Congestion Management by Generator Rescheduling and FACTS Devices using Multi Objective Genetic Algorithm

1 EEE Department, Kings College of Engineering, Punalkulam, Thanjavur, India. 2 Professor, EEE Department, Kalasalingam University, Krishnankoil, Virudhunagar (Dt.), India ----------------------------------------------------------------------------------------------------------------------------------------------------------Abstract: Congestion management is one of the key issues in Deregulated power system as the customers would like to purchase the electricity from the cheapest available sources. The Independent Power Producers (IPP) would like to derive more benefit out of their investments, engages with contracts that leads to overloading of the transmission elements of the power system. An Independent System Operator (ISO) coordinates the trades and make sure that the interconnected power system operates in a secure state at a minimum cost by meeting the all the load requirements and losses. In this work Congestion is mitigated by Generator Rescheduling and implementation of FACTS devices. Minimization of rescheduling costs of the generator and minimization of the cost of deploying FACTS devices are taken as the objectives of the given multi-objective optimization problem. Multi Objective Genetic Algorithm is used to solve this problem by implementing the series FACTS device namely TCSC. The proposed algorithm is tested on IEEE 30 bus system.