Stochastic modelling of electric vehicle behaviour to estimate available energy storage in parking lots. Issue 6 (10th July 2020)

• Record Type: Journal Article
• Authors: Bin Irshad, Usama; Rafique, Sohaib; Town, Graham
• Is Part Of: IET smart grid. Volume 3:Issue 6(2020)
• Page Start: 760
• Page End: 767
• Publication Date: 2020-07-10
• Subjects: energy consumption -- energy storage -- energy conservation -- secondary cells -- demand side management -- electric vehicles -- stochastic processes -- battery powered vehicles; battery degradation -- travel pattern -- PLs -- different occupancy distributions -- shopping centre PL -- workplace PL -- available energy storage capacity -- hourly using real household travel data -- car park occupancy records -- aggregated energy storage capacity -- charging rate -- stochastic modelling -- energy consumption -- user behaviour -- peak capacity -- deterministic modelling -- viable energy resource -- electric vehicle behaviour -- parking lots -- electric vehicles -- power systems -- particular opportunity -- parked EVs -- associated services -- potential energy storage capacity -- stochastic model -- EV behaviours; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2020.0011
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : 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.