ILP-based multistage placement of PMUs with dynamic monitoring constraints |
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| Affiliation: | 1. Department of Electrical Engineering and Electronics, School of Engineering, Universidad de los Andes, Bogotá, Colombia;2. School of Electrical Technology, Universidad Tecnológica de Pereira, Pereira, Colombia;1. School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, Australia;2. Electrical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran;3. Department of Industrial Engineering, University of Salerno, Fisciano, Italy;4. Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran;5. Department of Electrical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran;1. Department of Electrical Engineering, Indian School of Mines, Dhanbad, Jharkhand, India;2. Department of Electrical Engineering, Galgotias University, G B Nagar, Uttar Pradesh, India;1. Center of Excellence for Power Systems Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran;2. Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran;1. Universidad De La Salle, Cra 2 10-70, Bogota, Colombia;2. XM Filial de ISA, Calle 12 Sur 18-168, Medellin, Antioquia, Colombia;3. Universidad Tecnologica de Pereira, Complejo Educativo La Julita, Pereira, Risaralda, Colombia;1. School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China;2. School of Economics and Management, Beijing University of Technology, Beijing, 100124, China;3. Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Sask, S4S 0A2, Canada |
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| Abstract: | This paper addresses two aspects of the optimal Phasor Measurement Unit (PMU) placement problem. Firstly, an ILP (Integer Linear Programing) model for the optimal multistage placement of PMUs is proposed. The approach finds the number of PMUs and its placement in separate stages, while maximizing the system observability at each period of time. The model takes into account: the available budget per stage, the power system expansion along with the multistage PMU placement, redundancy in the PMU placement against the failure of a PMU or its communication links, user defined time constraints for PMU allocation, and the zero-injection effect. Secondly, it is proposed a methodology to identify buses to be observed for dynamic stability monitoring. Two criteria, which are inter-area observability and intra-area observability, have been considered. The methodology identifies coherent groups in large power systems by using a new technique based on graph theory. The technique requires neither full stability studies nor a predefined number of groups. Also, a centrality criterion is used to select a bus for monitoring each coherent area and supervise inter-area oscillations. Then, PMUs are located to ensure complete observability inside each area (intra-area monitoring). Methodology is applied on the 14-bus test system, the 57-bus test system with expansion plans, and the 16-machine 68 bus test system. Results indicate that the optimization model finds the optimal number of PMUs when the PMU placement by stages is required, while the observability at each stage is maximized. Additionally, it is shown that expansion plans and particular requirements of observability can be considered in the model without increasing the number of required PMUs, and the zero-injection effect, which reduces the number of PMUs, can be considered in the model. |
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| Keywords: | Phasor Measurement Unit (PMU) Multistage PMU placement Observability Integer Linear Programming (ILP) Coherency recognition Community detection |
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