Maximum loadability assessment of deregulated power system based on evolutionary algorithms

Abstract

newlineThis work proposes the application of soft computing techniques to evaluate the optimal location and control settings of Flexible AC Transmission System in order to improve the Maximum Load ability ML of the pool as well as the hybrid structure of deregulated power system during scheduled outages like single N-1 and double N-2 contingencies Particle Swarm Optimization PSO Hybrid Particle Swarm Optimization HPSO Differential Evolution DE and Modified Differential Evolution MDE algorithms are applied Three different FACTS devices namely series type Thyristor Controlled Series Compensator TCSC shunt type Static Var Compensator SVC and series shunt type Unified Power Flow Controller UPFC are considered to reduce the Installation Cost IC and optimal location of these devices in the system based on priority indices like Contingency Severity Index CSI and Fast Voltage Stability Index FVSI The proposed approach uses flow equations as equality constraints and voltage real and VAR power settings of FACTS devices as inequality constraints Hybrid structure is modeled using bilateral transactions The problem is tested using Western System Coordinating Council WSCC 9 bus IEEE 30 bus IEEE 57 bus systems and optimized using Particle Swarm Optimization PSO Hybrid Particle Swarm Optimization HPSO Differential Evolution DE and Modified Differential Evolution MDE algorithms The numerical and graphical analysis shows that HPSO and MDE are comparatively superior in performance to PSO and DE respectively in locating and sizing of FACTS devices for identifying the ML.