Peak demand alert system based on electricity demand forecasting for smart meter data
نویسندگان
چکیده
منابع مشابه
Hierarchical Probabilistic Forecasting of Electricity Demand with Smart Meter Data
Electricity smart meters record consumption, on a near real-time basis, at the level of individual commercial and residential properties. From this, a hierarchy can be constructed consisting of time series of demand at the smart meter level, and at various levels of aggregation, such as substations, cities and regions. Forecasts are needed at each level to support the efficient and reliable man...
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Over the past years, smart meters have been widely deployed in many countries. These devices replace conventional electrical meters and are able to provide measurements for time intervals of typically less than one hour and can send these to the utility. This technology provides utilities a large amount of data and the opportunity to use this data to improve the way they run the grid. We want t...
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We want to forecast the peak electricity demand in a half-hour period in twenty years time. We have fifteen years of half-hourly electricity data, temperature data and some economic and demographic data. The location is South Australia: home to the most volatile electricity demand in the world.
متن کاملDemand Forecasting for Electricity
Introduction Forecasting demand is both a science and an art. Econometric methods of forecasting, in the context of energy demand forecasting, can be described as ‘the science and art of specification, estimation, testing and evaluation of models of economic processes’ that drive the demand for fuels. The need and relevance of forecasting demand for an electric utility has become a much-discuss...
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Generalized Additive Models (GAM) are a widely popular class of regression models to forecast electricity demand, due to their high accuracy, flexibility and interpretability. However, the residuals of the fitted GAM are typically heteroscedastic and leptokurtic caused by the nature of energy data. In this paper we propose a novel approach to estimate the time-varying conditional variance of th...
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ژورنال
عنوان ژورنال: Energy and Buildings
سال: 2020
ISSN: 0378-7788
DOI: 10.1016/j.enbuild.2020.110307