A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework
Open Access
- 27 August 2012
- Vol. 12 (9), 11571-11591
- https://doi.org/10.3390/s120911571
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.Keywords
This publication has 27 references indexed in Scilit:
- The Influence of Recent Climate Change on Tree Height Growth Differs with Species and Spatial EnvironmentPLOS ONE, 2011
- Climate change and electricity consumption—Witnessing increasing or decreasing use and costs?Energy Policy, 2010
- Density Forecasting for Long-Term Peak Electricity DemandIEEE Transactions on Power Systems, 2009
- Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessmentEnergy, 2009
- Analyzing the Impact of Climate Change on Future Electricity Demand in ThailandIEEE Transactions on Power Systems, 2008
- Analyzing the Impact of Weather Variables on Monthly Electricity DemandIEEE Transactions on Power Systems, 2005
- The impacts of weather variations on energy demand and carbon emissionsResource and Energy Economics, 2000
- Non‐Linearities in Electricity Demand and Temperature: Parametric Versus Non‐Parametric MethodsOxford Bulletin of Economics and Statistics, 1997
- Characterizing nonlinearities in business cycles using smooth transition autoregressive modelsJournal of Applied Econometrics, 1992
- Semiparametric Estimates of the Relation between Weather and Electricity SalesJournal of the American Statistical Association, 1986