Coordinated optimal operation strategy of thermal power-energy storage considering demand response and life model of energy storage

被引：0
|
作者：
Chen Y. [1 ,2 ,3 ]
Wu C. [1 ]
Jiao Y. [1 ]
Sun Z. [1 ]
Dai S. [4 ]
Zhang P. [5 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing
[2] Qinghai Key Laboratory of Efficient Utilization of Clean Energy, Tus-Institute for Renewable Energy, Qinghai University, Xining
[3] School of Engineering, Xining University, Xining
[4] State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing
[5] Beijing Electric Power Economic and Technological Research Institute Co., Ltd., Beijing
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Coordinated optimal operation; Deep peak regulation; Demand response; Life model of energy storage; New energy consumption;
D O I：
10.16081/j.epae.202201012
中图分类号：
学科分类号：
摘要：
Aiming at the peak regulation and consumption problems caused by the large-scale grid-connected new energy, and the insufficient consideration of existing optimal scheduling strategy on the life cost of energy storage, a coordinated optimal operation strategy of thermal power-energy storage considering demand response and life model of energy storage is proposed. The upper layer guides the electricity consumption through time-of-use electricity price, and the optimized load curve is obtained with the goal of minimizing the fluctuation of net load, which aims to reduce the peak regulation pressure of thermal power-energy storage and improve the consumption of new energy. The lower layer coordinates and optimizes the operation of wind power, photovoltaic, thermal power and energy storage with the goal of minimizing the total scheduling cost of the system. Considering the deep peak regulation of thermal power and embedding the life model of energy storage in the optimal scheduling, the optimal operation mode of each power source and energy sto-rage is obtained. Taking an actual system in a certain area as the example, the results show that the proposed strategy can effectively improve the peak regulation pressure of the system, improve the consumption capacity of new energy, reasonably reflect the life cost of energy storage, and improve the operation economy of the system. © 2022, Electric Power Automation Equipment Press. All right reserved.
引用
收藏
页码：16 / 24
页数：8
相关论文
共 21 条
  • [1] ZHAO Dongyuan, HU Nan, FU Jing, Et al., Research on the practice and road map of enhancing the flexibility of a new generation power system in China, Power System Protection and Control, 48, 24, pp. 1-8, (2020)
  • [2] CHEN Y B, ZHAO J Y, MA J., Fast decoupled multi-energy flow calculation for integrated energy system, Journal of Modern Power Systems and Clean Energy, 8, 5, pp. 951-960, (2020)
  • [3] ZENG Ming, YANG Yongqi, XIANG Hongwei, Et al., Optimal dispatch model based on coordination between"generation-grid-load-energy storage" and demand-side resource, Electric Po-wer Automation Equipment, 36, 2, pp. 102-111, (2016)
  • [4] CHEN Y B, YAO Y, ZHANG Y., A robust state estimation method based on SOCP for integrated electricity-heat system, IEEE Transactions on Smart Grid, 12, 1, pp. 810-820, (2021)
  • [5] CHEN Y B, YAO Y, LIN Y Z, Et al., Dynamic state esti-mation for integrated electricity-gas systems based on Kalman filter, CSEE Journal of Power and Energy Systems
  • [6] LI Junhui, ZHANG Jiahui, MU Gang, Et al., Day-ahead optimal scheduling strategy of peak regulation for energy storage considering peak and valley characteristics of load, Electric Power Automation Equipment, 40, 7, pp. 128-133, (2020)
  • [7] DENG Tingting, LOU Suhua, TIAN Xu, Et al., Optimal dispatch of power system integrated with wind power considering demand response and deep peak regulation of thermal power units, Automation of Electric Power Systems, 43, 15, pp. 34-41, (2019)
  • [8] LI Benxin, HAN Xueshan, LIU Guojing, Et al., Thermal unit commitment with complementary wind power and energy sto-rage system, Electric Power Automation Equipment, 37, 7, pp. 32-37, (2017)
  • [9] QIAN Weiting, ZHAO Changfei, WAN Can, Et al., Probabilistic forecasting based stochastic optimal dispatch and control method of hybrid energy storage for smoothing wind power fluctuations, Automation of Electric Power Systems, 45, 18, pp. 18-27, (2021)
  • [10] LI Junhui, ZHANG Jiahui, MU Gang, Et al., Hierarchical optimization scheduling of deep peak shaving for energy-storage auxiliary thermal power generating units, Power System Technology, 43, 11, pp. 3961-3970, (2019)
123