Demand Forecasting in the Smart Grid Paradigm: Features and Challenges

Hongyu Wu; Mohammad Khodayar

doi:10.1016/j.tej.2015.06.001

Demand Forecasting in the Smart Grid Paradigm: Features and Challenges

Hongyu Wu
, Mohammad Khodayar

Power Systems Engineering

Illinois Institute of Technology

Research output: Contribution to journal › Article › peer-review

40 Scopus Citations

Abstract

Demand forecasting faces challenges that include a large volume of data, increasing number of factors that affect the demand profile, uncertainties in the generation profile of the distributed and renewable generation resources and lack of historical data. A hierarchical demand forecasting framework can incorporate the new technologies, customer behaviors and preferences, and environmental factors.

Original language	American English
Pages (from-to)	51-62
Number of pages	12
Journal	Electricity Journal
Volume	28
Issue number	6
DOIs	https://doi.org/10.1016/j.tej.2015.06.001
State	Published - 2015

NLR Publication Number

NREL/JA-5D00-64946

Keywords

demand forecasting
smart grids

Access to Document

10.1016/j.tej.2015.06.001

Cite this

@article{b2c8966cf6c94936bda4b133b5197b5c,

title = "Demand Forecasting in the Smart Grid Paradigm: Features and Challenges",

abstract = "Demand forecasting faces challenges that include a large volume of data, increasing number of factors that affect the demand profile, uncertainties in the generation profile of the distributed and renewable generation resources and lack of historical data. A hierarchical demand forecasting framework can incorporate the new technologies, customer behaviors and preferences, and environmental factors.",

keywords = "demand forecasting, smart grids",

author = "Hongyu Wu and Mohammad Khodayar",

year = "2015",

doi = "10.1016/j.tej.2015.06.001",

language = "American English",

volume = "28",

pages = "51--62",

journal = "Electricity Journal",

issn = "1040-6190",

publisher = "Elsevier Inc.",

number = "6",

}

TY - JOUR

T1 - Demand Forecasting in the Smart Grid Paradigm: Features and Challenges

AU - Wu, Hongyu

AU - Khodayar, Mohammad

PY - 2015

Y1 - 2015

N2 - Demand forecasting faces challenges that include a large volume of data, increasing number of factors that affect the demand profile, uncertainties in the generation profile of the distributed and renewable generation resources and lack of historical data. A hierarchical demand forecasting framework can incorporate the new technologies, customer behaviors and preferences, and environmental factors.

AB - Demand forecasting faces challenges that include a large volume of data, increasing number of factors that affect the demand profile, uncertainties in the generation profile of the distributed and renewable generation resources and lack of historical data. A hierarchical demand forecasting framework can incorporate the new technologies, customer behaviors and preferences, and environmental factors.

KW - demand forecasting

KW - smart grids

U2 - 10.1016/j.tej.2015.06.001

DO - 10.1016/j.tej.2015.06.001

M3 - Article

SN - 1040-6190

VL - 28

SP - 51

EP - 62

JO - Electricity Journal

JF - Electricity Journal

IS - 6

ER -

Demand Forecasting in the Smart Grid Paradigm: Features and Challenges

Abstract

NLR Publication Number

Keywords

Access to Document

Fingerprint

Cite this