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Title: Managing time-substitutable electricity usage using dynamic controls

Abstract

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

Inventors:
; ; ; ;
Issue Date:
Research Org.:
International Business Machines Corp., Armonk, NY (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1771560
Patent Number(s):
10816942
Application Number:
15/352,054
Assignee:
International Business Machines Corporation (Armonk, NY)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06Q - DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y04 - INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS Y04S - SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
DOE Contract Number:  
OE0000190
Resource Type:
Patent
Resource Relation:
Patent File Date: 11/15/2016
Country of Publication:
United States
Language:
English

Citation Formats

Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramanian, Shivaram, and Zhang, Xiaoxuan. Managing time-substitutable electricity usage using dynamic controls. United States: N. p., 2020. Web.
Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramanian, Shivaram, & Zhang, Xiaoxuan. Managing time-substitutable electricity usage using dynamic controls. United States.
Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramanian, Shivaram, and Zhang, Xiaoxuan. Tue . "Managing time-substitutable electricity usage using dynamic controls". United States. https://www.osti.gov/servlets/purl/1771560.
@article{osti_1771560,
title = {Managing time-substitutable electricity usage using dynamic controls},
author = {Ghosh, Soumyadip and Hosking, Jonathan R. and Natarajan, Ramesh and Subramanian, Shivaram and Zhang, Xiaoxuan},
abstractNote = {A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {10}
}

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