Real-Time Control of Plug-in Electric Vehicles for Congestion Management of Radial LV Networks: A Comparison of Implementations

César García Veloso, Kalle Rauma, Julián Fernández and Christian Rehtanz
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César García Veloso: School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 11428 Stockholm, Sweden
Kalle Rauma: Institute of Energy Systems, Energy Efficiency and Energy Economics (ie3), TU Dortmund University, 44227 Dortmund, Germany
Julián Fernández: Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
Christian Rehtanz: Institute of Energy Systems, Energy Efficiency and Energy Economics (ie3), TU Dortmund University, 44227 Dortmund, Germany

Energies, 2020, vol. 13, issue 16, 1-19

Abstract: The global proliferation of plug-in electric vehicles (PEVs) poses a major challenge for current and future distribution systems. If uncoordinated, their charging process may cause congestion on both network transformers and feeders, resulting in overheating, deterioration, protection triggering and eventual risk of failure, seriously compromising the stability and reliability of the grid. To mitigate such impacts and increase their hosting capacity in radial distribution systems, the present study compares the levels of effectiveness and performances of three alternative centralized thermal management formulations for a real-time agent-based charge control algorithm that aims to minimize the total impact upon car owners. A linear formulation and a convex formulation of the optimization problem are presented and solved respectively by means of integer linear programming and a genetic algorithm. The obtained results are then compared, in terms of their total impact on the end-users and overall performance, with those of the current heuristic implementation of the algorithm. All implementations were tested using a simulation environment considering multiple vehicle penetration and base load levels, and equipment modeled after commercially available charging stations and vehicles. Results show how faster resolution times are achieved by the heuristic implementation, but no significant differences between formulations exist in terms of network management and end-user impact. Every vehicle reached its maximum charge level while all thermal impacts were mitigated for all considered scenarios. The most demanding scenario showcased over a 30% reduction in the peak load for all thermal variants.

Keywords: plug-in electric vehicles; radial low voltage networks; real-time control; centralized thermal management; active distribution networks; user impact minimization (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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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