In the quest for sustainable and decentralized energy solutions, a groundbreaking study led by Athipthep Boonman from the Joint Graduate School of Energy and Environment at King Mongkut’s University of Technology Thonburi in Bangkok, Thailand, has developed a spatial decision-support tool that could revolutionize the site selection process for community-scale biomass power plants (CSBPPs). Published in the journal Energies, the research offers a flexible and replicable framework for regional biomass planning, with significant implications for the energy sector.
The study focuses on Thailand’s Eastern Economic Corridor (EEC), a region comprising Chachoengsao, Chonburi, and Rayong provinces. The EEC is a hub of economic activity, and the integration of CSBPPs could provide a decentralized approach to electricity generation, utilizing locally available biomass while delivering socioeconomic benefits. “Site selection is a critical factor in the success of CSBPPs,” Boonman explains. “Our study aims to streamline this process by considering diverse spatial and non-spatial factors.”
The research employs a geoprocessing workflow that integrates Geographic Information Systems (GISs), Multi-Criteria Decision-Making (MCDM), and the Analytic Hierarchy Process (AHP). Using ModelBuilder tools in ArcGIS Pro, the team developed a model that evaluates thirteen sub-criteria related to geographical, infrastructural, and socioeconomic–cultural dimensions. These criteria were assessed by 15 experts from diverse stakeholder groups, ensuring a comprehensive and balanced approach.
One of the key findings of the study is the identification of a remaining biomass energy potential of 34,156 TJ in the EEC, with sugarcane residues contributing over 80% of this potential. Approximately 20% of the EEC area, about 0.262 million hectares, was classified as highly suitable for CSBPP development. This revelation opens up several viable site options for developers, potentially accelerating the deployment of community-scale biomass power plants in the region.
The proposed model offers a flexible and replicable framework for regional biomass planning. “Our model can be adapted to other locations by adjusting the criteria and integrating optimization techniques,” Boonman notes. This adaptability is crucial for the energy sector, as it allows for the customization of the model to fit the unique needs and characteristics of different regions.
The commercial impacts of this research are significant. By providing a robust and data-driven approach to site selection, the model can help reduce the risks and uncertainties associated with CSBPP development. This, in turn, can attract more investment and accelerate the transition to decentralized energy systems. The model’s ability to integrate diverse criteria and stakeholder inputs ensures that the selected sites are not only technically feasible but also socially and environmentally sustainable.
As the energy sector continues to evolve, the need for decentralized and sustainable energy solutions becomes increasingly apparent. The research led by Athipthep Boonman offers a promising path forward, providing a tool that can shape the future of biomass power plant development. By harnessing the power of geospatial modeling and expert input, this study paves the way for a more sustainable and resilient energy landscape.