Automatic Generation Control of Two Area Multi Source Power System Tuned the Fuzzy PID Using Hybrid Lus-PSO Optimization

Abstract

This study discloses AGC of multi-source multi area power systems, first time optimized by a technique which is the hybrid of local unimodal sampling and particle swarm optimization (Lus-PSO).  The controller parameters of Fuzzy PID and PID are compared in addition to FACTs devices are also proposed in this paper. In this case power system includes unlike engendering sources like thermal, hydro and gas plants. Initially this paper describes two area systems with the help of tie-line power control which may be AC tie line only or DC parallel to existing AC link using particle swarm optimization technique, but this technique has the disadvantage of prematurity so leads to a population based local search unimodal sampling which is able to handle the non-differentiable, nonlinear system with diversity.. A comparison is also made in this paper which states that HVDC system is more advantageous than AC tie line only with respect to transient stability that means low frequency oscillation. PID controller parameters are optimized by hybrid DEPSO method. Here further explaining the concept of fuzzy PID controller to an interconnected power system which is an intelligent based either range to range or range to point control. There are four scaling factors, optimized by hybrid Lus-PSO method. The dynamic assessments are compared through numerous simulations. Facts devices such as TCPS and SMES units are introduced here in this paper which enhances the power transfer capacity. Again a comparison is made between coordinated TCPS and SMES with the individuals.

Keywords: AGC: Automatic Generation Control, TCPS: Thyristor Controlled Phase Shifter, SMES: Super Magnetic Energy Storage, FPID: Fuzzy Proportional Integral Derivative, IPS: Interconnected Power Systems, DEPSO: Differential Evolution Particle Swarm Optimization