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Multi Agent Control Based Energy Optimization of a Prosumer Household and a Community with Bidirectional Electric Vehicles

Sakarwala, Aliqyaan and Beg, Nauman and Derendorf, Karen and Schuldt, Frank (2023) Multi Agent Control Based Energy Optimization of a Prosumer Household and a Community with Bidirectional Electric Vehicles. In: 16th International Renewable Energy Storage Conference 2022 (IRES 2022), 16, pp. 434-450. Atlantis Press. IRES 2022, 2022-09-20 - 2022-09-22, Düsseldorf, Deutschland. doi: 10.2991/978-94-6463-156-2_28. ISBN 978-94-6463-156-2. ISSN 2589-4943.

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Official URL: https://www.atlantis-press.com/proceedings/ires-22/125987309


Prosumer households with photovoltaic systems face the problem of occasionally generating electricity that cannot be used within the house but must be fed into the electricity grid. This is not desired since with changing policies in Germany, the feed-in tariff has been reduced considerably and the cost of power consumed from the grid has increased significantly. It’s advisable to consume the solar power instead of feeding it into the grid. To achieve this, the excess solar power can be consumed by an electric vehicle present at the household. Additionally, this system can supply power to the household if solar power is insufficient. This study presents how bidirectional electric vehicles can optimize the self-consumption of solar photovoltaic energy and increase the self-sufficiency of the loads in a household and a community (i.e., group of households) by a hierarchical structure of control systems: car, household and community. They are optimizing power flow locally and additionally consider information from the over- and underlying controllers. The car controller is a bidirectional charging station where the electric vehicle is connected, it takes user preferences that are used by the household controller to perform power optimization by handling the mismatch between generation and demand. The community level controller performs an on-the-top optimization which reduces the power flow between the community and the electricity grid. The effect of the proposed system is investigated on a reference distribution grid simulated in the software package DIgSILENT PowerFactory whereas the control framework is developed in Python. Real load and photovoltaic profiles are used to execute the simulations. The results show that there is a 40% and 36% increase in the self-consumption and selfsufficiency on a household level whereas a 51% and 31% increase on a community level when the coordinated control system is implemented.

Item URL in elib:https://elib.dlr.de/194314/
Document Type:Conference or Workshop Item (Poster)
Title:Multi Agent Control Based Energy Optimization of a Prosumer Household and a Community with Bidirectional Electric Vehicles
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Beg, NaumanUNSPECIFIEDhttps://orcid.org/0000-0001-9751-2800UNSPECIFIED
Derendorf, KarenUNSPECIFIEDhttps://orcid.org/0000-0002-0163-3067UNSPECIFIED
Schuldt, FrankUNSPECIFIEDhttps://orcid.org/0000-0002-4196-2025UNSPECIFIED
Date:25 May 2023
Journal or Publication Title:16th International Renewable Energy Storage Conference 2022 (IRES 2022)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 434-450
EditorsEmailEditor's ORCID iDORCID Put Code
Droege, PeterUniversität LichtensteinUNSPECIFIEDUNSPECIFIED
Publisher:Atlantis Press
Series Name:Atlantis Highlights in Engineering
Keywords:Vehicle-to-Grid, Self-Sufficiency, Self-Consumption, Prosumer Household, Electric Vehicles
Event Title:IRES 2022
Event Location:Düsseldorf, Deutschland
Event Type:international Conference
Event Start Date:20 September 2022
Event End Date:22 September 2022
HGF - Research field:Energy
HGF - Program:Energy System Design
HGF - Program Themes:Digitalization and System Technology
DLR - Research area:Energy
DLR - Program:E SY - Energy System Technology and Analysis
DLR - Research theme (Project):E - Energy System Technology
Location: Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems > Energy System Technology
Deposited By: Derendorf, Karen
Deposited On:02 Nov 2023 13:08
Last Modified:24 Apr 2024 20:55

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