Collaborative approach for energy cost minimization in smart grid communities

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

Abstract

In this paper we propose a novel demand side management method for minimizing the cost of electricity consumed by households from a smart community. Some households in the community may own renewable energy sources (RESs) and energy storing systems (ESSs). Other households in the community may own ESSs only, while the remaining households are pure energy consumers. The RESs and ESSs owning households can individually optimize their costs by using their available storage spaces and renewable energy production. In this paper we propose a collaborative model in which the RESs and ESSs owners may minimize their costs by exchanging energy and sharing the produced renewable energy and energy storing spaces. They also sell energy to the plain energy consumers at a lower price than that offered by the utility company. We model the collaborative cost minimization as a constrained optimization problem that may be solved as a linear program. Simulation show that the proposed collaborative method may reduce the RESs and ESSs owners' costs by 12 to 50% in comparison to performing individual optimization. The pure energy consumers can also reduce their costs by about 7-8% in comparison to the case of buying all needed energy from the utility company.

Details

Original languageEnglish
Title of host publication2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventIEEE Global Conference on Signal and Information Processing - Montreal, Canada
Duration: 14 Nov 201716 Nov 2017
Conference number: 5

Conference

ConferenceIEEE Global Conference on Signal and Information Processing
Abbreviated titleGlobalSIP
CountryCanada
CityMontreal
Period14/11/201716/11/2017

Download statistics

No data available

ID: 25785043