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Geospatial Optimization of Location-Dependent Costs for Gravity Energy Storage Plants in a Mountainous Suburban Area: The Case of Fukuoka City, Japan

Author

Listed:
  • Tetsuhito Hoshino

    (Graduate School of Energy Science, Kyoto University, Japan)

  • Soumya Basu

    (Graduate School of Energy Science, Kyoto University, Japan)

  • Takaya Ogawa

    (Graduate School of Energy Science, Kyoto University, Japan)

  • Keiichi N. Ishihara

    (Graduate School of Energy Science, Kyoto University, Japan)

  • Kiyoshi Hoshino

    (School of Science and Technology, Meiji University, University of Tsukuba, Japan)

  • Hideyuki Okumura

    (Graduate School of Energy Science, Kyoto University, Japan)

Abstract

Gravity Energy Storage (GES) systems are recently being considered as a viable solution for storing intermittent renewable energy power, specifically in high curtailment zones. While a few studies have analyzed the material costs of GES systems, there is a paucity of literature on analyzing the socioeconomic costs of GES systems. This study analyzes the location-dependent costs of GES plants using a multi-factor spatial parameterization model for evaluating the existence of a point of minimum cost in a suburban mountainous geography. A case study of 500x500 points in a 50x50km2 area in the suburban area of Fukuoka city in Japan is performed. It is found that the cost of material transportation and transmission is more dominant in determining the position of an optimal cost location than factors of excavation and land costs. The position of the minima is also related to the principal urban area in that the line connecting the Center Business District (CBD) and suburban flat areas (line 1) is where the potential minima lie. The intersection point of an orthogonal to the line connecting the CBD with a substation nearest to the flat area with line 1, is the potential zone of minima location. The findings of this study are critical for urban energy planners and reveals how socioeconomic cost factors can aid in geolocation a suitable GES installation site.

Suggested Citation

  • Tetsuhito Hoshino & Soumya Basu & Takaya Ogawa & Keiichi N. Ishihara & Kiyoshi Hoshino & Hideyuki Okumura, 2024. "Geospatial Optimization of Location-Dependent Costs for Gravity Energy Storage Plants in a Mountainous Suburban Area: The Case of Fukuoka City, Japan," Energy Technologies and Environment, Anser Press, vol. 2(1), pages 50-63, March.
    • Handle: RePEc:bba:j00006:v:2:y:2024:i:1:p:50-63:d:331
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    References listed on IDEAS

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    1. Amjad, Fahd & Shah, Liaqat Ali, 2020. "Identification and assessment of sites for solar farms development using GIS and density based clustering technique- A case of Pakistan," Renewable Energy, Elsevier, vol. 155(C), pages 761-769.
    2. Asim, Nilofar & Sopian, Kamaruzzaman & Ahmadi, Shideh & Saeedfar, Kasra & Alghoul, M.A. & Saadatian, Omidreza & Zaidi, Saleem H., 2012. "A review on the role of materials science in solar cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5834-5847.
    3. Ottensmann, John R. & Payton, Seth & Man, Joyce, 2008. "Urban Location and Housing Prices within a Hedonic Model," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 38(01), pages 1-17.
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