of large-scale renewable energy aggravates the burden of frequency regulation for power grid, so the power system is required to be more capable of following power changes timely, that means higher demand for operational flexibility at sub-hourly time-scales. Thus this paper proposes a unit commitment (UC) model with energy storage considering operational flexibility at sub-hourly time-scales. Based on the analysis of range characteristics of the net load, the operational flexibility constraints are set according to the key scenarios of net load fluctuation. Therefore day-ahead dispatch in hourly time-scale is tied with sub-hourly operational flexibility requirements in UC. Meanwhile, the principles and restrictive factors of energy storage in different running states of charging, discharging and non-charging-and-non-discharging are discussed. Then the flexibility provided by energy storage is modeled and added to the system energy and power balance equation and operational flexibility constraints, respectively. Therefore the model of UC integrated with optimal deployment of energy storage is developed. By linearized processing, the model is reformed as a mixed integer linear programming (MILP) problem for solving. Simulations show that the proposed method can significantly improve the operational flexibility of power system at sub-hourly time-scales by using energy storage optimally. This work is supported by National Natural Science Foundation of China (No. 51477091). © 2018 Automation of Electric Power Systems Press.
引用
收藏
页码：48 / 56
页数：8
相关论文
共 35 条
  • [1] Liu Z., Golbal Energy Internet, (2015)
  • [2] Ela E., O'malley M., Studying the variability and uncertainty impacts of variable generation at multiple timescales, IEEE Transactions on Power Systems, 27, 3, pp. 1324-1333, (2012)
  • [3] Lin W., Wen J., Ai X., Et al., Probability density function of wind power variations, Proceedings of the CSEE, 32, 1, pp. 38-46, (2012)
  • [4] Xue Y., Yu C., Zhao J., Et al., A review on short-term and ultra-short-term wind power prediction, Automation of Electric Power Systems, 39, 6, pp. 141-151, (2015)
  • [5] Han M., Cui J., Yao S., Et al., Frequency control characteristics for a power system with large amounts of wind power, Automation of Electric Power Systems, 32, 1, pp. 29-33, (2008)
  • [6] Ding L., Qiao Y., Lu Z., Et al., Impact on frequency regulation of power system from wind power with high penetration, Automation of Electric Power Systems, 38, 14, pp. 1-8, (2014)
  • [7] Nosair H., Bouffard F., Reconstructing operating reserve: flexibility for sustainable power systems, IEEE Transactions on Sustainable Energy, 6, 4, pp. 1624-1637, (2015)
  • [8] Ortega-Vazquez M.A., Kirschen D.S., Estimating the spinning reserve requirements in systems with significant wind power generation penetration, IEEE Transactions on Power Systems, 24, 1, pp. 114-124, (2009)
  • [9] Papavasiliou A., Oren S.S., O'neill R.P., Reserve requirements for wind power integration: a scenario-based stochastic programming framework, IEEE Transactions on Power Systems, 26, 4, pp. 2197-2206, (2011)
  • [10] Matos M.A., Bessa R.J., Setting the operating reserve using probabilistic wind power forecasts, IEEE Transactions on Power Systems, 26, 2, pp. 594-603, (2011)
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