Quantifying electric power quality via fuzzy modelling and analytic hierarchy processing

Farghal, S.A.; Kandil, M.S.; Elmitwally, A.

doi:10.1049/ip-gtd:20020006

Cited by 67 publications

(30 citation statements)

References 8 publications

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“…(2)The results from CVM1~CVM4 and [5] are almost consistent while those of [3], [8] and [17] are basically similar. Actually, the key discrepancy concentrates on the priority of s 1 and s 2 .…”

mentioning

confidence: 57%

“…For the further demonstration of the validity of modified CVM and the impacts of different empowerment approaches on the evaluation, another eight random samples of PQ from [3] With the application of CVM with equitable weight (CVM1), CVM with AHP (CVM2), CVM with VCM (CVM3), and CVM with SE (CVM4), the corresponding close value set can be separately represented as E , E 1 Therefore, the final assessment results derive from CVM1 to CVM4 and [3,5,8,17] can be compared in the Table 3. Table 3 ranking results of PQ by various methods Sampleto be inferior to those of s 2 , though s 1 holds a higher PSR.…”

Section: Assessment Of Eight Random Samples Of Pqmentioning

confidence: 99%

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Application of Modified Close Value Method in Power Quality Evaluation

Hu¹,

Jing²,

Yan³

et al. 2017

Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

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Abstract:For enhancing the accuracy and rationality of power quality (PQ) evaluation, close value method (CVM) based on the target optimization principle is introduced to symbolize the performance of PQ samples. To tackle with the defect, in calculating close value of PQ samples, that the calculation formula of close value is divided by zero, a modified CVM is correspondingly developed to adapt to the randomness of PQ samples. Meanwhile, for analyzing the impacts of weighting approaches on the evaluation outcome, different weighting approaches are orderly utilized to improve CVM. Case analysis shows that the new calculating method of close value is proved to be more simplified and applicable; the impacts different weighting approaches have on the evaluation outcome differ to some extent.

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mentioning

confidence: 57%

Section: Assessment Of Eight Random Samples Of Pqmentioning

confidence: 99%

Application of Modified Close Value Method in Power Quality Evaluation

Hu¹,

Jing²,

Yan³

et al. 2017

Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)

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“…The impacts of such disturbing effects can be directly related to power losses, insulation stress, over voltages, power oscillations or even malfunction and damage on sensitive loads (Bollen, 2000). Among a number of different areas related to this question, during the last decades intensive research has been directed to the definition of power quality indices and revenue metering techniques, suitable for monitoring nonlinear and unbalanced systems (Ferrero et al, 1998;Marafão et al, 2002;Farghal et al, 2002). Considering the power quality monitoring, important indices have been defined to estimate the amount of harmonic distortion or unbalances on the measured voltage (v) and currents (i) or also how these distortions affect other indicators, such as, e.g., the power factor (PF).…”

Section: Revenue Metering and Power Quality Monitoringmentioning

confidence: 99%

Kalman Filter on Power Electronics and Power Systems Applications

Marafão¹,

Colón²,

Padua³

et al. 2009

Kalman Filter Recent Advances and Applications

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The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields. The book is divided into 24 chapters and organized in five blocks corresponding to recent advances in Kalman filtering theory, applications in medical and biological sciences, tracking and positioning systems, electrical engineering and, finally, industrial processes and communication networks.

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“…One of the most important indices of energy quality is voltage deviation. For the investigation of electric energy quality indices in 2000 IEEE formed a team of specialists, the results of the work of this team are available in [2,3]. Analysis of consumers sensitiving to voltage quality is shown in [4].…”

Section: Introductionmentioning

confidence: 99%

Integral Index of Operation Quality for Evaluation of Impact of Distributive Generation Sources on Electric Network Modes

Лежнюк

Komar

Sobchuk

et al. 2017

Adv. Sci. Technol. Res. J.

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Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE) is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

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Quantifying electric power quality via fuzzy modelling and analytic hierarchy processing

Cited by 67 publications

References 8 publications

Application of Modified Close Value Method in Power Quality Evaluation

Application of Modified Close Value Method in Power Quality Evaluation

Kalman Filter on Power Electronics and Power Systems Applications

Integral Index of Operation Quality for Evaluation of Impact of Distributive Generation Sources on Electric Network Modes

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