Multi-Criteria Evaluation of Reconstruction Strategies for Distribution Power Networks Designed for Rural Power Supply

Multi-Criteria Evaluation of Reconstruction Strategies for Distribution Power Networks Designed for Rural Power Supply

Tamara Leshchinskaya (Russian State Agrarian University – Moscow Timiryazev Agricultural Academy, Russia), Pavel Podobedov (Federal State Budgetary Scientific Institution, Federal Scientific Agroengineering Center VIM, Russia), Pavel Maslennikov (Federal State Budgetary Scientific Institution, Federal Scientific Agroengineering Center VIM, Russia), Anton Nekrasov (Federal State Budgetary Scientific Institution, Federal Scientific Agroengineering Center VIM, Russia) and Alexey Nekrasov (Federal State Budgetary Scientific Institution, Federal Scientific Agroengineering Center VIM, Russia)
DOI: 10.4018/978-1-7998-1216-6.ch013

Abstract

The rural distribution network has deteriorated. This is due to the high failure rate of electrical equipment, high maintenance costs, reduced power quality, and the increased duration of power outages in agricultural production. This leads to a short supply of electricity, downtime of processing equipment, loss of production or production of low-grade products, as well as excessive energy losses during transmission. The important issue is the development of advanced methods for assessing the feasibility and effectiveness for component replacement of power transmission equipment with newer and more modern, reducing electrical energy loss in the distribution network. To solve these problems, various strategies have been developed and studied to improve the reliability of 10 kV overhead power lines by using modern insulators, wires, and supports.
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Data And Methods

Based on results of expert surveys followed by their analysis and on those of sampling statistical data related to 10 kV power distribution networks, reliability levels of currently operated lines have been studied. These studies made it possible to define the most perspective equipment for 10 kV OHL renovation. Multi-criteria evaluation was made for two options of partial criteria combinations followed by their convolution into an entire composed evaluation function. These results were obtained based on Bayes’s criterion with the use of fuzzy-set theory. In the frames of multi-criteria model, parameters optimization was performed in accordance with the following algorithm:

  • Development of strategies for operation performance improvement of 10 kV power distribution lines with the purpose of power supply reliability enhancement and electric energy quality perfection

  • Selection and scientific description of partial criteria for practicability evaluation of electric equipment application designed to enhance power supply reliability and to reduce energy loss, in 10 kV power distribution networks

  • Development of mathematical models for partial-criteria-based evaluation including analytical equations for partial criteria

  • Selection of uncertainty factor for environment expressed in form of growth factor for perspective load extension (Leshchinskaya & Knyazev 2006)

  • Partial criteria calculating for strategies under consideration, for various values of load growth factor

  • Selecting a method for partial criteria convolution into an entire combined function

  • Calculating values of matrix for evaluation functional

  • Selecting optimal options in accordance with Bayes’s criterion with the use of fuzzy-set theory

Key Terms in this Chapter

Reliability of Power Supply: Is the ability of the electrical system to provide connected consumers with electrical energy of a given quality at any time interval.

Fuzzy Set Theory: Is a branch of applied mathematics devoted to methods of analysis of uncertain data, in which the description of uncertainties of real phenomena and processes is carried out using the concept of sets that do not have clear boundaries.

Multi-Criteria Evaluation: Evaluation using several specific criteria.

Power Quality: The extent to which the parameters of electrical energy their established values.

Criterion Bayesian: Criterion of maximum average win.

The Fuzzy Set Membership Function: Is a generalization of the indicator (or characteristic) function of the classical set.

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