Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid
Sajjad Haider and
Peter Schegner
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Sajjad Haider: Boysen-TU Dresden-Research Training Group, Chair of Electrical Power Supply, Technical University of Dresden, 01062 Dresden, Germany
Peter Schegner: Institute of Electrical Power Systems and High Voltage Engineering, Technical University of Dresden, 01062 Dresden, Germany
Energies, 2020, vol. 13, issue 22, 1-19
Abstract:
It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.
Keywords: electric vehicles; optimization; low voltage; network; heuristic (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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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:22:p:6069-:d:447931
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