6533b822fe1ef96bd127ccf6
RESEARCH PRODUCT
Modeling Energy Demand Aggregators for Residential Consumers
G. Di BellaGiovanni NegliaIlenia TinnirelloMariano Giuseppe IppolitoLaura GiarreAlain Jean-mariesubject
0209 industrial biotechnologydemand-response paradigm020209 energyEnergy current02 engineering and technologycomputer.software_genre7. Clean energyNews aggregatorload regulation[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]020901 industrial engineering & automationdemand side management; load regulation; queueing theory; smart power grids; demand-response paradigm; energy consumers; energy demand aggregator modeling; greedy energy consumers; home users; industrial plants; power load control; queuing theory; residential consumers; smart grids; Delays; Home appliances; Load modeling; Power demand; Sociology; Statistics; Switchesresidential consumerSociologySettore ING-INF/04 - Automatica0202 electrical engineering electronic engineering information engineeringindustrial plantenergy demand aggregator modelingDemand loadSimulationStatisticQueueing theoryDelayLoad modelingdemand side managementSettore ING-INF/03 - Telecomunicazionigreedy energy consumerpower load controlLoad balancing (electrical power)Poisson processEnvironmental economicsGridenergy consumerHome applianceSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSmart gridQueueing theorymart gridLoad regulationqueuing theoryPower demandEnergy demand aggregatorsmart power gridcomputerSwitcheshome userdescription
International audience; Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by considering which scale the aggregator should reach in order to be able to control a significant power load. The challenge of our study derives from residential users' demand being much less predictable than that of industrial plants. For this reason we resort to queuing theory to study analytically the problem and quantify the trade-off between load control and tolerable service delays.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-09-01 |