Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 11, Issue 2, 2023 >479-488. DOI:10.35833/MPCE.2022.000003
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Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints
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Affiliation:

1. Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China2. Shenzhen Research Institute of Xiamen University, Shenzhen, China 3. CTC Intelligence (Shenzhen) Technology Co., Ltd., Shenzhen, China 4. Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK 5. Cambridge Centre for Advanced Research and Education in Singapore, CREATE Tower, Singapore 6. School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 7. Department of Engineering, University of Cambridge, UK

Fund Project:

This work was supported by the National Natural Science Foundation of China (No. 61903314), Basic Research Program of Science and Technology of Shenzhen, China (No. JCYJ20190809162807421), Natural Science Foundation of Fujian Province (No. 2019J05020), and National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.

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    Abstract:

    The distribution of measurement noise is usually assumed to be Gaussian in the optimal phasor measurement unit (PMU) placement (OPP) problem. However, this is not always accurate in practice. This paper proposes a new OPP method for smart grids in which the effects of conventional measurements, limited channels of PMUs, zero-injection buses (ZIBs), single PMU loss contingency, state estimation error (SEE), and the maximum SEE variance (MSEEV) are considered. The SEE and MSEEV are both obtained using a robust t-distribution maximum likelihood estimator (MLE) because t-distribution is more flexible for modeling both Gaussian and non-Gaussian noises. The A- and G-optimal experimental criteria are utilized to form the SEE and MSEEV constraints. This allows the optimization problem to be converted into a linear objective function subject to linear matrix inequality observability constraints. The performance of the proposed OPP method is verified by the simulations of the IEEE 14-bus, 30-bus, and 118-bus systems as well as the 211-bus practical distribution system in China.

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History
  • Received:January 06,2022
  • Revised:April 25,2022
  • Online: March 25,2023

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