Abstract
The evaluation of solutions is an important phase in power distribution system planning (PDSP) which allows issues such as quality of supply, cost, social service and environmental implications to be considered and usually involves the judgments of a group of experts. The planning problem is thus suitable for the multi-criteria group decision-making (MCGDM) method. The evaluation process and evaluation criteria often involve uncertainties incorporated in quantitative analysis with crisp values and qualitative judgments with linguistic terms; therefore, fuzzy sets techniques are applied in this study. This paper proposes a fuzzy multi-criteria group decision-making (FMCGDM) method for PDSP evaluation and applies a fuzzy multi-criteria group decision support system (FMCGDSS) to support the evaluation task. We introduce a PDSP evaluation model, which has evaluation criteria within three levels, based on the characteristics of a power distribution system. A case-based example is performed on a test distribution network and demonstrates how all the problems in a PDSP evaluation are addressed using FMCGDSS. The results are acceptable to expert evaluators.
Highlights
The evaluation of solutions is an important phase in power distribution system planning (PDSP), 1 which consists of two stages
The comprehensive evaluation of planning solutions is an important phase in the PDSP process to ensure the development of a robust planning solution
This evaluation process is a preference based decision but involves a complex situation in which both quantitative and qualitative criteria are within a hierarchy and multiple members are involved with different opinions
Summary
The evaluation of solutions is an important phase in power distribution system planning (PDSP), 1 which consists of two stages. Evaluations of PDSP solutions are often made in groups, for example, by experts from different sections of electricity distribution companies and invited peer experts in this field, and require the gathering, processing and assessing of information from diverse functional groups within an organization. In PDSP evaluation, cost coefficients, forecasting demand, electricity price, technology development and equipment failures are fraught with uncertainty, which will affect the data of indirect criteria Even these linguistic terms reflect the uncertainty, inaccuracy and fuzziness of humans, and these uncertainties will affect the optimization process. The simple multi-attribute rating technique (SMART) and analytical hierarchy process (AHP) 12 were used to determine the weighted decision scores for each of the alternatives; a uniform possibility distribution was used to represent uncertain data entries.[7] In Ref. 13, an interval AHP-based method was proposed and applied to a practical planning case, in which the uncertain information was handled by intervals.
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