Power quality state estimation

Watson, N.R.

doi:10.1002/etep.357

Cited by 26 publications

(17 citation statements)

References 23 publications

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“…Sources, harmonic levels and transients in a power system vary with time and can be followed with the EKF algorithm. The EKF is based on a Taylor series approximation; its main steps are initialization, time update or prediction and measurement update or correction; time and measurement updates are evaluated at each time step [8,[23][24][25][26]. The monitored variable waveforms defined in the measurements vector z are sampled from the power system in a discrete form.…”

Section: Ekfmentioning

confidence: 99%

Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

Cisneros-Magana

Medína

Anaya‐Lara

2016

Int. Trans. Electr. Energ. Syst.

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This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm are selected from the simulation of the propagated harmonics in the system with an under-determined condition of the measurement matrix. The state estimation results are compared against the actual time-domain system response; both results closely agree hence verifying the effectiveness of the EKF to solve the time-domain power system state estimation. Several sampling frequencies and measurement noise are applied to assess the effects on the state estimation process, the error covariance matrix, residuals and on the execution tim

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Section: Ekfmentioning

confidence: 99%

Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

Cisneros-Magana

Medína

Anaya‐Lara

2016

Int. Trans. Electr. Energ. Syst.

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“…This mathematical approach has already been used for the state estimation of other power quality disturbances [13]- [16]. In particular, the expression (1) is used for the estimation of voltage sags in [9] where the system equations are obtained by means of an analytical method.…”

Section: Formulationmentioning

confidence: 99%

“…For such problems, the SVD technique can provide a particular solution of quadratic minimum norm. This methodology has previously been proposed for the estimation of other power quality disturbances [13]- [16].…”

Section: Solution Of the System Equationsmentioning

confidence: 99%

“…In comparison to [9] and [11], in this approach the equations are straightly determined according to the number of fault positions selected. In addition, the method proposed here to find the solution is Singular Value Decomposition, a technique that has already been used for similar problems regarding other power quality disturbances [13]- [16] and that presents advantageous characteristics with respect to IPL and GA. One of these advantages is that, contrary to ILP and GA, SVD is not an iterative method and, thus, it is not exposed to convergence problems and it always provides a solution, whatever the size and type of the network. In terms of computing time consumption, the solution by means of SVD is also very beneficial with V almost negligible computation time compared to GA and, specially, to ILP.…”

Section: Introductionmentioning

confidence: 99%

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SVD Applied to Voltage Sag State Estimation

Hernàndez

Espinosa-Juárez

Castro

et al. 2013

IEEE Trans. Power Delivery

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Abstract-The method presented in this paper addresses the problem of voltage sag state estimation (VSSE). The problem consists in estimating the voltage sags frequency at non-monitored buses from the number of sags measured at monitored sites. Usually, due to limitations on the number of available voltage sag monitors, this is an underdetermined problem. In this approach, the mathematical formulation presented is based on the fault positions concept and is solved by means of the Singular Value Decomposition (SVD) technique. The proposed estimation method has been validated by using the IEEE 118 test system and the results obtained have been very satisfactory.Index Terms-voltage sags (dips), power quality monitoring, power system, Power Quality. I. INTRODUCTIONOLTAGE sags (also known as voltage dips) are a frequent power quality disturbance that can cause failure or malfunctioning to very common devices used in industrial and tertiary sectors. This disturbance, as with other power quality problems, must be approached from a compatibility point of view that requires characterizing the equipment sensitivity as well as the power system behavior. This paper relies on this second aspect.In order to describe the voltage sags performance in the power system, a method must be established that can provide representative values of the expected number and characteristics of voltage sags at system buses. To quantify the system behavior, a great emphasis has been placed recently on the use of different quality indices. Some of these indices are defined at a site level (for a specific point of the supply system), but there are others defined at a system level (for the whole system) [1]- [4]. For assessing site indices, monitoring the power supply at the site of interest can directly provide the information to evaluate the index. However, in order to calculate voltage sag indices of the whole system, ideally the monitoring of all sites should be required. Clearly, such a monitoring program is not economically justifiable.This work has been financed by the Ministerio de Ciencia e Innovación (MICINN), Spain, under project ENE2010-17459 (CON) A. Hernández, R. M. de Castro and M. Izzeddine are with the

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“…This approach, however, does not always yield satisfying results because some power networks are lightly damped and because of difficulties in establishing suitable steady-state initial conditions [10]. This solution approach is also time-consuming and sometimes inconclusive [11].…”

Section: State Of Artmentioning

confidence: 99%

A Brief Review on Advances of Harmonic State Estimation Techniques in Power Systems

Arumugam¹

2011

IJIEE

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Abstract-As the demand for power increases, the need for harmonic state estimation (HSE) has been increasing as well. Harmonics, injected by the non-linear equipments along the distribution networks, causes several power quality issues. Therefore, HSE plays an important role in harmonics monitoring and control. Various HSE techniques and algorithms have been developed since 1989, which would be reviewed and discussed in this paper. The author outlines the role of artificial intelligence (AI) in the field and the process overview of neural network and also a hybrid algorithm which combines particle swarm optimization (PSO) and gradient descent (GD) to train the weights of neural network (NN).

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Power quality state estimation

Cited by 26 publications

References 23 publications

Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter

SVD Applied to Voltage Sag State Estimation

A Brief Review on Advances of Harmonic State Estimation Techniques in Power Systems

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