A Cyber-Physical Residential Energy Management System via Virtualized Packets
This paper proposes a cyber-physical system to manage flexible residential loads based on virtualized energy packets. Before being used, flexible loads need to request packets to an energy server, which may be granted or not. If granted, the energy server guarantees that the request will be fulfille...
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doaj-6ab0476e81db48359cf61946809a10c62020-11-25T03:32:39ZengMDPI AGEnergies1996-10732020-02-0113369910.3390/en13030699en13030699A Cyber-Physical Residential Energy Management System via Virtualized PacketsMauricio de Castro Tomé0Pedro H. J. Nardelli1Hafiz Majid Hussain2Sohail Wahid3Arun Narayanan4Centre for Wireless Communications, University of Oulu, 90570 Oulu, FinlandCentre for Wireless Communications, University of Oulu, 90570 Oulu, FinlandSchool of Energy Systems, LUT University, 53850 Lappeenranta, FinlandSchool of Energy Systems, LUT University, 53850 Lappeenranta, FinlandSchool of Energy Systems, LUT University, 53850 Lappeenranta, FinlandThis paper proposes a cyber-physical system to manage flexible residential loads based on virtualized energy packets. Before being used, flexible loads need to request packets to an energy server, which may be granted or not. If granted, the energy server guarantees that the request will be fulfilled. Each different load has a specific consumption profile and user requirement. In the proposed case study, the residential consumers share a pool of energy resources that need to be allocated by the energy server whose aim is to minimize the imports related to such a group. The proposed solution shows qualitative advantages compared to the existing approaches in relation to computational complexity, fairness of the resource allocation outcomes and effectiveness in peak reduction. We demonstrate our solution based on three different representative flexible loads; namely, electric vehicles, saunas and dishwashers. The numerical results show the efficacy of the proposed solution for three different representative examples, demonstrating the advantages and drawbacks of different allocation rules.https://www.mdpi.com/1996-1073/13/3/699demand-side managementenergy internetpacketized energy managementenergy allocation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mauricio de Castro Tomé Pedro H. J. Nardelli Hafiz Majid Hussain Sohail Wahid Arun Narayanan |
spellingShingle |
Mauricio de Castro Tomé Pedro H. J. Nardelli Hafiz Majid Hussain Sohail Wahid Arun Narayanan A Cyber-Physical Residential Energy Management System via Virtualized Packets Energies demand-side management energy internet packetized energy management energy allocation |
author_facet |
Mauricio de Castro Tomé Pedro H. J. Nardelli Hafiz Majid Hussain Sohail Wahid Arun Narayanan |
author_sort |
Mauricio de Castro Tomé |
title |
A Cyber-Physical Residential Energy Management System via Virtualized Packets |
title_short |
A Cyber-Physical Residential Energy Management System via Virtualized Packets |
title_full |
A Cyber-Physical Residential Energy Management System via Virtualized Packets |
title_fullStr |
A Cyber-Physical Residential Energy Management System via Virtualized Packets |
title_full_unstemmed |
A Cyber-Physical Residential Energy Management System via Virtualized Packets |
title_sort |
cyber-physical residential energy management system via virtualized packets |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2020-02-01 |
description |
This paper proposes a cyber-physical system to manage flexible residential loads based on virtualized energy packets. Before being used, flexible loads need to request packets to an energy server, which may be granted or not. If granted, the energy server guarantees that the request will be fulfilled. Each different load has a specific consumption profile and user requirement. In the proposed case study, the residential consumers share a pool of energy resources that need to be allocated by the energy server whose aim is to minimize the imports related to such a group. The proposed solution shows qualitative advantages compared to the existing approaches in relation to computational complexity, fairness of the resource allocation outcomes and effectiveness in peak reduction. We demonstrate our solution based on three different representative flexible loads; namely, electric vehicles, saunas and dishwashers. The numerical results show the efficacy of the proposed solution for three different representative examples, demonstrating the advantages and drawbacks of different allocation rules. |
topic |
demand-side management energy internet packetized energy management energy allocation |
url |
https://www.mdpi.com/1996-1073/13/3/699 |
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