ABSTRACT
Transmission grid congestion is one of the obstacles of renewable energy integration. It is therefore important to understand the causes and consequences of congestion. This paper describes three published data sets that contain pivotal information about transmission grid congestion and two countermeasures, that are typically used in uniform price electricity systems: redispatch and feed-in-management. As such data is rare and not always comprehensively available, these data sets can help to investigate the causes and development of transmission grid congestion. The intention of this paper is to give an overview of the data to help to increase the still rare research activities in the field of empirical congestion analysis. The three data sets, which cover different aspects of transmission grid congestion are described and evaluated as a starting point for future research.
- BDEW. 2018. Redispatch in Deutschland.Google Scholar
- Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen. 2009. Pearson correlation coefficient. In Noise reduction in speech processing. Springer, 1--4. Google ScholarDigital Library
- Valentin Bertsch, Margeret Hall, Christof Weinhardt, and Wolf Fichtner. 2016. Public acceptance andpreferences related to renewable energy and grid expansion policy: Empirical insights for Germany. Energy 114 (2016), 465--477.Google ScholarCross Ref
- Iryna Chychykina and Christian Klabunde Martin Wolter. 2017. Comparison of different redispatch optimization strategies. In 2017 IEEE Manchester PowerTech. IEEE, 1--6.Google Scholar
- Ron Kohavi et al. 1995. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Ijcai, Vol. 14. Montreal, Canada, 1137--1145. Google ScholarDigital Library
- German Federal Republic. 2018. Paragraph 13 Systemverantwortung der Betreiber von Uebertragungsnetzen.Google Scholar
- Hans Schermeyer, Claudio Vergara, and Wolf Fichtner. 2018. Renewable energy curtailment: A case study on today's and tomorrow's congestion management. Energy Policy 112 (2018), 427--436.Google ScholarCross Ref
- Philipp Staudt, Benjamin Rausch, and Christof Weinhardt. 2019. Congestion data of 50 Hertz 2015-2017.Google Scholar
- Philipp Staudt, Benjamin Rausch, and Christof Weinhardt. 2019. Redispatch data Germany 2015-2017.Google Scholar
- Philipp Staudt, Benjamin Rausch, and Christof Weinhardt. 2019. Renewable feed-in management data Germany 2015-2018.Google Scholar
- Philipp Staudt, Benjamin Rausch, Christof Weinhardt, et al. 2018. Predicting Redispatch in the German Electricity Market using Information Systems based on Machine Learning. (2018).Google Scholar
- Philipp Staudt, Marc Schmidt, Johannes Gärttner, and Christof Weinhardt. 2018. A decentralized approach towards resolving transmission grid congestion in Germany using vehicle-to-grid technology. Applied energy 230 (2018), 1435--1446.Google Scholar
- Katrin Trepper, Michael Bucksteeg, and Christoph Weber. 2015. Market splitting in Germany--New evidence from a three-stage numerical model of Europe. Energy Policy 87 (2015), 199--215.Google ScholarCross Ref
Index Terms
- Transmission Grid Congestion Data and Directions for Future Research
Recommendations
On Explicit Congestion Notification for Stream Control Transmission Protocol in Lossy Networks
As a congestion avoidance mechanism, Explicit Congestion Notification (ECN) is designed to inform a data source to react to potential congestion early. Currently, the new transport protocol, Stream Control Transmission Protocol (SCTP), is not ECN-...
TCP and explicit congestion notification
This paper discusses the use of Explicit Congestion Notification (ECN) mechanisms in the TCP/IP protocol. The first part proposes new guidelines for TCP's response to ECN mechanisms (e.g., Source Quench packets, ECN fields in packet headers). Next, ...
Comments