Forecasting Electricity Demand Using Gener- alized Long Memory

  title={Forecasting Electricity Demand Using Gener- alized Long Memory},
  author={Ensaios Econ{\^o}micos and Lacir Jorge Soares and Leonardo Rocha Souza and Fundaç{\^a}o Getulio Vargas and Escola DE P{\'O}S-GRADUAÇ{\~A}O and em Economia and Diretor Geral and Renato Fragelli Cardoso and Diretor de Ensino and Luis Henrique Bertolino Braido and Diretor de Pesquisa and Jo{\~a}o Victor Issler and Ricardo de Oliveira Cavalcanti and Jorge Soares},
This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies… CONTINUE READING

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