Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

3rd International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Zhao, Yan^1 ; Yang, Zijiang^2 ; Gao, Song^1 ; Liu, Jinbiao^3

State Grid Shandong Electric Power Research Institute, Jinan, China^1

College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China^2

Datang Linqing Thermal Power Co. Ltd, Liaocheng, China^3

关键词: Automatic generation control;    Industrial case study;    Nonlinear regression models;    Performance indices;    Power generation units;    Quality of power supply;    System identification techniques;    Thermal power generation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/113/1/012113/pdf
DOI  :  10.1088/1755-1315/113/1/012113

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.