A multi-criteria decision analysis to rank energy alternative options using analytic hierarchy process with a sustainable criteria: A case study of Mae Sariang, Mae Hon Song Province, Thailand

Providing and using energy efficiently is hampered by concerns about the environment and the unpredictability of fossil fuel prices and quantities. To address these issues, energy planning is a crucial tool. The aim of the study was to prioritize renewable energy options for use in Mae Sariang’s microgrid using an analytical hierarchy process (AHP) to produce electricity. A prioritization exercise involved the use of questionnaire surveys to involve five expert groups with varying backgrounds in Thailand’s renewable energy sector. We looked at five primary criteria. The following four combinations were suggested: (1) Grid + Battery Energy Storage System (BESS); (2) Grid + BESS + Solar Photovoltaic (PV); (3) Grid + Diesel Generator (DG) + PV; and (4) Grid + DG + Hydro + PV. To meet demand for electricity, each option has the capacity to produce at least 6 MW of power. The findings indicated that production (24.7%) is the most significant criterion, closely followed by economics (24.2%), technology (18.5%), social and environmental (18.1%), and structure (14.5%). Option II is strongly advised in terms of economic and structural criteria, while option I has a considerable advantage in terms of production criteria and the impact on society and the environment. The preferences of options I, IV, and III were ranked, with option II being the most preferred choice out of the four.

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Publication Details

Journal
Journal of Infrastructure Policy and Development
Published
2024-09-20
DOI
https://doi.org/10.24294/jipd.v8i10.5565
Citations
1
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
0.49
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article

A multi-criteria decision analysis to rank energy alternative options using analytic hierarchy process with a sustainable criteria: A case study of Mae Sariang, Mae Hon Song Province, Thailand

Parnuwat Usapein, Bancha Yathip, Sirichai Jirawongnusorn, Chakphed Madtharad
1 citations
Journal of Infrastructure Policy and Development
Multi-Criteria Decision Making
0.49
article

A multi-criteria decision analysis to rank energy alternative options using analytic hierarchy process with a sustainable criteria: A case study of Mae Sariang, Mae Hon Song Province, Thailand

Parnuwat Usapein, Bancha Yathip, Sirichai Jirawongnusorn, Chakphed Madtharad
article en
1 citations

Abstract

Providing and using energy efficiently is hampered by concerns about the environment and the unpredictability of fossil fuel prices and quantities. To address these issues, energy planning is a crucial tool. The aim of the study was to prioritize renewable energy options for use in Mae Sariang’s microgrid using an analytical hierarchy process (AHP) to produce electricity. A prioritization exercise involved the use of questionnaire surveys to involve five expert groups with varying backgrounds in Thailand’s renewable energy sector. We looked at five primary criteria. The following four combinations were suggested: (1) Grid + Battery Energy Storage System (BESS); (2) Grid + BESS + Solar Photovoltaic (PV); (3) Grid + Diesel Generator (DG) + PV; and (4) Grid + DG + Hydro + PV. To meet demand for electricity, each option has the capacity to produce at least 6 MW of power. The findings indicated that production (24.7%) is the most significant criterion, closely followed by economics (24.2%), technology (18.5%), social and environmental (18.1%), and structure (14.5%). Option II is strongly advised in terms of economic and structural criteria, while option I has a considerable advantage in terms of production criteria and the impact on society and the environment. The preferences of options I, IV, and III were ranked, with option II being the most preferred choice out of the four.

Journal of Infrastructure Policy and DevelopmentVol. 8(10)
Electricity Generating Authority of Thailand (TH), Rajamangala University of Technology Rattanakosin (TH)
Openalex Percentile: Top 31%
Multi-Criteria Decision Making
0.49
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