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access icon openaccess Stochastic modelling of electric vehicle behaviour to estimate available energy storage in parking lots

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 13/01/2020, Accepted 26/05/2020, Revised 22/04/2020, Published 27/05/2020

The increasing penetration of electric vehicles (EVs) brings challenges and opportunities for power systems. One particular opportunity concerns the use of parked EVs to provide energy and associated services to the grid. In this work, the potential energy storage capacity of parking lots (PLs) of EVs is computed using the proposed stochastic model which considers the sporadic nature of the EV’ behaviours (i.e. arrival/departure, battery degradation, travel pattern, charge/discharge rates). The analysis was performed for two types of PLs with very different occupancy distributions, i.e. a shopping centre PL, and a workplace PL. In both cases, the available energy storage capacity of EVs was estimated hourly using real household travel data, i-MiEV data and car park occupancy records. The results show that the aggregated energy storage capacity closely follows the occupancy of EVs in the PLs, and is substantial, with little sensitivity to charging rate. The proposed stochastic modelling considered the variations in energy consumption, battery degradation, and user behaviour, predicted 13.4% less peak capacity than deterministic modelling. Moreover, the authors conclude that the shopping centre PL is a viable energy resource to the grid, with their scale and throughput compensating for the relatively low occupancy.

Inspec keywords: energy conservation; secondary cells; energy consumption; battery powered vehicles; demand side management; energy storage; stochastic processes; electric vehicles

Other keywords: PLs; aggregated energy storage capacity; viable energy resource; parked EVs; electric vehicles; associated services; stochastic modelling; particular opportunity; hourly using real household travel data; battery degradation; EV behaviours; travel pattern; potential energy storage capacity; available energy storage capacity; user behaviour; parking lots; shopping centre PL; car park occupancy records; charging rate; workplace PL; peak capacity; stochastic model; different occupancy distributions; energy consumption; power systems; electric vehicle behaviour; deterministic modelling

Subjects: Optimisation techniques; Secondary cells; Other topics in statistics; Transportation; Secondary cells; Power system management, operation and economics; Other topics in statistics

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