Two-step procedure for multi-criteria choice of generating-capacity structure in remote areas

The paper dwells upon the problem of multi-criteria choice of ways to develop generating capacities to supply power to remote consumers. We herein propose a two-step multi-criteria analysis method: choosing promising power-generation technology first, and then specifying the generating-capacity stru...

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Bibliographic Details
Main Authors: Nefedov Aleksandr, Shakirov Vladislav
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20197702009
Description
Summary:The paper dwells upon the problem of multi-criteria choice of ways to develop generating capacities to supply power to remote consumers. We herein propose a two-step multi-criteria analysis method: choosing promising power-generation technology first, and then specifying the generating-capacity structure. The paper describes the structure of the proposed multi-criteria methods: the interval TOPSIS method for Step 1; for Step 2, an upgraded analytic hierarchy process based on identifying the structure of the decision maker’s preferences. We demonstrate the use of this method with evidence from the Penzhinsky District, Kamchatka Krai. Thermal power plants, hydroelectric power plants, diesel power plants, as well as solar and wind power are analyzed as power sources. Step 1 includes: analyzing the potential power-supply loads in a specific area; formulating alternative power-generation technology; formulating goals and criteria; criterion-based evaluation of alternative options using objective and subjective models; multi-criteria evaluation of alternatives; analyzing the sensitivity of results and the selection of promising technology. Step 2 includes: formulating goals and criteria on the basis of the selected power-generation technologies; formulating the available alternatives; criterion-based evaluation of alternatives; multi-criteria evaluation and final decision-making.
ISSN:2267-1242