Abstract
Optimal setting and location of Flexible AC Transmission Systems (FACTS) devices are widely used in enhancing power system security. The most effective FACTS device is Unified Power Flow Controller (UPFC) which has both series and shunt compensation. The effectiveness of FACTS device over the mitigation of security issues depends on its location and its parameter settings. Hence, this paper presents Ant Colony Optimization (ACO) methodology to optimally locate UPFC to enhance power system security under single contingencies (N-1 Contingency). The simulation is carried out on IEEE 6 bus and IEEE 14 bus test systems considering line over loads and bus voltage violations for ensuring system security. This approach is twofold. Initially, an N-1 contingency test is performed based on severity ranking is done then UPFC is placed optimally using ACO algorithm to mitigate the severity. Further to validate the proposed approach the results are compared with the conventional Non Linear Programming – Interior Point (NLP-IP) technique.
Highlights
In the present day power scenario with the ever increasing demand, the power utilities are looking for ways to maximize the utilization of their existing transmission system
The fundamental approach underlying Ant Colony Optimization (ACO) is an iterative process in which a population of simple agents repeatedly construct candidate solutions; this construction process is probabilistically guided by heuristic information on the given problem instance as well as by a shared memory containing experience gathered by the ants in previous iteration [18]-[20]
It is understand from available literatures, very few research works has been reported based on mitigation of power system security using Unified Power Flow Controller (UPFC) with ACO algorithms
Summary
In the present day power scenario with the ever increasing demand, the power utilities are looking for ways to maximize the utilization of their existing transmission system. The fundamental approach underlying ACO is an iterative process in which a population of simple agents repeatedly construct candidate solutions; this construction process is probabilistically guided by heuristic information on the given problem instance as well as by a shared memory containing experience gathered by the ants in previous iteration [18]-[20] It is understand from available literatures, very few research works has been reported based on mitigation of power system security using UPFC with ACO algorithms. This paper presents the application of ACO technique to find the optimal location and parameter settings of UPFC to enhance power system security constraints such as thermal limits of transmission lines and bus voltage limits under N-1 contingencies.
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