A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system

• Published in: International journal of electrical power & energy systems 2016-01, Vol.74, p.58-69
• Main Authors: Sahu, Binod Kumar, Pati, Tridipta Kumar, Nayak, Jyoti Ranjan, Panda, Sidhatrha, Kar, Sanjeeb Kumar
• Format: Article
• Language: English
• Subjects: Fuzzy logic controller (FLC); Load frequency control (LFC); Local Unimodal Sampling (LUS); Teaching Learning Based Optimization (TLBO)
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2015.07.020

•Design and use of fuzzy-PID controller for LFC of interconnected power system.•Maiden application of hybrid LUS–TLBO optimization algorithm.•Superiority of proposed hybrid optimization technique and controller is proved.•Robustness of the proposed controller is proved on the basis of statistical study. In this paper, a novel hybrid Local Unimodal Sampling (LUS) and Teaching Learning Based Optimization (TLBO) based fuzzy-PID controller is proposed for load frequency control (LFC) of a two-area interconnected multi-source power system with and without HVDC link. Each area of the multi-source power system consists of a reheat thermal, a hydro and a gas unit. Fuzzy-PID and conventional PID controllers are used to study the dynamic performance of the power system by applying a step load change of 0.01pu in area1. The scaling factors of the fuzzy-PID controllers and the conventional PID controllers’ gains are optimized using the proposed hybrid LUS and TLBO (LUS–TLBO) algorithm. The supremacy of the proposed LUS–TLBO algorithm optimized fuzzy-PID controller is proved for both the power systems (with and without HVDC link) by comparing the results with that of recently published article based on Differential Evolution (DE) algorithm optimized conventional PID controller for the same power systems. Again the robustness of the proposed controller for power system with AC tie-line only is studied under parametric variation conditions by varying all the parameters from −50% to 50% of their nominal values in steps of 25%. Finally it is seen that LUS–TLBO optimized fuzzy-PID controller exhibit superior performance as compared to DE optimized fuzzy-PID controller and hybrid LUS–TLBO, TLBO, LUS & DE optimized conventional PID controller.