Multi‐objective salp swarm algorithm‐based fractional order fuzzy precompensated PDPI controller for frequency regulation of hybrid power system

• Published in: International journal of numerical modelling Vol. 36; no. 5
• Main Authors: Mohanty, Debidasi, Panda, Sidhartha
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Inc 01.09.2023; Wiley Subscription Services, Inc
• Subjects: Algorithms; Controllers; Distributed generation; Electrical loads; Energy storage; fractional order fuzzy precompensated PDPI controller; Frequency control; Frequency deviation; Frequency stability; Fuzzy control; hybrid power system; Hybrid systems; load frequency control; multi‐objective salp swarm algorithm; Proportional integral derivative
• ISSN: 0894-3370; 1099-1204
• DOI: 10.1002/jnm.3094

Significant number of renewable sources when integrated with distributed generations and energy storage components form a sustainable power system called hybrid power system (HPS). But the stochastic nature of the sources and continuous variation of load cause serious issues in the power systems like frequency instability. Our work proposes a novel approach for load frequency control (LFC) of the proposed system. For the work, both frequency deviation and control signal are used to give the input signal to energy storage components. A new fuzzy‐based controller called fractional order fuzzy precompensated PDPI (FO‐FPPDPI) controller for LFC of the mentioned HPS is suggested in this paper. The controller is optimized by a nature inspired multi‐objective salp swarm algorithm (MSSA). The comparison of the proposed approach with the classical PID controller and Fuzzy PID (FPID) controller is carried out by taking several system operating conditions. Robustness of the FO‐FPPDPI controller is also validated for system parameter variations and the superiority of the proposed control strategy over PID and FPID controllers is validated for all the situations. Finally, the control strategy is realized in OPAL‐RT to measure its fidelity with the simulation results.