Open Data and Energy Analytics

• Autore: Nastasi Benedetto
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 online resource (218 p.)
• Soggetto topico: Research and information: general
• Soggetto non controllato: artificial neural network; big data; building dataset; building performance simulation; building stock; buildings; classification; clustering; collaborative work; data analytics; data envelopment analysis; data mining; data pre- and post-processing; data-aware planning; data-handling; decision tree; district heating; domestic hot water; electrification modelling; energy; energy consumption; energy data; energy efficiency; energy management; energy mapping; energy modelling; energy performance certificate; energy planning; energy potential mapping; energy-consuming activities; EU28; factor analysis; forecasting; heat density map; heat map; heating; heating energy demand; integrated assessment modelling; kNN; Kohonen self-organizing maps; machine learning; Malawi; market assessment; MESSAGEix; model calibration; multiple regression; OnSSET; ontology; open data; open data analytics; open energy governance; open modelling and data; parametric modelling; Passive House; pattern recognition; polygeneration; random forest; regression; reproducibility; smart cities; social media; space heating; spatial analysis; spatial planning; support vector machine; urban database; urban energy atlas; urban energy transition
• Persona (resp. second.): ManfrenMassimiliano; NoussanMichel; NastasiBenedetto
• Sommario/riassunto: Open 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.
• Titolo autorizzato: Open Data and Energy Analytics
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557116603321
• Lo trovi qui: Univ. Federico II