As a response to the increasing demand for renewable power, the solar photovoltaic (PV) market is growing fast. In addition to PV systems, the energy from solar radiation can be converted intoheat energy in solar thermal (ST) systems. This study uses a method that identifies solar energy systems using aerial imagery and deep machine learning to create and evaluate an inventory of solar energy systems in three Swedish municipalities together with socioeconomic and demographic data, to understand the relation between different variables and PV and ST adoption. The variables are age, sex, birth region, education, unemployment, average income and economic standard. Information about the locations also include owner, time at residence, tax value, purpose of property and purpose of building. The relation is analyzed through a correlation and regression analysis at three different granularity levels: households, demographic statistical areas and municipalities. Out of 692 inventoried PV systems and 399 ST systems, the majority was installed in rural or regional center areas. The most common buildings were residential and complementary. Most of the properties were owned by individuals, and the tax value of properties was in general lower for ST systems, indicating that it is more common for companies to install PV systems and at larger properties. The average income, age and percentage of males are higher for households that have adopted PV and/or ST systems compared to the municipalities average. However, the difference is clearer for PV systems than for ST systems. The analysis concludes that share of the population in age group 45-64 years, share of males, share born in Sweden and high average income have a positive correlation to PV adoption. Share of the population within age group 25-44 years, unemployment and low economic standard isfound to have a negative correlation to PV deployment. Positive correlation to ST adoption is found for a share of the population within age group 45-64 years and born in Sweden. Share of population in age group 24-44 years and unemployment was found to have a negative correlation to ST deployment.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-485279 |
Date | January 2022 |
Creators | Ekbring, Sofia |
Publisher | Uppsala universitet, Byggteknik och byggd miljö |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | UPTEC STS, 1650-8319 ; 22035 |
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