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    Probabilistic Optimisation of Generation Scheduling Considering Wind Power Output and Stochastic Line Capacity

    218683_218683.pdf (380.4Kb)
    Access Status
    Open access
    Authors
    Banerjee, Binayak
    Jayaweera, Dilan
    Islam, Syed
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Banerjee, B. and Jayaweera, D. and Islam, S. 2012. Probabilistic Optimisation of Generation Scheduling Considering Wind Power Output and Stochastic Line Capacity, in Mochamad Ashari (General Chair) (ed), 22nd Australasian Universities Power Engineering Conference, Sep 26 2012. Bali, Indonesia: Institut Teknologi Sepuluh Nopember.
    Source Title
    Proceedings of the 22nd Australasian Universities Power Engineering Conference
    Source Conference
    22nd Australasian Universities Power Engineering Conference
    Additional URLs
    http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6360252
    ISBN
    9789791884723
    School
    Department of Electrical and Computer Engineering
    Remarks

    Copyright © 2012 IEEE. Personal use of this material is permitted. Permission from IEEEmust be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/23072
    Collection
    • Curtin Research Publications
    Abstract

    Optimising the power flow in a system has been a challenge for decades. Due to the complexities that are introduced by new technologies, this problem is evolving. Lately, the effect of integrating wind turbines into the system has been taken into account when solving optimal power flow. However, transmission system constraints are usually modeled as fixed constraints using deterministic methods. Deterministic transmission line ratings have been shown to significantly underestimate the capability of the network. However, probabilistic line ratings are not used in optimization studies. In this paper, stochastic optimisation is used to consider the integration of wind turbines as well as probabilistic real time line capacities. It is shown that optimization considering probabilistic line ratings that lead to dynamic constraints in the OPF problem, represents the operational situation more accurately. This approach further reduces the optimum cost of system operation.

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