PI-controlled ANN-based Energy Consumption Forecasting for Smart Grids

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Tarih

2015

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Dergi ISSN

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Yayıncı

IEEE

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Although Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities must comply with new expectations for their operations, and address new challenges such as energy efficiency regulations and guidelines, possibility of economic recessions, volatility of fuel prices, new user profiles and demands of regulators. In order to meet all these emerging economic and regulatory realities, the electric utilities operating SGs must be able to determine and meet load, implement new technologies that can effect energy sales and interact with their customers for their purchases of electricity. In this respect, load forecasting which has traditionally been done mostly at city or country level can address such issues vital to the electric utilities. In this paper, an artificial neural network based energy consumption forecasting system is proposed and the efficiency of the proposed system is shown with the results of a set of simulation studies. The proposed system can provide valuable inputs to smart grid applications.

Açıklama

12th International Conference on Informatics in Control Automation and Robotics (ICINCO) -- JUL 21-23, 2015 -- Alsace, FRANCE

Anahtar Kelimeler

Smart Grid, Demand Forecasting, Artificial Neural Network, Optimization, Demand Response

Kaynak

Icimco 2015 Proceedings Of The 12th International Conference On Informatics In Control, Automation And Robotics, Vol. 1

WoS Q Değeri

N/A

Scopus Q Değeri

N/A

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