Secured loadability enhancement with TCSC in transmission system using computational intelligence techniques for pool and hybrid model
This paper proposes an algorithm for the optimal location and control of Flexible AC Transmission System (FACTS) devices for enhancing the loadability in transmission system using particle swarm optimization (PSO) and differential evolution (DE) for pool and hybrid model in deregulated electricity market. This approach uses AC load flow equations with the constraints on power generation, transmission line flow, magnitude of bus voltages and FACTS device settings. The bilateral transactions are modeled using secured bilateral transaction matrix utilizing AC distribution factor with the slack bus contribution. In this proposed approach, Thyristor Controlled Series Compensator (TCSC) is used. To validate the proposed approach, simulations are performed on 39 bus New England test system and IEEE 118 bus system. Comparisons are made in terms of maximum loadability, computation time and convergence characteristics. The simulation result obtained indicates that by optimal location and control of TCSC, using DE, enhances the loadability in transmission system with less computation time and faster convergence than using PSO. This comparative study concludes that by optimal location and control of TCSC, using DE will be more effective for secured loadability enhancement in transmission system of pool and hybrid model in deregulated electricity market.
hybrid model particle swarm optimization differential evolution secured bilateral transaction matrix thyristor controlled series compensator maximum loadability pool model