This paper addresses the problem of electric load forecasting for distribution networks with Active Demand (AD), a new concept in smart-grids introduced within the EU project ADDRESS. By changing the typical consumption pattern of the consumers, AD adds a new dimension to the problem of load forecasting, and therefore makes currently available load forecasting techniques no more suitable. A new approach to load forecasting in the presence of AD is therefore proposed. The approach is based on a decomposition of the load into its components, namely the base load (representing different seasonal patterns), and a residual term depending both on stochastic fluctuations and AD effects. The performance of the proposed approach is illustrated through a numerical example. Since data sets including AD are not yet available, in the numerical example AD effects are simulated and added to real measurements representing the aggregated load of about 60 consumers from an Italian LV network.

Paoletti, S., Casini, M., Giannitrapani, A., Facchini, A., Garulli, A., Vicino, A. (2011). Load forecasting for active distribution networks. In Proc. of 2nd IEEE PES Innovative Smart Grid Technologies Europe (pp.1-6). New York, USA : IEEE [10.1109/ISGTEurope.2011.6162780].

Load forecasting for active distribution networks

PAOLETTI, SIMONE;CASINI, MARCO;GIANNITRAPANI, ANTONIO;FACCHINI, ANGELO;GARULLI, ANDREA;VICINO, ANTONIO
2011-01-01

Abstract

This paper addresses the problem of electric load forecasting for distribution networks with Active Demand (AD), a new concept in smart-grids introduced within the EU project ADDRESS. By changing the typical consumption pattern of the consumers, AD adds a new dimension to the problem of load forecasting, and therefore makes currently available load forecasting techniques no more suitable. A new approach to load forecasting in the presence of AD is therefore proposed. The approach is based on a decomposition of the load into its components, namely the base load (representing different seasonal patterns), and a residual term depending both on stochastic fluctuations and AD effects. The performance of the proposed approach is illustrated through a numerical example. Since data sets including AD are not yet available, in the numerical example AD effects are simulated and added to real measurements representing the aggregated load of about 60 consumers from an Italian LV network.
2011
978-1-4577-1421-4
Paoletti, S., Casini, M., Giannitrapani, A., Facchini, A., Garulli, A., Vicino, A. (2011). Load forecasting for active distribution networks. In Proc. of 2nd IEEE PES Innovative Smart Grid Technologies Europe (pp.1-6). New York, USA : IEEE [10.1109/ISGTEurope.2011.6162780].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/21824