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Comparative Analysis on Power Transmission Congestion Management using Evolutionary Algorithms, Hybrid Model under Overload and Contingency Conditions
Abstract
The power system is said to be in balanced state if generated power is equal to demand ideally. Here demand comprises of industrial loads, commercial loads, infrastructure, domestic loads, critical loads, etc. Due to increase in population the demand of electricity is also increasing drastically. Due to increase in demand, there is a considerable effect on power carrier (transmission lines) connecting generating stations and loads in the form of congestion. Since, if there is increase in demand the transmission lines must carry the power sometimes it can be more than its maximum power transfer limit and may cause protective system to operate to protect the transmission line this may divert the power in adjacent transmission lines and may lead to cascade outages. Similar situation can be experienced under contingency conditions as well. However, these effects can be overcome if series FACTS device (Thyristor Controlled Series Capacitor) is installed in the transmission system. In this paper a control algorithm is proposed to change the reactance of transmission line based on power carrying capacity at that instant using TCSC. This algorithm has been integrated with Evolutionary Algorithms like PSO and GA separately for optimal design of TCSC. In this paper a comparative analysis is also done on the performance of PSO, GA and Hybrid Model on 14 bus system under overloading condition, contingency condition. Initially, in this work the control algorithm is tested in 5 bus test system and then control algorithm along with EA technologies (PSO, GA and Hybrid Model) is tested on 14 bus test system.
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