Assessment of automatic generation control performance of power generation units based on amplitude changes. (June 2019)

• Record Type: Journal Article
• Authors: Wang, Jiandong; Pang, Xiangkun; Gao, Song; Zhao, Yan; Cui, Shijun
• Is Part Of: International journal of electrical power & energy systems. Volume 108(2019)
• Page Start: 19
• Page End: 30
• Publication Date: 2019-06
• Subjects: Performance assessment -- Automatic generation control -- Power generation units -- Piece-wise linear representations -- Amplitude changes; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2018.12.046
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A new method is proposed to assess the AGC performance of a power generation unit. The performance is on the amplitude changes of generated and desired active powers. Amplitude changes are calculated from piece-wise linear representations of signals. A threshold of significant amplitude changes is determined via an analytic relation. Industrial examples from a power generation unit are provided. Abstract: Automatic generation control (AGC) is an important auxiliary service provided by power generation units, such that generated active powers closely follow the changes of desired active powers as required by power grids. This paper proposes a new method to assess the AGC performance of a power generation unit by comparing amplitude changes of generated and desired active powers. Time sequences of generated and desired active powers are separated into short straight lines, from which their amplitude changes are obtained. If the difference between amplitude changes of generated and desired active powers are larger than the threshold of significant amplitude changes, then the performance is regarded to be unsatisfactory. As a critical parameter, the significant threshold of amplitude changes is determined by a relationship between the amplitude change and a so-called R-squared statistic. An alarm variable is introduced to indicate the performance status, and a performance index is formulated as the sample mean of the alarm variable. The unsatisfactory performance is classified into six abnormal scenarios based on the amplitude changes for a further analysis. Industrial examples are provided to illustrate the effectiveness of the proposed method.