Publisher: John Wiley & Sons Inc
E-ISSN: 1931-4981|10|6|628-635
ISSN: 1931-4973
Source: IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Vol.10, Iss.6, 2015-11, pp. : 628-635
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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.