Sensitivity analysis of method for harmonic state estimation in the power system

Becirovic, V.; Pavić, Ivica; Filipović-Grčić, Božidar

doi:10.1016/j.epsr.2017.07.029

Cited by 16 publications

(10 citation statements)

References 26 publications

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“…The actual and estimated harmonic voltages magnitude and voltage phasor at each bus are shown in columns 2 to 5. The percentage of harmonic measurement error calculated using (9) and (10) is provided in column 6. This measurement error is calculated between the actual value and estimated value at each bus for harmonic frequencies 5, 7, 11, and 13.…”

Section: Case B With ±5% Measurement Errormentioning

confidence: 99%

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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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Section: Case B With ±5% Measurement Errormentioning

confidence: 99%

“…Similarly, the authors in [9] suggested a fast and accurate HSE based on the concept of matrix algebra and using a genetic algorithm (GA) optimization technique. In [10], L1-norm minimization method is utilized to solve HSE by formulating it as a constrained Sparsity maximization method.…”

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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“…A practical approach to incorporate the FACTS controllers into a Weighted Least Squares (WLS) SE algorithm is proposed in [4]. In Reference [5], a new algorithm based on node voltage method, Kron reduction matrix, modeling of power system in frequency domain using phase values and GA optimization is proposed for the harmonic SE in power systems. A new approach for the SE of a non-linear AC power system in a non-iterative manner based on the Kipnis-Shamir relinearization technique is proposed in [6].…”

Section: Introductionmentioning

confidence: 99%

Artificial fish swarm optimization algorithm for power system state estimation

Salkuti

2020

IJEECS

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In this paper, the power system state estimation (SE) problem is formulated as a general non-linear programming problem with equality constraints and boundary limits on the state variables. The proposed SE problem is solved using an evolutionary based Artificial Fish Swarm Optimization Algorithm (AFSOA). The AFSOA is a global search algorithm based on the characteristics of fish swarm and its autonomous model. The detailed algorithm with its flow chart is presented in this paper. To show the effectiveness of the proposed SE approach, six bus test system is considered. The obtained results are compared with other algorithms reported in the literature.

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“…A operação em tempo real dos sistemas de potência depende de uma avaliação de sua segurança a qual deve ser mantida para garantir o fornecimento e a qualidade de energia entregue aos consumidores (Bečirović et al, 2018;Kamyabi et al, 2018;Albu et al, 2016).…”

Section: Introductionunclassified

Avaliação da estabilidade de tensão em sistemas de potência através de análise modal e estimação de estados

Mingorança

Melo

Antunes

et al. 2020

Anais Do Congresso Brasileiro De Automática 2020

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Este artigo apresenta uma nova abordagem para a avaliação da estabilidade de tensão em sistemas de potência utilizando análise modal aplicada aos resultados obtidos por um estimador de estados. Na abordagem proposta, medições são obtidas de uma rede elétrica monitorada por medidores de grandezas elétricas e essas são processadas através do método dos mínimos quadrados ponderados (MQP). A partir das estimativas de magnitudes e ângulos de tensões em barramentos do sistema, é possível calcular uma matriz de sensibilidade das potências reativas em relação às magnitudes de tensão através de equações algébricas. A análise modal é aplicada nesta matriz, calculando seus autovalores e autovetores os quais são utilizados para se estimar fatores de participação de cada barra do sistema indicando as mais críticas. O sistema IEEE de 30 barras será utilizado para a condução de testes e os resultados de estimação serão analisados através de métricas estatísticas.

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Sensitivity analysis of method for harmonic state estimation in the power system

Cited by 16 publications

References 26 publications

Reverse harmonic load flow analysis using an evolutionary technique

Reverse harmonic load flow analysis using an evolutionary technique

Artificial fish swarm optimization algorithm for power system state estimation

Avaliação da estabilidade de tensão em sistemas de potência através de análise modal e estimação de estados

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