Analysis of Energy Transition Impact on the Low-Voltage Network Using Stochastic Load and Generation Models

Raoul Bernards, Werner van Westering, Johan Morren and Han Slootweg
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Raoul Bernards: Enexis Netbeheer B.V., Magistratenlaan 116, 5223 MB ’s-Hertogenbosch, The Netherlands
Werner van Westering: Delft Center of Systems & Control, Delft University of Technology, Delft Mekelweg 2, 2628 CD Delft, The Netherlands
Johan Morren: Electrical Energy Systems, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
Han Slootweg: Electrical Energy Systems, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands

Energies, 2020, vol. 13, issue 22, 1-21

Abstract: The energy transition poses a challenge for the electricity distribution network design as new energy technologies cause increasing and uncertain network loads. Traditional static load models cannot cope with the stochastic nature of this new technology adoption. Furthermore, traditional nonlinear power methods have difficulty evaluating very large networks with millions of cables, because they are computationally expensive. This paper proposes a method which uses copulas for modeling the uncertainty of technology adoption and load profiles, and combines it with a fast linear load flow model. The copulas are able to accurately model the stochastic behavior of solar irradiance, load measurements, and mobility data, converting them into electricity load profiles. The linear load flow model has better scalability and stability compared to traditional load flow models. The models are applied to a case study which uses a real-world dataset consisting of a realistic technology adoption scenario and a low-voltage network with millions of cables, which considers both voltage and current problems. Results show that risk profiles can be generated for all cables in the network, resulting in a valuable map for the district network operator as to where to focus their efforts.

Keywords: energy transition; copula stochastic modeling; low voltage distribution network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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