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Forecast of Renewable Curtailment in Distribution Grids Considering Uncertainties

Memmel, Elena and Schlüters, Sunke and Völker, Rasmus and Schuldt, Frank and von Maydell, Karsten and Agert, Carsten (2021) Forecast of Renewable Curtailment in Distribution Grids Considering Uncertainties. IEEE Access, 9, pp. 60828-60840. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/ACCESS.2021.3073754. ISSN 2169-3536.

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Abstract

Renewable energies curtailment induced by grid congestions increase due to grown renewable energies integration and the resulting mismatch of grid expansion. Short-term predictions for curtailment can help to increase the efficiency of its management. This paper proposes a novel, holistic approach of a short-term curtailment prediction for distribution grids. The load flow calculations for congestion detection are realized by taking different operational security criteria into account, whereas the models for the node-injections are adjusted to the characteristic of each grid node specifically. The determination of required curtailment based on the resulting congestions considers uncertainties of component loading and its corresponding probability. The forecast model is validated using an actual 110 kV distribution grid located in Germany. In order to meet the requirements of a forecast model designed for operational business, prediction accuracy, and its greatest source of error are analyzed. Furthermore, a suitable length of training data is investigated. Results indicate that a six month time period for maintenance gains the highest accuracy. Curtailment prediction accuracy is better for transmission system operator components than for distribution system operator components, but the Słrensen Dice factor for the aggregated grid shows a high match of historic and predicted curtailment with a value of 0.84 and a low error for curtailed energy, which makes 2.23% of the historic curtailed energy. The model is a promising approach, which can contribute to improvement of curtailment strategies and enable valuable insight into distribution grids.

Item URL in elib:https://elib.dlr.de/142664/
Document Type:Article
Title:Forecast of Renewable Curtailment in Distribution Grids Considering Uncertainties
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Memmel, ElenaElena.Memmel (at) dlr.dehttps://orcid.org/0000-0003-0619-5905
Schlüters, Sunkesunke.schlueters (at) dlr.dehttps://orcid.org/0000-0002-2186-812X
Völker, RasmusRasmus.Voelker (at) dlr.deUNSPECIFIED
Schuldt, FrankDLR-Institut für Vernetzte Energiesysteme e.V.https://orcid.org/0000-0002-4196-2025
von Maydell, KarstenKarsten.Maydell (at) dlr.dehttps://orcid.org/0000-0003-0966-5810
Agert, Carstencarsten.agert (at) dlr.dehttps://orcid.org/0000-0003-4733-5257
Date:16 April 2021
Journal or Publication Title:IEEE Access
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:9
DOI :10.1109/ACCESS.2021.3073754
Page Range:pp. 60828-60840
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:2169-3536
Status:Published
Keywords:Power system operation, distribution grid, power flow analysis, congestion management, renewable power curtailment, short-term prediction, probabilistic uncertainty quantification
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: Memmel, Elena
Deposited On:21 Jun 2021 11:13
Last Modified:21 Jun 2021 11:13

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