Spatial Multi-Criteria Land Suitability Analysis for Community-Scale Biomass Power Plant Site Selection

บทความในวารสาร

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Boonman, A.; Fukuda, S.; Junpen, A.

ผู้เผยแพร่: MDPI

ปีที่เผยแพร่ (ค.ศ.): 2025

วารสาร: Energies (1996-1073)

Volume number: 18

Issue number: 17

หน้าแรก: 4469

นอก: 1996-1073

eISSN: 1996-1073

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015969912&doi=10.3390%2Fen18174469&partnerID=40&md5=b18bb0700b7042905fd86b16ce3c3f97

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

Community-scale biomass power plants (CSBPPs) offer a decentralized approach for electricity generation by utilizing locally available biomass while delivering socioeconomic benefits. Site selection plays a critical role in the success of CSBPPs and requires the consideration of diverse spatial and non-spatial factors. This study presents a spatial decision-support tool for identifying suitable CSBPP sites in Thailand’s Eastern Economic Corridor (EEC), which comprises the Chachoengsao, Chonburi, and Rayong provinces. A geoprocessing workflow integrating Geographic Information Systems (GISs), Multi-Criteria Decision-Making (MCDM), and the Analytic Hierarchy Process (AHP) was developed using ModelBuilder tools in ArcGIS Pro (version 3.0.2). Thirteen sub-criteria related to geographical, infrastructural, and socioeconomic–cultural dimensions, along with exclusion zones, were evaluated by 15 experts from diverse stakeholder groups. Biomass availability from five major economic crops was combined with other spatial data layers, incorporating expert-assigned weights and suitability scores. The findings indicated a remaining biomass energy potential was 34,156 TJ, with sugarcane residues contributing over 80%. Approximately 20% of the EEC area (about 0.262 million hectares) was classified as highly suitable for CSBPP development, revealing several viable site options. The proposed model offers a flexible and replicable framework for regional biomass planning and can be adapted to other locations by adjusting the criteria and integrating optimization techniques. © 2025 by the authors.

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