Modeling Energy Demand Aggregators for Residential Consumers
type: Dataset
description: 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 report 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.
identifier: Report N°: RR-8355
issued: 2026-05-09T17:01:50.965518
language: en
modified: 2026-05-09T17:01:50.965524
contact point: Organization
  fn: CCSD
keyword: energy-demand-aggregators
keyword: infoeu-reposemanticsreport
keyword: infoinfo-nicomputer-science-csnetworking-and-internet-architecture-csni
keyword: poisson-process
keyword: queueing-theory
keyword: reports
landing page: https://inria.hal.science/hal-00863243

Modeling Energy Demand Aggregators for Residential Consumers
type: Distribution
format: HTML
issued: 2026-05-09T17:01:50.966851
modified: 2026-05-09T17:01:50.957479
access URL: https://inria.hal.science/hal-00863243

test_moissonnage_selune
type: Agent