EconPapers    
Economics at your fingertips  
 

A Robust Fractional-Order PID Controller Based Load Frequency Control Using Modified Hunger Games Search Optimizer

Ahmed Fathy, Dalia Yousri, Hegazy Rezk, Sudhakar Babu Thanikanti and Hany M. Hasanien
Additional contact information
Ahmed Fathy: Electrical Engineering Department, Faculty of Engineering, Jouf University, Sakaka 42421, Saudi Arabia
Dalia Yousri: Department of Electrical Engineering, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt
Hegazy Rezk: College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
Sudhakar Babu Thanikanti: Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology (CBIT), Hyderabad 500075, India
Hany M. Hasanien: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt

Energies, 2022, vol. 15, issue 1, 1-25

Abstract: In this article, a recent modified meta-heuristic optimizer named the modified hunger games search optimizer (MHGS) is developed to determine the optimal parameters of a fractional-order proportional integral derivative (FOPID) based load frequency controller (LFC). As an interconnected system’s operation requires maintaining the tie-line power and frequency at their described values without permitting deviations in them, an enhanced optimizer is developed to identify the controllers’ parameters efficiently and rapidly. Therefore, the non-uniform mutation operator is proposed to strengthen the diversity of the solutions and discover the search landscape of the basic hunger games search optimizer (HGS), aiming to provide a reliable approach. The considered fitness function is the integral time absolute error (ITAE) comprising the deviations in tie-line power and frequencies. The analysis is implemented in two networks: the 1st network comprises a photovoltaic (PV) plant connected to the thermal plant, and the 2nd network has four connected plants, which are PV, wind turbine (WT), and 2 thermal units with generation rate constraints and governor dead-band. Two different load disturbances are imposed for two studied systems: static and dynamic. The results of the proposed approach of MHGS are compared with the marine predators algorithm (MPA), artificial ecosystem based optimization (AEO), equilibrium optimizer (EO), and Runge–Kutta based optimizer (RUN), as well as movable damped wave algorithm (DMV) results. Moreover, the performance specifications of the time responses of frequencies and tie-line powers’ violations comprising rise time, settling time, minimum/maximum setting values, overshoot, undershoot, and the peak level besides its duration are calculated. The proposed MHGS shows its reliability in providing the most efficient values for the FOPID controllers’ parameters that achieve the lowest fitness of 0.89726 in a rapid decaying. Moreover, the MHGS based system becomes stable the most quickly as it has the shortest settling time and is well constructed as it has the smallest peak, overshoots at early times, and then the system becomes steady. The results confirmed the competence of the proposed MHGS in designing efficient FOPID-LFC controllers that guarantee reliable operation in case of load disturbances.

Keywords: multi-interconnected system; load frequency control; FOPID; hunger games search optimizer; renewable energy plants (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/1/361/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/1/361/ (text/html)

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:gam:jeners:v:15:y:2022:i:1:p:361-:d:717767

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:15:y:2022:i:1:p:361-:d:717767