Optimal Phasor Data Compression Unit Installation for Wide-Area Measurement Systems-An Integer Linear Programming Approach

Phasor measurement units (PMUs) are time-synchronous measuring devices that acquire highly accurate phasor data at high frequency. They are the core components in wide-area measurement systems for smart grid monitoring, protection, and control. However, they do generate much data and create a heavy...

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Veröffentlicht in:IEEE transactions on smart grid Jg. 7; H. 6; S. 2644 - 2653
Hauptverfasser: Wen, Miles H. F., Li, Victor O. K.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.11.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Data compression
Formulations
Frequency measurement
Integer linear programming
integer linear programming (ILP)
Integer programming
Linear programming
Monitoring
Optimization
phasor measurement unit (PMU)
Phasor measurement units
Phasors
power system monitoring
Smart grid
Smart grids
Traffic engineering
Traffic flow
ISSN:1949-3053, 1949-3061
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Zusammenfassung:Phasor measurement units (PMUs) are time-synchronous measuring devices that acquire highly accurate phasor data at high frequency. They are the core components in wide-area measurement systems for smart grid monitoring, protection, and control. However, they do generate much data and create a heavy burden on the communication network. One of the most practical ways of alleviating this problem is to install phasor data compression units (PDCUs) across the power system to concentrate PMU data and reduce total data traffic. These PDCUs implement hardware-based compression algorithms and, therefore, will incur minimum communication delays while significantly reducing the overall traffic generated by PMU. Since these PDCUs are pieces of hardware to be installed, given a target traffic reduction rate, it is economical to decide the optimal deployment of PDCUs. We will call this the optimal PDCU installation (OPI) problem. In this paper, we first introduce the functionality of PDCU and then give a generalized OPI formulation. We also provide an extra OPI formulation that fits under the integer linear programming framework and introduce a binary search algorithm to efficiently solve it. The OPI solutions for the IEEE 30-bus, 57-bus, 118-bus, and 300-bus systems are provided in this paper.
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2015.2503425