Modeling of power demands of electric vehicles in correlated probabilistic load flow studies
| dc.contributor.author | Bhat, N.G. | |
| dc.contributor.author | Rajanarayan, Prusty, B. | |
| dc.contributor.author | Jena, D. | |
| dc.date.accessioned | 2020-03-30T10:23:12Z | |
| dc.date.available | 2020-03-30T10:23:12Z | |
| dc.date.issued | 2017 | |
| dc.description.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. | en_US |
| dc.identifier.citation | IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2016, 2017, Vol.2016-January, , pp.1-6 | en_US |
| dc.identifier.uri | https://idr.nitk.ac.in/handle/123456789/8986 | |
| dc.title | Modeling of power demands of electric vehicles in correlated probabilistic load flow studies | en_US |
| dc.type | Book chapter | en_US |