Hierarchical Probabilistic Forecasting of Electricity Demand With 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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Accurate electricity demand forecast plays a key role in sustainable power systems. It enables better decision making in the planning of electricity generation and distribution for many use cases. The electricity demand data can often be represented in a hierarchical structure. For example, the electricity consumption of a whole country could be disaggregated by states, cities, and households. ...
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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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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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In this paper, we investigate a critical problem in smart meter data mining: computing electricity consumption profiles. We present a simple, interpretable and practical profiling framework for residential consumers, which accounts for variations in electricity consumption at different times of day and at different external temperatures. Our approach is to isolate the effect of external tempera...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2020
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2020.1736081