Application of HSA and GA in Optimal Placement of FACTS Devices Considering Voltage Stability and Losses
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Application of HSA and GA in Optimal Placement of FACTS Devices Considering Voltage Stability and Losses

Authors: A. Parizad, A. Khazali, M. Kalantar

Abstract:

Voltage collapse is instability of heavily loaded electric power systems that cause to declining voltages and blackout. Power systems are predicated to become more heavily loaded in the future decade as the demand for electric power rises while economic and environmental concerns limit the construction of new transmission and generation capacity. Heavily loaded power systems are closer to their stability limits and voltage collapse blackouts will occur if suitable monitoring and control measures are not taken. To control transmission lines, it can be used from FACTS devices. In this paper Harmony search algorithm (HSA) and Genetic Algorithm (GA) have applied to determine optimal location of FACTS devices in a power system to improve power system stability. Three types of FACTS devices (TCPAT, UPFS, and SVC) have been introduced. Bus under voltage has been solved by controlling reactive power of shunt compensator. Also a combined series-shunt compensators has been also used to control transmission power flow and bus voltage simultaneously. Different scenarios have been considered. First TCPAT, UPFS, and SVC are placed solely in transmission lines and indices have been calculated. Then two types of above controller try to improve parameters randomly. The last scenario tries to make better voltage stability index and losses by implementation of three types controller simultaneously. These scenarios are executed on typical 34-bus test system and yields efficiency in improvement of voltage profile and reduction of power losses; it also may permit an increase in power transfer capacity, maximum loading, and voltage stability margin.

Keywords: FACTS Devices, Voltage Stability Index, optimal location, Heuristic methods, Harmony search, Genetic Algorithm.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1061788

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