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Combined PV Power and Load Prediction for Building-Level Energy Management Applications

Telle, Jan-Simon and Maitanova, Nailya and Steens, Thomas and Hanke, Benedikt and von Maydell, Karsten and Grottke, Matthias (2020) Combined PV Power and Load Prediction for Building-Level Energy Management Applications. In: 2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020. IEEE. 2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), 10.-12. Sept. 2020, Online / Monte-Carlo, Monaco. doi: 10.1109/EVER48776.2020.9243026. ISBN 978-172815641-5.

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Abstract

In order to successfully integrate renewable energy technologies, the requirements of local energy management systems are becoming increasingly complex, as is the sector integration of electricity, heat and transportation. To address this, this study investigated the combination of machine learning-based PV power and load demand prediction approaches to forecast residual load at the building level. The forecast accuracy, seasonal dependencies and the effects of single forecasts on the residual load were evaluated by means of three different metrics, namely: mean absolute error (MAE), root-mean-square error (RMSE) and the mean absolute scaled error (MASE). The applicability of the combined forecast was tested via a case study of integrated battery-electric vehicles and a PV system in an existing commercial building. The results show how the residual load forecast can help schedule grid-friendly charging demand and optimize PV self-consumption.

Item URL in elib:https://elib.dlr.de/137127/
Document Type:Conference or Workshop Item (Speech)
Title:Combined PV Power and Load Prediction for Building-Level Energy Management Applications
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Telle, Jan-SimonJan-Simon.Telle (at) dlr.dehttps://orcid.org/0000-0001-6228-6815
Maitanova, NailyaNailya.Maitanova (at) dlr.dehttps://orcid.org/0000-0003-1287-8139
Steens, ThomasThomas.Steens (at) dlr.dehttps://orcid.org/0000-0002-4218-3015
Hanke, BenediktBenedikt.Hanke (at) dlr.dehttps://orcid.org/0000-0001-7927-0123
von Maydell, KarstenKarsten.Maydell (at) dlr.dehttps://orcid.org/0000-0003-0966-5810
Grottke, MatthiasMatthias.Grottke (at) hammer.agUNSPECIFIED
Date:2 November 2020
Journal or Publication Title:2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI :10.1109/EVER48776.2020.9243026
Publisher:IEEE
Series Name:2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)
ISBN:978-172815641-5
Status:Published
Keywords:Combined PV-power and load prediction, load Management in commercial buildings, machin learning approaches, optimized charging of battery electric vehicles
Event Title:2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)
Event Location:Online / Monte-Carlo, Monaco
Event Type:international Conference
Event Dates:10.-12. Sept. 2020
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Energy Systems Technology (old)
Location: Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems > Energy System Technology
Deposited By: Telle, Jan-Simon
Deposited On:11 Nov 2020 15:39
Last Modified:12 Jul 2021 10:00

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