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      A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework

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          Abstract

          One of the main challenges of today's society is the need to fulfill at the same time the two sides of the dichotomy between the growing energy demand and the need to look after the environment. Smart Grids are one of the answers: intelligent energy grids which retrieve data about the environment through extensive sensor networks and react accordingly to optimize resource consumption. In order to do this, the Smart Grids need to understand the existing relationship between energy demand and a set of relevant climatic variables. All smart “systems” (buildings, cities, homes, consumers, etc.) have the potential to employ their intelligence for self-adaptation to climate conditions. After introducing the Smart World, a global framework for the collaboration of these smart systems, this paper presents the relationship found at experimental level between a range of relevant weather variables and electric power demand patterns, presenting a case study using an agent-based system, and emphasizing the need to consider this relationship in certain Smart World (and specifically Smart Grid and microgrid) applications.

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          Most cited references62

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          The path of the smart grid

          H Farhangi (2010)
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            Density Forecasting for Long-Term Peak Electricity Demand

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                Sensors (Basel, Switzerland)
                Molecular Diversity Preservation International (MDPI)
                1424-8220
                2012
                27 August 2012
                : 12
                : 9
                : 11571-11591
                Affiliations
                [1 ] CIEMAT (CEDER), Autovía de Navarra A15, salida 56, 42290 Lubia (Soria), Spain
                [2 ] Dpto. TSyCeIT, ETSIT, Universidad de Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain; E-Mails: cbalzor@ 123456ribera.tel.uva.es (C.B.); javagu@ 123456tel.uva.es (J.M.A.); lcaldom@ 123456ribera.tel.uva.es (L.C.); belcar@ 123456tel.uva.es (B.C.); antsan@ 123456tel.uva.es (A.S.-E.)
                [3 ] School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA; E-Mail: cook@ 123456eecs.wsu.edu
                [4 ] Escuela de Ingeniería Informática, Universidad de San Jorge, Campus del Parque Tecnológico Walqa, 22197 Cuarte, (Huesca), Spain; E-Mail: dchinarro@ 123456usj.es
                [5 ] Dpto. Sistemas Informáticos y Programación, Facultad de Informática, Universidad Complutense de Madrid, Juan del Rosal 8, 28040 Madrid, Spain; E-Mail: jjgomez@ 123456fdi.ucm.es
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: luis.hernandez@ 123456ciemat.es ; Tel.: +34-975-281-013; Fax: +34-975-281-051.
                Article
                sensors-12-11571
                10.3390/s120911571
                3478798
                23112671
                7d67488a-51f0-41bc-a239-822ff036e27d
                © 2012 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 06 July 2012
                : 17 August 2012
                : 17 August 2012
                Categories
                Article

                Biomedical engineering
                weather variables,smart world,microgrid,smart city,electric power demand,smart environment,smart grid,sensor

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