Autori
May, Caterina
Fusai, Gianluca

Titolo
Functional clustering and linear regression for peak load forecasting
Periodico
Università degli Studi del Piemonte Orientale 'A. Avogadro' : Facoltà di Economia - Dipartimento di Scienze Economiche e Metodi Quantitativi "SEMEQ" - Quaderni
Anno: 2008 - Fascicolo: 5 - Pagina iniziale: 1 - Pagina finale: 20

In this paper we consider the problem of short-term peak load forecasting using past load demand data in a co-generation system. Our data-set consists of four separated periods, with 198 days each period and 24 hourly observations within each day. It presents two seasonality patterns: an intra-daily seasonality and a seasonality effect within each period. We take advantage of the functional nature of the data-set and we propose a forecasting methodology based on functional statistics. In particular, we use a functional clustering to classify the daily load curves. Then on the basis of the obtained groups we define a family of functional linear regression models. To make forecast we assign new load curves to clusters applying a functional discriminant analysis. Finally we evaluate the performance of the proposed approach in comparison with classical models.



Testo completo: http://semeq.unipmn.it/files/quaderno%20goia5.pdf

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