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Evaluating the capability of distribution networks to maintain power quality and voltage level, case study: alborz electric power distribution company

Jamshidieini, B ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1049/iet-gtd.2018.5532
  3. Abstract:
  4. Distribution system operators that seek operational excellence are supposed to design and implement capable processes throughout their value stream and assess how well their real services match the design specifications. Process capability analysis is a critical stage in systematic and sophisticated quality engineering approaches such as six sigma, which are based on quantitative studies. The capability of a distribution network to maintain the power quality and voltage level within an acceptable range is one of the most important aspects of design and utilisation of electricity distribution network. Capability analysis has been successfully used in the previous studies to assess the quality of conformance in the power distribution network. However, these studies were limited to a voltage level and other aspects of quality such as total harmonic distortion were neglected. In addition, parametric methods were not available to overcome the problem of multimodality in voltage distribution, especially in the presence of distributed generation. In the current study, for the first time, a parametric approach based on decomposing complex distributions to a few Gaussian distributions by artificial bee colony optimisation were used for evaluating the capability of the distribution network to maintain voltage level and power quality indices in predefined ranges. © The Institution of Engineering and Technology 2018
  5. Keywords:
  6. Electric utilities ; Optimization ; Process engineering ; Quality control ; Artificial bee colonies ; Design and implements ; Electricity distribution networks ; Operational excellence ; Power distribution network ; Power quality indices ; Process capability analysis ; Total harmonic distortion (THD) ; Power quality
  7. Source: IET Generation, Transmission and Distribution ; Volume 12, Issue 16 , 2018 , Pages 3883-3891 ; 17518687 (ISSN)
  8. URL: https://ieeexplore.ieee.org/document/8444490