FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2793676216> ?p ?o ?g. }

• W2793676216 endingPage "211" @default.
• W2793676216 startingPage "189" @default.
• W2793676216 abstract "Abstract Photovoltaic (PV) panels are a very promising technology that answers part of the increasing need for global renewable energy production, particularly in urban areas. We present a novel methodology combining Geographic Information Systems (GIS), solar models and a Machine Learning (ML) algorithm, Random Forests, to estimate the potential for rooftop PV solar energy at the scale of a country. We use a hierarchical approach which divides the computation of the final potential into several steps. Each step is reached by estimating multiple variables of interest using widely available data, and combining these variables into potential values. The method for estimating each variable of interest is as follows: (1) collect all the data related to the variable, (2) train a Random Forest model based on the collected data and (3) use the model to predict the variables in unknown locations. The variables of interest include available area for PV installation on rooftops, shape, slope and direction of rooftops, global solar horizontal and tilted radiations, as well as shading factors over rooftops. The study focuses on Switzerland and provides the rooftop PV technical potential for each (200 × 200) [m2] pixel of a grid covering the entire country. The methodology, however, is generalizable to any region for which similar data is available and could therefore be useful for researchers, energy service companies, stockholders and municipalities to assess the rooftop PV capacity of the region. Prediction Intervals are also provided for the different estimated variables, in order to measure the uncertainty of the estimations. The results show that Switzerland has a large potential for rooftop PV installations. More specifically, for roofs orientated at ± 90 ° from due south, the total estimated potential PV electricity production is about 16.29 TWh/year, which corresponds to 25.3% of the total electricity demand in 2017." @default.
• W2793676216 created "2018-03-29" @default.
• W2793676216 creator A5031505076 @default.
• W2793676216 creator A5065992543 @default.
• W2793676216 creator A5083629220 @default.
• W2793676216 date "2018-05-01" @default.
• W2793676216 modified "2023-10-12" @default.
• W2793676216 title "Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests" @default.
• W2793676216 cites W1120922828 @default.
• W2793676216 cites W1191826283 @default.
• W2793676216 cites W1875061881 @default.
• W2793676216 cites W1963920400 @default.
• W2793676216 cites W1975688506 @default.
• W2793676216 cites W1981176609 @default.
• W2793676216 cites W1986009302 @default.
• W2793676216 cites W1989513893 @default.
• W2793676216 cites W1990701853 @default.
• W2793676216 cites W1993693581 @default.
• W2793676216 cites W1994725169 @default.
• W2793676216 cites W2003879698 @default.
• W2793676216 cites W2009283913 @default.
• W2793676216 cites W2015929940 @default.
• W2793676216 cites W2018856214 @default.
• W2793676216 cites W2019135906 @default.
• W2793676216 cites W2033406960 @default.
• W2793676216 cites W2039240409 @default.
• W2793676216 cites W2039392443 @default.
• W2793676216 cites W2040255771 @default.
• W2793676216 cites W2046890513 @default.
• W2793676216 cites W2052958822 @default.
• W2793676216 cites W2056239924 @default.
• W2793676216 cites W2064661229 @default.
• W2793676216 cites W2076491061 @default.
• W2793676216 cites W2086350890 @default.
• W2793676216 cites W2086982321 @default.
• W2793676216 cites W2089487480 @default.
• W2793676216 cites W2159961704 @default.
• W2793676216 cites W2508967951 @default.
• W2793676216 cites W2565802871 @default.
• W2793676216 cites W2569349941 @default.
• W2793676216 cites W2591643705 @default.
• W2793676216 cites W2729015950 @default.
• W2793676216 cites W2749305807 @default.
• W2793676216 cites W2756625063 @default.
• W2793676216 cites W2762911305 @default.
• W2793676216 cites W2911964244 @default.
• W2793676216 cites W3125121909 @default.
• W2793676216 cites W3125269015 @default.
• W2793676216 doi "https://doi.org/10.1016/j.apenergy.2018.02.118" @default.
• W2793676216 hasPublicationYear "2018" @default.
• W2793676216 type Work @default.
• W2793676216 sameAs 2793676216 @default.
• W2793676216 citedByCount "100" @default.
• W2793676216 countsByYear W27936762162018 @default.
• W2793676216 countsByYear W27936762162019 @default.
• W2793676216 countsByYear W27936762162020 @default.
• W2793676216 countsByYear W27936762162021 @default.
• W2793676216 countsByYear W27936762162022 @default.
• W2793676216 countsByYear W27936762162023 @default.
• W2793676216 crossrefType "journal-article" @default.
• W2793676216 hasAuthorship W2793676216A5031505076 @default.
• W2793676216 hasAuthorship W2793676216A5065992543 @default.
• W2793676216 hasAuthorship W2793676216A5083629220 @default.
• W2793676216 hasBestOaLocation W27936762161 @default.
• W2793676216 hasConcept C119599485 @default.
• W2793676216 hasConcept C127413603 @default.
• W2793676216 hasConcept C154945302 @default.
• W2793676216 hasConcept C169258074 @default.
• W2793676216 hasConcept C201995342 @default.
• W2793676216 hasConcept C205649164 @default.
• W2793676216 hasConcept C2778755073 @default.
• W2793676216 hasConcept C39432304 @default.
• W2793676216 hasConcept C41008148 @default.
• W2793676216 hasConcept C41291067 @default.
• W2793676216 hasConcept C541104983 @default.
• W2793676216 hasConcept C542589376 @default.
• W2793676216 hasConcept C58640448 @default.
• W2793676216 hasConcept C96250715 @default.
• W2793676216 hasConceptScore W2793676216C119599485 @default.
• W2793676216 hasConceptScore W2793676216C127413603 @default.
• W2793676216 hasConceptScore W2793676216C154945302 @default.
• W2793676216 hasConceptScore W2793676216C169258074 @default.
• W2793676216 hasConceptScore W2793676216C201995342 @default.
• W2793676216 hasConceptScore W2793676216C205649164 @default.
• W2793676216 hasConceptScore W2793676216C2778755073 @default.
• W2793676216 hasConceptScore W2793676216C39432304 @default.
• W2793676216 hasConceptScore W2793676216C41008148 @default.
• W2793676216 hasConceptScore W2793676216C41291067 @default.
• W2793676216 hasConceptScore W2793676216C541104983 @default.
• W2793676216 hasConceptScore W2793676216C542589376 @default.
• W2793676216 hasConceptScore W2793676216C58640448 @default.
• W2793676216 hasConceptScore W2793676216C96250715 @default.
• W2793676216 hasFunder F4320320924 @default.
• W2793676216 hasFunder F4320320998 @default.
• W2793676216 hasLocation W27936762161 @default.
• W2793676216 hasOpenAccess W2793676216 @default.
• W2793676216 hasPrimaryLocation W27936762161 @default.
• W2793676216 hasRelatedWork W1542638601 @default.

• next