Thermo-economic modeling and GIS-based spatial data analysis of ground source heat pump systems for regional shallow geothermal mapping

Younes Noorollahi, Hamidreza Gholami Arjenaki and Roghayeh Ghasempour

Renewable and Sustainable Energy Reviews, 2017, vol. 72, issue C, 648-660

Abstract: The increasing interest in ground source heat pump system (GSHP) as well as its high initial investment cost accentuate the necessity for an assessment tool which supports policy makers with decisions regarding technology development and subsidization. Since the performance of a geothermal heat pump system depends strongly on parameters such as geological and climate conditions, a regional-scale energy-economic mapping by spatial analysis was accomplished for priority assessment of each region which is to be subsidized. The procedure includes numerical modeling and optimization of GSHP systems by Genetic Algorithm (GA), regional heating/cooling design load estimation and spatial data analysis to achieve an economic-based map for 234 cities in Iran. Moreover, spatial interpolation was carried out in order to achieve a statistical surface map for the entire country. For the first time, Iran's regional shallow geothermal map was accurately presented along with other geographical maps including air and earth surface’s mean temperature, heating/cooling loads, GSHP required operating hours and Iran's climatology. Total Annual Cost (TAC) values were categorized into five equal ranges from CA (the highest priority class) to CE (the lowest priority class) which highlight the convenient regions for shallow geothermal energy use. Finally, Iran’s provinces were sorted according to TAC weighted average values.

Keywords: Ground source heat pump; Shallow geothermal energy; Spatial data analysis; Potential mapping; Thermo-economic modeling; Optimization (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:72:y:2017:i:c:p:648-660

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DOI: 10.1016/j.rser.2017.01.099

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