LEADER 01556oam 2200457 450 001 9910150198603321 005 20190911100035.0 010 $a0-7660-8295-4 035 $a(OCoLC)962756528 035 $a(MiFhGG)GVRL05GA 035 $a(EXLCZ)993710000000942256 100 $a20160518h20172017 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSolar energy /$fColin Grady 210 1$aNew York :$cEnslow Publishing,$d2017. 210 4$d?2017 215 $a1 online resource (24 pages) $ccolor illustrations 225 1 $aSaving the planet through green energy 311 $a0-7660-8294-6 320 $aIncludes bibliographical references and index. 327 $aEnergy from the sun -- Passive solar power -- Making electricity -- Solar panels in action -- The future of solar power. 330 $aIn this book, readers will learn how solar panels work, what passive solar power is, and how the sun can be used to make electricity. 410 0$aSaving the planet through green energy. 606 $aSolar energy 606 $aPhotovoltaic power generation 606 $aRenewable energy sources 615 0$aSolar energy. 615 0$aPhotovoltaic power generation. 615 0$aRenewable energy sources. 676 $a333.792/3 700 $aGrady$b Colin$01244953 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910150198603321 996 $aSolar energy$92892609 997 $aUNINA LEADER 05104nam 2201201z- 450 001 9910557116603321 005 20210501 035 $a(CKB)5400000000040880 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68684 035 $a(oapen)doab68684 035 $a(EXLCZ)995400000000040880 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aOpen Data and Energy Analytics 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (218 p.) 311 08$a3-03936-218-6 311 08$a3-03936-219-4 330 $aOpen data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies. 606 $aResearch and information: general$2bicssc 610 $aartificial neural network 610 $abig data 610 $abuilding dataset 610 $abuilding performance simulation 610 $abuilding stock 610 $abuildings 610 $aclassification 610 $aclustering 610 $acollaborative work 610 $adata analytics 610 $adata envelopment analysis 610 $adata mining 610 $adata pre- and post-processing 610 $adata-aware planning 610 $adata-handling 610 $adecision tree 610 $adistrict heating 610 $adomestic hot water 610 $aelectrification modelling 610 $aenergy 610 $aenergy consumption 610 $aenergy data 610 $aenergy efficiency 610 $aenergy management 610 $aenergy mapping 610 $aenergy modelling 610 $aenergy performance certificate 610 $aenergy planning 610 $aenergy potential mapping 610 $aenergy-consuming activities 610 $aEU28 610 $afactor analysis 610 $aforecasting 610 $aheat density map 610 $aheat map 610 $aheating 610 $aheating energy demand 610 $aintegrated assessment modelling 610 $akNN 610 $aKohonen self-organizing maps 610 $amachine learning 610 $aMalawi 610 $amarket assessment 610 $aMESSAGEix 610 $amodel calibration 610 $amultiple regression 610 $aOnSSET 610 $aontology 610 $aopen data 610 $aopen data analytics 610 $aopen energy governance 610 $aopen modelling and data 610 $aparametric modelling 610 $aPassive House 610 $apattern recognition 610 $apolygeneration 610 $arandom forest 610 $aregression 610 $areproducibility 610 $asmart cities 610 $asocial media 610 $aspace heating 610 $aspatial analysis 610 $aspatial planning 610 $asupport vector machine 610 $aurban database 610 $aurban energy atlas 610 $aurban energy transition 615 7$aResearch and information: general 700 $aNastasi$b Benedetto$4edt$01302975 702 $aManfren$b Massimiliano$4edt 702 $aNoussan$b Michel$4edt 702 $aNastasi$b Benedetto$4oth 702 $aManfren$b Massimiliano$4oth 702 $aNoussan$b Michel$4oth 906 $aBOOK 912 $a9910557116603321 996 $aOpen Data and Energy Analytics$93028798 997 $aUNINA