4.6 Article

Optimal phasor measurement unit placement for power system observability using teaching-learning based optimization

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ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2021.107775

Keywords

Optimal PMU placement(OPP); Phasor measurement unit (PMU); Smart grid (SG); Teaching learning-based optimization (TLBO); wide-area monitoring system (WAMS) and zero; injection bus (ZIB)

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This paper presents an optimal PMU placement technique that considers data traffic and installation cost index, and uses the TLBO technique to obtain optimal PMU positions. By considering the zero injection bus case, the PMU count and installation cost can be reduced.
A Phasor measurement unit (PMU) is a device that gives a fast and accurate measurement of both current and voltage with time synchronization. This PMU data facilitates effective monitoring and control of power systems in a smart grid (SG). PMU collects data from various buses linked with it and led to an increase in the data generation of the particular PMU and it encourages cramming in data transmission. The delay in data reception at the control centre affects the performance of the SG protection. In a wide-area monitoring system (WAMS), the data traffic model is introduced to calculate the data traffic index. The net traffic can be reduced by installing the PMUs at suitable buses such that the number of PMUs must be reduced which, minimizes the system cost. This paper presents the optimal PMU placement technique with complete system observability by considering the WAMS data traffic index and installation cost index. The teaching learning-based optimization (TLBO) technique is used to obtain optimal PMU positions. In addition, the zero injection bus (ZIB) case is considered for further reduction in the PMU count which in turn reduces installation cost. The selection of an appropriate PMU location set is identified based on the installation cost and WAMS data traffic for normal and ZIB cases. The proposed optimum PMU placement (OPP) algorithm is tested on various test systems such as IEEE 14-bus, 24-bus, 30-bus, 57-bus, and 118-bus systems for normal and ZIB cases. The MATLAB-based simulation results are compared with the various optimization techniques existing in the state of art. The results show that the effectiveness of the proposed methodology for determining the best PMU locations.

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