Novel application of optimal fuzzy-adaptive symbiotic organism search-based two-degree-of-freedom fuzzy proportional integral derivative controller for automatic generation control study

摘要

A knowledgeable and intelligent control strategy for automatic generation control (AGC) is required to supply reliable, secure, and stable power in most complex power system. So a proficient controller for AGC is indispensable to supply quality power with frequent load demand divergence. A novel two degree of freedom optimized fuzzy PID (2DOF OFPID) controller is proposed for the purpose to counterbalance generation and demand power expeditiously. This proposed controller is incorporated by blending the benefits of 2DOF PID and optimized fuzzy logic controller (FLC). The parameters and rules of proposed controller are decided by symbiotic organism search (SOS) and proposed passing vehicle search optimized fuzzy-based SOS (PVSOFSOS) algorithms. In this work, the decisive parameters of SOS algorithm are decided by FLC. The rules of FLC in proposed algorithm are decided by PVS algorithm. The preeminence of proposed algorithm over SOS and PVS algorithms is demonstrated by resolving 12 benchmark functions (constraint and unconstrained). Further, the proposed approaches are implemented in two-area and three-area thermal power systems with load variation enforced in area 1. The effectiveness of the proposed approaches are graded by conceding maximum undershoot/overshoot and settling time. Sensitivity analysis of the system with proposed optimal controller is validated with large variations of system parameters. It is observed that PVSOFSOS-based 2DOF OFPID controller proposed for AGC is more adequate as compared to some recently proposed techniques.