Generation‐based automatic generation control with multisources power system using bacterial foraging algorithm. Issue 8 (10th August 2020)

• Record Type: Journal Article
• Authors: Hakimuddin, Nizamuddin; Nasiruddin, Ibraheem; Bhatti, Terlochan Singh
• Is Part Of: Engineering reports. Volume 2:Issue 8(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-10
• Subjects: automatic generation control -- multisources power system -- generation‐based controller -- bacterial foraging algorithm; Engineering -- Periodicals; Computer science -- Periodicals; 620.005
• DOI: 10.1002/eng2.12191
• Languages: English
• ISSNs: 2577-8196

Abstract

Abstract: This article presents an application of bacterial foraging algorithm (BFA) for design and implementation of generation‐based PID structured automatic generation control (AGC) in a 2‐area multisources power system with hydro, thermal, and gas power plants incorporated in each area. Most of AGC studies carried out so far have considered the initial system loading to be equal to 50% of the area generation capacity. But, AGC controller parameters are uncertain due to stochastic nature of power demand of the end users. Hence, in this article, the design of AGC controller is proposed on the basis of generation schedule by incorporating changes in power system gain constant, power system time constant, frequency bias constant, and so on. The dynamic responses of power system with BFA tuned AGC controller are compared with the genetic algorithm tuned AGC controller. The parameters of the controllers are evaluated by using these techniques and investigations are carried out to find the best performance of the system. Therefore, it is desirable to find the parameters of the generation‐based controller depending upon the contribution of its constituent hydro, thermal, and gas energy sources in the total power generation. Abstract : AGC is a most essential application of the control system engineering in power systems. The design parameters of AGC controller depend upon its constituent hydro, thermal, and gas energy sources in total power generation. Bacterial foraging algorithm can play a significant role to design generation‐based AGC controllers in interconnected power systems.