A New Technique for Unbalance Current and Voltage Estimation With Neural Networks

Alcántara, F. Javier; Salmerón, P.

doi:10.1109/tpwrs.2005.846051

Cited by 48 publications

(15 citation statements)

References 7 publications

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“…In this way, the IEEE Standard establishes the procedure to assess the voltage and current distortion and unbalance in the electric network PCC, [1,2]. Power monitoring equipment is frequently used to do that, [3][4][5][6][7]. However, the Standard does not regulate the procedure to assign the responsibility for the network harmonic distortion and/or unbalance to the different agents in the electric power system.…”

Section: Introductionmentioning

confidence: 99%

Unbalance and harmonic distortion assessment in an experimental distribution network

Martín

Herrera

Vázquez

et al. 2015

Electric Power Systems Research

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Section: Introductionmentioning

confidence: 99%

Unbalance and harmonic distortion assessment in an experimental distribution network

Martín

Herrera

Vázquez

et al. 2015

Electric Power Systems Research

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“…Different approaches have been presented in the technical literature for spectral analysis based of the Fourier theory including discrete Fourier transform (DFT) algorithm, fast Fourier transform (FFT) algorithm [14]- [19], Kalman filter (KF) [10], least mean square (LMS) technique [20], phaselocked-loop (PLL) [1], finite-impulse-response (FIR) filters [2], Newton-type algorithm (NTA) [21], optimization algorithms [22], least squares (LS) method [23], recursive least squares (RLS) method [24], using orthogonal vectors for three-phase power systems [25], and artificial neural networks (ANNs) [26]. The most widely utilized algorithms amongst these approaches are FFT and DFT which, however, suffer from three major pitfalls namely aliasing, picket-fence effect, and leakage [18]- [19].…”

Section: Introductionmentioning

confidence: 99%

Undersampled on-line ANN-EKF based estimation of harmonics/interharmonics in power systems

Sadinezhad

Agelidis

2010

IEEE PES General Meeting

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This paper describes a new approach to estimate harmonics/interharmonics of power system voltages and currents based on a hybrid artificial neural network (ANN) and extended Kalman filter (EKF) structure. A very low sampling rate is used to implement the proposed ANN-EKF structure with the modest hardware demands. The ANN structure is used for spectral estimation, consumes a very low processing power, and needs a few samples per cycle for real-time implementation. An EKF performs a secondary process on the ANN fundamental frequency phasor estimation to recover it from the errors due to the ANN internal setting. The presented ANN-EKF structure is a very simple and intelligent module to be used by utilities for statistical assessment of harmonics/interharmonics pollution. Besides, it can be a part of utility practices to control, compress, and process large volume of information flowing into data centers through sensors to be placed across the future intelligent power grids. The performance of the proposed method is evaluated by simulations in MATLAB-Simulink environment and confirmed by experimental results.Index Terms-Adaptive Kalman filtering, neural network applications, power system harmonics/interharmonics, signal reconstruction, signal sampling.

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“…A solution method was given to formulate a multiphase power flow model and state estimation for distribution systems [11]. A new measurement procedure based on neural networks was presented for the estimation of current/voltage symmetrical components [12]. The measurements and simulation studies of NSC before and after outage of major transmission systems were compared [13].…”

Section: Introductionmentioning

confidence: 99%

Reassessment of Permissible Negative Sequence Current for Power Plant Operation of Taipower

Ho¹,

Wu²,

Chang³

et al. 2010

EPE

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The N3 power plant of Taipower is located in the southern tip of Taiwan and connected to the power pool by four out-linking 345-kV overhead transmission circuits. There are two 951-MW generators. Each generator occupied 11% of the system peak load in 1985 when the generator was in commercial operation. Since Taipower is an isolated system, at the N-2 conditions, those generators were reduced to 75% loading to protect the power system. By the way, to avoid damage of negative sequence current (NSC), the limits of the N3 power plant are stricter than those in the IEEE Standard. However, in 2010, the capacity ratio of each generator in the plant to the system peak load has been reduced to 3% only. To increase the economic benefit of those generators, it is required to reassess the operation limits of NSC. EMTP was used to calculate the levels of NSC from the out-linking transmission circuits. From the results of this study, the effects of NSC could be ignored when the four out-linking circuits are in N-0, N-1, and N-2 conditions. The generators can be operated in full loading under these conditions. The modifications to the NSC limits of the N3 power plant are also suggested.

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A New Technique for Unbalance Current and Voltage Estimation With Neural Networks

Cited by 48 publications

References 7 publications

Unbalance and harmonic distortion assessment in an experimental distribution network

Unbalance and harmonic distortion assessment in an experimental distribution network

Undersampled on-line ANN-EKF based estimation of harmonics/interharmonics in power systems

Reassessment of Permissible Negative Sequence Current for Power Plant Operation of Taipower

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