A comparison of novel optimization model and algorithm for solving PMU deployment issues in the grid
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Sådhanå (2020)45:284 https://doi.org/10.1007/s12046-020-01522-y
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A comparison of novel optimization model and algorithm for solving PMU deployment issues in the grid ANSHUL AGARWAL1,*
and KRITHI RAMAMRITHAM2
1
Department of Computer Science and Engineering, VNIT, Nagpur, India Department of Computer Science and Engineering, IIT, Bombay, India e-mail: [email protected]
2
MS received 22 August 2020; revised 2 October 2020; accepted 9 October 2020 Abstract. Phasor Measurement Unit (PMU) sensors are commonly used nowadays for sensing different line parameters of the grid for making it more efficient and reliable. However, they are costly to procure and maintain. Also, they may fail and produce measurements with errors. Towards these issues, a novel optimization model and a polynomial time algorithm are developed that solve these issues with respect to minimal PMU deployment in the grid. These techniques are compared and tested on the standard IEEE 5, 14, 30, 57 and 118 bus systems. For achieving cross-validation and robustness ability in the grid, the developed optimization model and algorithm deploy about 70% and 141% less number of additional PMUs, respectively, as compared with the baseline approach. The results indicate that the developed techniques are very pragmatic and holistic since they take minimal time for allocating minimum PMU sensors while solving problems of cross-validation of PMU measurements and robustness against PMU outages. Keywords.
Algorithm; minimum PMU allocation; optimization model; PMU deployment issues.
1. Introduction In a smart grid, line parameters like voltage and current phasors are sensed to estimate the status of the grid for avoiding its breakdown and failure. Phasor Measurement Unit (PMU) sensors [1] are most commonly used for this purpose [2]. However, they require communication facilities, are very expensive and their maintenance is costly [3, 4]. Therefore, it is required that minimum PMUs should be installed in the grid. While installing PMU sensors in the grid, additional problems related to their deployment may arise like the presence of errors in the measurement [5] and failure of PMU sensors. Thus this work aims to install the minimum number of PMU sensors in the grid while ensuring that the line parameters of all the buses in the grid are sensed (called as full observability of the grid), and issues related to PMU deployment (like errors and failure) in the grid are tackled. Following are the main contributions of this paper: • A novel optimization model that deploys the minimum number of PMUs for achieving full observability of the grid while satisfying various issues related to PMU deployment. • A novel (polynomial running time) algorithm to allocate minimal PMU sensors for tackling different *For correspondence
PMU deployment problems since minimum PMU allocation is NP-Complete. • To demonstrate the effectiveness of the newly developed optimization model and algorithm, they are applied on the standard IE
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