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Extension algorithm for generic low-voltage networks

: Marwitz, Simon; Olk, Christopher

Volltext urn:nbn:de:0011-n-4917378 (350 KByte PDF)
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Erstellt am: 8.5.2018

Institute of Physics -IOP-, London:
SciGRID International Conference on Power Grid Modelling 2017 : 30-31 March 2017, Oldenburg, Germany
Bristol: IOP Publishing, 2018 (Journal of physics. Conference series 977)
Art. 012006, 9 S.
International Conference on Power Grid Modelling <2017, Oldenburg>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ISI ()

Distributed energy resources (DERs) are increasingly penetrating the energy system which is driven by climate and sustainability goals. These technologies are mostly connected to low-voltage electrical networks and change the demand and supply situation in these networks. This can cause critical network states. Network topologies vary significantly and depend on several conditions including geography, historical development, network design or number of network connections. In the past, only some of these aspects were taken into account when estimating the network investment needs for Germany on the low-voltage level. Typically, fixed network topologies are examined or a Monte Carlo approach is used to quantify the investment needs at this voltage level. Recent research has revealed that DERs differ substantially between rural, suburban and urban regions. The low-voltage network topologies have different design concepts in these regions, so that different network topologies have to be considered when assessing the need for network extensions and investments due to DERs. An extension algorithm is needed to calculate network extensions and investment needs for the different typologies of generic low-voltage networks. We therefore present a new algorithm, which is capable of calculating the extension for generic low-voltage networks of any given topology based on voltage range deviations and thermal overloads. The algorithm requires information about line and cable lengths, their topology and the network state only. We test the algorithm on a radial, a loop, and a heavily meshed network. Here we show that the algorithm functions for electrical networks with these topologies. We found that the algorithm is able to extend different networks efficiently by placing cables between network nodes. The main value of the algorithm is that it does not require any information about routes for additional cables or positions for additional substations when it comes to estimating network extension needs.