Abstract
Intermittent distributed generators (IDGs), such as distributed wind turbine generator (WTG) and photovoltaic generator (PVG), have been developing rapidly in recent years. The output power of WTG and PVG highly depends on the wind speed and illumination intensity, respectively. There always exist correlations among the wind speed, illumination intensity, and bus load, which could have significant influence on the determination of siting and sizing of IDGs in distribution system. Given this background, a chance‐constrained‐programming‐based IDGs planning model, which can take into account the correlations, is developed in this paper. Latin hypercube sampling technique and Cholesky decomposition are introduced to handle the correlations. A Monte Carlo simulation‐embedded multi‐population differential evolution algorithm is employed to solve the developed model. Case studies carried out on the Baran & Wu 33‐bus distribution system verify the feasibility of the developed model and effectiveness of the proposed solving methodology. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEJ Transactions on Electrical and Electronic Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
