Performance Estimation of Frequency Regulation for a Micro-Grid Power System Using PSO-PID Controller

D. Boopathi, S. Saravanan, K. Jagatheesan and B. Anand
Additional contact information
D. Boopathi: Paavai Engineering College, India
S. Saravanan: Muthyammal Engineering College, India
K. Jagatheesan: Paavai Engineering College, India
B. Anand: Hindusthan College of Engineering and Technology, India

International Journal of Applied Evolutionary Computation (IJAEC), 2021, vol. 12, issue 2, 36-49

Abstract: This paper proposes the particle swarm optimization (PSO) technique-based proportional integral derivative (PID) controller suggested for frequency regulation of a micro grid (MG) system. MG system integrates with thermal power generating units, renewable energy sources (RES) like photovoltaic (PV), wind energy generators (WTG), and Energy storage systems (ESS) such as fuel cell (FC) and battery energy storage system (BESS). Indentifying the supremacy of proposed technique-based controller and supremacy is examined with three objective functions (integral absolute error [IAE], integral time absolute error [ITAE], and integral squared error [ISE]). The results of the system are compared with conventional PID controller results. From the comparison, it is clearly evident that PSO-PID controller gives better performance over conventional methods in terms of various time domain specific parameters such as settling time, peak overshoot, and undershoot. In both methods, ITAE objective function used controller produce more effective response in MG under sudden load demand situation.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJAEC.2021040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:12:y:2021:i:2:p:36-49

Access Statistics for this article

International Journal of Applied Evolutionary Computation (IJAEC) is currently edited by Sukhpal Singh Gill

More articles in International Journal of Applied Evolutionary Computation (IJAEC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().