Multi-objective strategy for deep peak shaving of power grid considering uncertainty of new energy

被引：0
|
作者：
Ying Y. [1 ]
Wang Z. [2 ]
Wu X. [2 ]
Fu R. [1 ]
Xu J. [1 ]
机构：
[1] Nanjing University of Posts and Telecommunications, Nanjing
[2] Control Center of State Grid Anhui Electric Power Co., Ltd., Hefei
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2020年 / 48卷 / 06期
基金：
中国国家自然科学基金;
关键词：
deep peak shaving; multi-target; new energy consumption; random characteristics;
D O I：
10.19783/j.cnki.pspc.190597
中图分类号：
学科分类号：
摘要：
Under the trend of large-scale new energy grid-connected consumption, the random characteristics of power grid new power generation and system peaking margin need to be considered. Firstly, according to the non-parametric estimation theory, the stochastic characteristics of the new energy output are processed. Secondly, based on the deep peak-shaving process of the thermal power peak-shaving unit, the operating cost of the unit is analyzed and modeled. Then, a multi-objective optimal scheduling model considering the economic stability and peak shaving flexibility of the power grid is constructed, and the multi-objective power grid deep peaking operation optimization scheduling strategy considering the stochastic characteristics of the new energy output is proposed. Finally, based on the multi-objective solution method, the power system of 10 thermal power units and the actual grid operation data of a certain area are simulated and analyzed, and the effectiveness of the multi-objective scheduling strategy is analyzed. © 2020 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码：34 / 42
页数：8
相关论文
共 23 条
  • [1] ZHANG Gaohang, LI Fengting, ZHOU Qiang, Et al., Day-ahead hierarchical dispatching model considering friendliness of wind power, Power System Protection and Control, 47, 6, pp. 118-124, (2019)
  • [2] LI Gang, CHENG Chuntian, ZENG Yun, Et al., Practical study and application of thermal load distribution solved by improved equal incremental principle, Power System Protection and Control, 40, 2, pp. 72-76, (2012)
  • [3] CHEN Zhangchao, GAO Jiafen, Optimization of thermal generating set commitment and scheduling using dynamic programming, Automation of Electric Power Systems, 9, 1, pp. 21-29, (1985)
  • [4] ZHOU Le, LIANG Yanan, Study on power unit commitment for large scale wind power generating interconnected with power grid, Ningxia Electric Power, 3, pp. 63-70, (2016)
  • [5] ZHANG Haifeng, GAO Feng, WU Jiang, Et al., A dynamic economic dispatching model for power grid containing wind power generation system, Power System Technology, 37, 5, pp. 1298-1303, (2013)
  • [6] CHEN C L., Simulated annealing-based optimal wind-thermal coordination scheduling, IET Generation Transmission & Distribution, 1, 3, pp. 447-455, (2007)
  • [7] ZHOU Wei, SUN Hui, GU Hong, Et al., Dynamic economic dispatch of wind integrated power systems based on risk reserve constraints, Proceedings of the CSEE, 32, 1, pp. 47-55, (2012)
  • [8] HETZER J, YU D C, BHATTARAI K., An economic dispatch model incorporating wind power, IEEE Transactions on Energy Conversion, 23, 2, pp. 603-611, (2008)
  • [9] CUI Yang, YANG Zhiwen, ZHANG Jietan, Et al., Scheduling strategy of wind power-photovoltaic power-concentrating solar power considering comprehensive costs, High Voltage Engineering, 45, 1, pp. 269-275, (2019)
  • [10] YU Na, LI Weimeng, HUANG Dawei, Et al., Day-ahead scheduling model in wind power integrated system incorporating shiftable load, Power System Protection and Control, 46, 17, pp. 61-67, (2018)
123