Modeling of power demands of electric vehicles in correlated probabilistic load flow studies
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Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
In this paper, extended cumulant method (ECM) is applied to probabilistic load flow analysis. Input uncertainties pertaining to plug-in hybrid electric vehicle and battery electric vehicle charging demands in residential community as well as charging stations are probabilistically modeled. Probability distributions of the result variables such as bus voltages and branch power flows pertaining to these inputs are accurately approximated; and at the same time, multiple input correlation cases are incorporated. The performance of ECM is demonstrated on the modified IEEE 69-bus radial distribution system. The results of ECM are compared with Monte-Carlo simulation. © 2016 IEEE.
Description
Keywords
Battery electric vehicle, Extended cumulant method, Plug-in hybrid electric vehicle, Probabilistic load flow, Radial distribution system
Citation
IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, 2017, Vol.2016-January, , p. 1-6