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Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand

Cumulant-based correlated probabilistic load flow considering photovoltaic generation and... Abstract This paper applies a cumulant-based analytical method for probabilistic load flow (PLF) assessment in transmission and distribution systems. The uncertainties pertaining to photovoltaic generations and aggregate bus load powers are probabilistically modeled in the case of transmission systems. In the case of distribution systems, the 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. The probability distributions of the result variables (bus voltages and branch power flows) pertaining to these inputs are accurately established. The multiple input correlation cases are incorporated. Simultaneously, the performance of the proposed method is demonstrated on a modified Ward-Hale 6-bus system and an IEEE 14-bus transmission system as well as on a modified IEEE 69-bus radial and an IEEE 33-bus mesh distribution system. The results of the proposed method are compared with that of Monte-Carlo simulation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Frontiers in Energy" Springer Journals

Cumulant-based correlated probabilistic load flow considering photovoltaic generation and electric vehicle charging demand

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Publisher
Springer Journals
Copyright
2017 Higher Education Press and Springer-Verlag Berlin Heidelberg
ISSN
2095-1701
eISSN
2095-1698
DOI
10.1007/s11708-017-0465-7
Publisher site
See Article on Publisher Site

Abstract

Abstract This paper applies a cumulant-based analytical method for probabilistic load flow (PLF) assessment in transmission and distribution systems. The uncertainties pertaining to photovoltaic generations and aggregate bus load powers are probabilistically modeled in the case of transmission systems. In the case of distribution systems, the 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. The probability distributions of the result variables (bus voltages and branch power flows) pertaining to these inputs are accurately established. The multiple input correlation cases are incorporated. Simultaneously, the performance of the proposed method is demonstrated on a modified Ward-Hale 6-bus system and an IEEE 14-bus transmission system as well as on a modified IEEE 69-bus radial and an IEEE 33-bus mesh distribution system. The results of the proposed method are compared with that of Monte-Carlo simulation.

Journal

"Frontiers in Energy"Springer Journals

Published: Jun 1, 2017

References