Siting Renewable Energy Facilities Using a Matching Algorithm: A Case Study in Japan

Noriko Irie (), Ryusei Iwamura, Kaho Sugiura and Naoko Kawahara
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Noriko Irie: Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama 790-8577, Japan
Ryusei Iwamura: Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama 790-8577, Japan
Kaho Sugiura: Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama 790-8577, Japan
Naoko Kawahara: Faculty of Business Administration, Kindai University, Higashiosaka 577-8502, Japan

Land, 2022, vol. 12, issue 1, 1-15

Abstract: Finding an optimal match between installation sites and renewable energy (RE) facilities while ensuring that private initiatives meet local socio-environmental needs is a significant albeit complicated task. Different sites may need diverse considerations, such as landscape conservation, while information on the true local preferences and costs of RE facilities is unknown to the planner, causing information asymmetry and inefficiency. This study explores how a matching model can be utilised for empirically planning RE siting using an illustrative case study. It employs the so-called ‘college admission problem’ of the matching model. The matching algorithm enables the matching of sites and RE specifications, reflecting the true preferences of local people regarding facility siting. The matching result would ensure the most desirable choice for local people, as adopting the ‘student-optimal matching’ algorithm generates desirable matching patterns for the locals among the stable matching patterns.

Keywords: matching algorithm; facility siting; land; renewable energy (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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