Harmonic state estimation for distribution networks using phasor measurement units

Neste trabalho, um modelo de otimização é formulado para se estimar estados harmônicos a partir de um algoritmo robusto à introdução de erros grosseiros. Na abordagem proposta, magnitudes e ângulos de tensões harmônicas são as variáveis de estados a serem determinadas pela solução do problema de otimização proposto. Medições fasoriais sincronizadas são consideradas para a abordagem sendo o sistema IEEE de 14 barras utilizado para validar o método proposto e atestar a eficiência do mesmo considerando cargas não lineares conectadas ao sistema. Comparações são realizadas com um fluxo de potência e o método tradicional dos Mínimos Quadrados Ponderados (MQP). A fim de se melhorar o desempenho computacional do processo da estimativa de estados para cada ordem harmônica, o uso de processamento paralelo é adotado. Palavras-chave: estimação de estados; qualidade de energia; distorção harmônica; fluxo de potência.

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“…O uso de PMUs no contexto da estimação de estados é amplamente citado na literatura como em [18][19][20][21].…”

Section: Introductionunclassified

“…Em [19], um problema de otimização com restrições não lineares é formulado para cada ordem harmônica a partir de um número reduzido de PMUs alocadas no sistema de distribuição. A resolução se dá via método de pontos interiores com barreira de segurança.…”

Section: Introductionunclassified

Estimação Robusta De Estados Harmônicos Considerando Supressão De Erros Grosseiros: Uma Abordagem Usando Um Modelo De Otimização / a Robust Harmonic State Estimation Considering Bad Data Suppression: An Approach Using an Optimization Model

Melo

Almeida

2021

BJD

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“…In this sense, several methodologies have been reported for the proper measurement and identification of harmonics. These methodologies use signal processing techniques like discrete Fourier transform (DFT) [8], chirp-z transform [9], phasor measurement units [10], Kalman filter based techniques [11], and discrete wavelet transform [12]. Although these methodologies offer a solution, they do not provide information regarding the source of the harmonic currents.…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Methodology for the Estimation of Generated Power and Harmonic Content in Photovoltaic Generation

et al. 2020

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Renewable generation sources like photovoltaic plants are weather dependent and it is hard to predict their behavior. This work proposes a methodology for obtaining a parameterized model that estimates the generated power in a photovoltaic generation system. The proposed methodology uses a genetic algorithm to obtain the mathematical model that best fits the behavior of the generated power through the day. Additionally, using the same methodology, a mathematical model is developed for harmonic distortion estimation that allows one to predict the produced power and its quality. Experimentation is performed using real signals from a photovoltaic system. Eight days from different seasons of the year are selected considering different irradiance conditions to assess the performance of the methodology under different environmental and electrical conditions. The proposed methodology is compared with an artificial neural network, with the results showing an improved performance when using the genetic algorithm methodology.

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“…In [10], L1-norm minimization method is utilized to solve HSE by formulating it as a constrained Sparsity maximization method. The concept of safety barrier interior point technique based on weighted least square (WLS) methodology is suggested in [11] by considering harmonic branch currents as state variables. However, the conventional WLS approach may not converge in the presence of uneven measurement weights.…”

Section: Introductionmentioning

confidence: 99%

Reverse harmonic load flow analysis using an evolutionary technique

Vedik

Shiva

Harish*³

2020

SN Appl. Sci.

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In the present paper, a new approach to estimate the harmonic distortions is proposed by considering the existence of harmonic sources in the power system. The algorithm employs a differential evolution technique by formulating the reverse harmonic load flow problem for each harmonic order and by considering a limited number of phasor measurement units (PMUs) deployed across the power system. The technique utilizes the measured voltage and current harmonics obtained using synchronized PMUs with known transmission network as input data. The proposed technique estimates the harmonic voltage phasors at the unmonitored buses of the power system with reasonable accuracy. The effectiveness and efficiency of the proposed method is validated by applying it to five bus and IEEE 14-bus test systems by considering uncertainty in measurement noise. It is shown that the proposed approach yields optimum solution and provides reliable and accurate harmonic state estimates.

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Harmonic state estimation for distribution networks using phasor measurement units

Cited by 53 publications

References 14 publications

Estimação Robusta De Estados Harmônicos Considerando Supressão De Erros Grosseiros: Uma Abordagem Usando Um Modelo De Otimização / a Robust Harmonic State Estimation Considering Bad Data Suppression: An Approach Using an Optimization Model

Estimação Robusta De Estados Harmônicos Considerando Supressão De Erros Grosseiros: Uma Abordagem Usando Um Modelo De Otimização / a Robust Harmonic State Estimation Considering Bad Data Suppression: An Approach Using an Optimization Model

Genetic Algorithm Methodology for the Estimation of Generated Power and Harmonic Content in Photovoltaic Generation

Reverse harmonic load flow analysis using an evolutionary technique

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