TY - GEN
T1 - A framework for demand-side management with demand response input
AU - Peinado-Guerrero, Miguel A.
AU - Campbell, Nicolas A.
AU - Villalobos, Jesus R.
AU - Phelan, Patrick E.
N1 - Funding Information: Acknowledgment for the funding of this work goes to Salt River Project (SRP) and the Industrial Assessment Program of the U.S. Department of Energy. Publisher Copyright: Copyright © 2020 ASME.
PY - 2020
Y1 - 2020
N2 - A framework is proposed for demand-side load management (DSLM) of manufacturers participating in demand response (DR) programs. Utilities are increasingly focused on enticing their portfolios of energy end-users to adjust their energy use patterns in a mutually beneficial manner such as with DR programs. DR programs allow the utility to receive bulk peak load reduction and the participating end-user to receive credit towards their electricity bills. Once an end-user is enrolled in a DR program, they receive periodic requests for some amount of load reduction, typically the day before. Failing to respond to a DR signal will usually cost the end-user handsomely. The enduser is often left to their own discretion on how to attain the level of load reduction requested by the utility. For a manufacturer, this means if the request in load reduction is high enough, they will need to figure out how to curtail production. On the other hand, if the load reduction requested is small enough to need no disruption to production, the utility may be missing out on untapped DR capabilities that could be offered from the ability of the manufacturer to reschedule their production. In either case, the availability of an optimal plan for the manufacturer to best schedule its production in response to a DR event can maximize the benefits for both parties. Most of the research found in literature addresses production scheduling with minimal energy use or cost with respect to a time-of-use price tariff. A system that communicates the desires of the utility to the end-user for a DR event and provides the end-user with support in the decision-making process remains to be developed. The framework proposed addresses these shortcomings, considering the introduction of IoT capabilities and the physical constraints of the manufacturer.
AB - A framework is proposed for demand-side load management (DSLM) of manufacturers participating in demand response (DR) programs. Utilities are increasingly focused on enticing their portfolios of energy end-users to adjust their energy use patterns in a mutually beneficial manner such as with DR programs. DR programs allow the utility to receive bulk peak load reduction and the participating end-user to receive credit towards their electricity bills. Once an end-user is enrolled in a DR program, they receive periodic requests for some amount of load reduction, typically the day before. Failing to respond to a DR signal will usually cost the end-user handsomely. The enduser is often left to their own discretion on how to attain the level of load reduction requested by the utility. For a manufacturer, this means if the request in load reduction is high enough, they will need to figure out how to curtail production. On the other hand, if the load reduction requested is small enough to need no disruption to production, the utility may be missing out on untapped DR capabilities that could be offered from the ability of the manufacturer to reschedule their production. In either case, the availability of an optimal plan for the manufacturer to best schedule its production in response to a DR event can maximize the benefits for both parties. Most of the research found in literature addresses production scheduling with minimal energy use or cost with respect to a time-of-use price tariff. A system that communicates the desires of the utility to the end-user for a DR event and provides the end-user with support in the decision-making process remains to be developed. The framework proposed addresses these shortcomings, considering the introduction of IoT capabilities and the physical constraints of the manufacturer.
KW - Decision-making
KW - Demand response
KW - Demand-side load management
KW - Energy management
KW - Load shifting
KW - Mathematical programming
KW - Optimization
KW - Smart grid
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UR - http://www.scopus.com/inward/citedby.url?scp=85094182196&partnerID=8YFLogxK
U2 - 10.1115/POWER2020-16635
DO - 10.1115/POWER2020-16635
M3 - Conference contribution
T3 - American Society of Mechanical Engineers, Power Division (Publication) POWER
BT - ASME 2020 Power Conference, POWER 2020, collocated with the 2020 International Conference on Nuclear Engineering
PB - American Society of Mechanical Engineers (ASME)
T2 - 2019 Canadian Society for Civil Engineering Annual Conference, CSCE 2019
Y2 - 12 June 2019 through 15 June 2019
ER -