Thursday, November 27, 2014

GA-based Congestion Management in Deregulated Power System using FACTS Devices || IEEE project

Posted by EDUCATIONS 360 at 3:42 PM 0 Comments
Abstract--Congestion in the transmission lines is one of the technical problems that appear particularly in the deregulated environment. There are two types of congestion management methodologies to relieve it. One is non-cost free and the other is cost free methods. Among them later method relives the congestion technically whereas the former is related with the economics. In this dissertation congestion is relieved using cost free method. One of the cost free techniques is installing FACTS devices into the system. FACTS devices have a great flexibility that can control the active power, reactive power and voltage simultaneously. SVC and UPFC are two FACTS devices which can relieve the congestion in the transmission lines efficiently. As the FACTS devices are costly hence it is required to find the optimal location for FACTS devices. In congestion management, the objective function is nonlinear hence in solving this function Genetic Algorithm (GA) technique is used to obtain the global optimal solution. This method is tested on IEEE test bus system with FACTS devices and it can be extended to any practical system.

Power system facts
genetic algorithm flowchart

To relieve the congestion in the lines multiple multi-types off ACTS devices are located optimally using genetic algorithm. The following conclusions have been derived:
• With the above proposal it is possible for ISO to find global optimal schedule with the minimum total generation cost.
• In some transmission lines power flows with the OPF generation schedule are very high. Such extra power flow scan be reduced by installing FACTS devices.
• Line loading with SVC is less as compared with the line loading with UPFC.
• It has also been observed that proposed algorithm is also suitable for large systems with more number of FACTS devices, and the results so obtained are found to be encouraging.

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