A New Approach to Optimal Placement of Power Quality Monitors for Voltage Sag Detection

Alicic, Raif; Smaka, Senad

doi:10.1109/isgteurope.2019.8905585

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…where i represents an arbitrary meter position; j represents an arbitrary fault position; t represents a given fault type. V t,ij is the lowest residual voltage magnitude of the phase voltages at bus i when a fault of type t takes place at the fault position, which can be obtained according to (4)- (7). The decision vector X of length N is defined to exhibit the need for a meter at bus i.…”

Section: Traditional Optimal Monitoring Methods a Optimal Monitomentioning

confidence: 99%

“…Evaluating the voltage sag observability of monitoring system reasonably is the key to the establishment of optimal placement model [7]- [10]. The MRA-based method achieves full observability of voltage sags by ensuring that every fault event is recorded by at least one monitor.…”

Section: B Voltage Sag Observability Random Vector Modelmentioning

confidence: 99%

“…As a means of obtaining voltage sag data and assessing voltage sag performance, power quality monitoring is a stated consensus that it will play a key role in the advancement of power systems infrastructure [6]. The ideal voltage sag monitoring system consists of PQMs installed at all buses in the considered network [7], [8]. However, it is unrealistic for economic reasons.…”

mentioning

confidence: 99%

“…Moreover, a variety of optimization methods, including Genetic Algorithm, Binary Particle Swarm Optimization (BPSO) and etc. are presented to find the minimum number of PQMs and their best arrangement [7], [9], [13]- [15].…”

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confidence: 99%

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A BPSO-Based Method for Optimal Voltage Sag Monitor Placement Considering Uncertainties of Transition Resistance

Jiang

Liu

et al. 2020

IEEE Access

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This study presents a new approach to the optimal placement of voltage sag monitors considering the uncertainties associated with transition resistance. The influence of transition resistance on the magnitude of voltage sags triggered by symmetrical and unsymmetrical faults is analyzed. Then the transition resistance interval set array for voltage sags is established, on the basis of which, a random vector model on voltage sag observability is proposed and related observability indices are defined in the form of conditional probability. The optimal placement model is established by taking the available number of monitors as the constraint condition and the maximum sag global observability index as the objective function. Binary particle swarm optimization (BPSO) is implemented to obtain the optimal placement results. Finally, simulation is carried out on IEEE 30-bus system, and it is shown that the proposed optimal monitor placement method is more applicable compared with the traditional MRA method. INDEX TERMS Binary particle swarm optimization, conditional probability, observability indices, optimal monitor placement, random vector model, transition resistance, uncertainties, voltage sags. I. INTRODUCTION Voltage sags are the most frequently occurring power quality disturbances, mainly caused by faults in a power system. Voltage sag is typically defined as the reduction of RMS voltage from 0.1 to 0.9 p.u. with a typical duration of 0.5 cycle to 1 min, which is usually characterized by its magnitude (the magnitude of during-fault voltages) and duration (the time during which the RMS voltage stays below a given threshold, usually 0.9 p.u.) [1]-[4]. Many studies conducted around the world have shown that voltage sags cause customers of various sectors significant financial losses, for instance, in a semiconductor manufacturing industry, economic losses per voltage sag have been estimated 3.8 million e[5], [6]. But it is unrealistic to expect that the grid will provide a completely financialloss-free power quality environment for all customers [6]. Before implementing adequate countermeasures, it is necessary to establish a monitoring system by using appropriate power quality monitors (PQMs) and this system should The associate editor coordinating the review of this manuscript and approving it for publication was Hui Ma .

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Section: Traditional Optimal Monitoring Methods a Optimal Monitomentioning

confidence: 99%

Section: B Voltage Sag Observability Random Vector Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A BPSO-Based Method for Optimal Voltage Sag Monitor Placement Considering Uncertainties of Transition Resistance

Jiang

Liu

et al. 2020

IEEE Access

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Data-driven prediction method for characteristics of voltage sag based on fuzzy time series

Wang

Yang

Zhang

et al. 2022

International Journal of Electrical Power & Energy Systems

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A multistage optimal placement approach of monitors considering voltage sag and fault position observability

Liu

Dai

Zhu

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Reasonable placement of limited monitors is beneficial to reduce the cost of monitoring for voltage sags assessment. However, existing methods only consider the observability of voltage sags, leading to information loss. To capture all the voltage sags and the corresponding fault positions in distribution network, a multistage optimal placement approach of power quality monitors considering voltage sag and fault position observability is proposed. The initial requirement of voltage sag monitoring, that is, voltage sag observability is ensured by monitoring reach area method. Then, based on a simple fault location method, the fault location observability index is proposed for describing monitoring effects for fault position observability. A series of placement schemes with different costs and monitoring effects are given, which is convenient for engineers to choose the proper placement scheme according to the budget and demand. The simulation results carried on the IEEE 69-bus system show that the proposed approach can is correct and available.

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A New Approach to Optimal Placement of Power Quality Monitors for Voltage Sag Detection

Cited by 5 publications

References 10 publications

A BPSO-Based Method for Optimal Voltage Sag Monitor Placement Considering Uncertainties of Transition Resistance

A BPSO-Based Method for Optimal Voltage Sag Monitor Placement Considering Uncertainties of Transition Resistance

Data-driven prediction method for characteristics of voltage sag based on fuzzy time series

A multistage optimal placement approach of monitors considering voltage sag and fault position observability

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