Abstract
Automatic generation control systems are designed to adjust electric power outputs of multiple generators simultaneously in accordance with the current load. However, the control instruction and the main steam pressure have significant impacts on the resulting active power generation of a conventional thermal generator, and the impacts may be associated with nonlinear characteristics. As a result, the control instruction requires an accurate modeling of the relationship between these three variables for a satisfactory control performance. This paper proposes a method to build a piecewise linear model for the nonlinear relationship from steady-state data hidden in historical data samples. The proposed method is composed by two main steps of steady-state interval detection and steady-state data segmentation. Historical data samples are grouped using the k-means clustering algorithm, and the time domains of each cluster are merged in a specific way to obtain the steady-state intervals. The steady-state data are taken as the samples means of data in the steady-state intervals. A bottom-up algorithm is utilized to partition the steady-state data into numbers of sets iteratively, and the parameters of the piecewise linear model for each data set are estimated by the least squares algorithm. The effectiveness of the proposed method is illustrated via industrial applications to two thermal power generation units.
Highlights
Automatic generation control (AGC) systems perform an important role in electric power systems by adjusting the active power generation in response to the load demand, and maintaining the scheduled system frequency and tieline power flows with neighboring control areas at desired tolerance values [1]–[3]
The process variables Qsp, U, Q and P are the electric power required from power grids, the AGC instruction, the generated power and the main steam pressure, respectively
This paper proposed a method to describe a nonlinear relationship among the control instruction, the main steam pressure, and the active power output for an AGC system
Summary
Automatic generation control (AGC) systems perform an important role in electric power systems by adjusting the active power generation in response to the load demand, and maintaining the scheduled system frequency and tieline power flows with neighboring control areas at desired tolerance values [1]–[3]. MAIN IDEA As discussed, the magnitude and duration of a variation are important features denoting steady-state intervals Specific algorithms are generally required to identify regions having small amplitude variations with sufficiently long durations in an automatic manner To this end, this paper takes an automatic search method being composed by four main steps. Tsi and tei respectively represent the starting and ending time instances for the ith interval It certainly satisfies an equality Max Q(tsi : tei ) − Min Q(tsi : tei ) ≤ W , where Max() and Min() respectively represent the maximal and minimal values of the data set Q(tsi : tei ).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
