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:
- 1344421
- Patent Number(s):
- 9576327
- Application Number:
- 13/912,181
- Assignee:
- INTERNATIONAL BUSINESS MACHINES CORPORATION
- 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: 2013 Jun 06
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Citation Formats
Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramaniam, Shivaram, and Zhang, Xiaoxuan. Managing time-substitutable electricity usage using dynamic controls. United States: N. p., 2017.
Web.
Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramaniam, Shivaram, & Zhang, Xiaoxuan. Managing time-substitutable electricity usage using dynamic controls. United States.
Ghosh, Soumyadip, Hosking, Jonathan R., Natarajan, Ramesh, Subramaniam, Shivaram, and Zhang, Xiaoxuan. Tue .
"Managing time-substitutable electricity usage using dynamic controls". United States. https://www.osti.gov/servlets/purl/1344421.
@article{osti_1344421,
title = {Managing time-substitutable electricity usage using dynamic controls},
author = {Ghosh, Soumyadip and Hosking, Jonathan R. and Natarajan, Ramesh and Subramaniam, 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 = {2017},
month = {2}
}
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