Next Article in Journal
Analysis of Fuel Economy and Battery Life depending on the Types of HEV using Dynamic Programming
Previous Article in Journal
Capacitor Based Battery Balancing System
 
 
World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Previous articles were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Electric Vehicles and the Smart Grid: Spatial Modelling of Impacts and Opportunities

CSIRO Energy Transformed Flagship, PO Box 56, Highett, VIC, 3190, Australia
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2012, 5(3), 739-747; https://0-doi-org.brum.beds.ac.uk/10.3390/wevj5030739
Published: 28 September 2012

Abstract

In this paper we present a novel composite methodology for obtaining spatial projections of the impacts and opportunities arising from the integration of plug-in electric vehicles with future smart electricity grids. We link models of future plug-in electric vehicle uptake, travel by household members, household electricity demand, and recharge of electric vehicles. The analysis is disaggregated in each case to a mesh block or local government area level; vehicle usage and household energy demand fluctuate on a hourly, daily and seasonal basis, subject also to the longer-term trends projected for uptake of the new technology. A similarly fine grain is applied with respect to socio-economic variables. The uptake model combines features of choice modelling, multi-criteria analysis and technology diffusion theory; in this case it was applied to four competing technologies (BEV, PHEV, HEV, ICE), and calibration revealed seven major determinants of uptake: performance, annual costs, purchase cost, household income, driving distance, demographic suitability, and risk or inconvenience. The travel model projects likely patterns of vehicle usage and travel duration based on existing patterns of private vehicle usage. The household demand model includes detailed representation of housing type and usage of electrical appliances. The charge-discharge model embodies plausible algorithms for managing household electricity usage in conjunction with electric vehicle batteries. In the paper we describe the various models and report projected impacts of electric vehicles on peak electrical grid loads for the Australian state of Victoria. The impacts are presented on a spatial basis, to the level of individual mesh blocks and network feeders, under a range of energy management scenarios.
Keywords: electric vehicle; electric grid; diffusion modelling; travel modelling; household energy electric vehicle; electric grid; diffusion modelling; travel modelling; household energy

Share and Cite

MDPI and ACS Style

Paevere, P.; Higgins, A.; Grozev, G.; Ren, Z.; Horn, M. Electric Vehicles and the Smart Grid: Spatial Modelling of Impacts and Opportunities. World Electr. Veh. J. 2012, 5, 739-747. https://0-doi-org.brum.beds.ac.uk/10.3390/wevj5030739

AMA Style

Paevere P, Higgins A, Grozev G, Ren Z, Horn M. Electric Vehicles and the Smart Grid: Spatial Modelling of Impacts and Opportunities. World Electric Vehicle Journal. 2012; 5(3):739-747. https://0-doi-org.brum.beds.ac.uk/10.3390/wevj5030739

Chicago/Turabian Style

Paevere, Phillip, Andrew Higgins, George Grozev, Zhengen Ren, and Mark Horn. 2012. "Electric Vehicles and the Smart Grid: Spatial Modelling of Impacts and Opportunities" World Electric Vehicle Journal 5, no. 3: 739-747. https://0-doi-org.brum.beds.ac.uk/10.3390/wevj5030739

Article Metrics

Back to TopTop