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    Value of distribution network reconfiguration in presence of renewable energy resources

    , Article IEEE Transactions on Power Systems ; Volume 31, Issue 3 , 2016 , Pages 1879-1888 ; 08858950 (ISSN) Dorostkar Ghamsari, M. R ; Fotuhi Firuzabad, M ; Lehtonen, M ; Safdarian, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc 
    Abstract
    Proliferation of renewable energy resources in distribution networks has captured distribution companies' attention towards more active management tools. Thanks to the smart grid paradigm, hourly network reconfiguration, which is still among immature ideas, can bring the activeness required to handle fluctuating output of renewable resources. The aim of this study is to analyze the worthiness of the hourly reconfiguration in the presence of renewable energy resources. For doing so, a mathematical model is devised to minimize daily network losses via applying hourly reconfigurations. The model is a mixed integer second-order cone programming problem and is solved via MOSEK solver. The... 

    Stochastic energy management of microgrids during unscheduled islanding period

    , Article IEEE Transactions on Industrial Informatics ; Volume 13, Issue 3 , Volume 13, Issue 3 , 2017 , Pages 1079-1087 ; 15513203 (ISSN) Farzin, H ; Fotuhi Firuzabad, M ; Moeini Aghtaie, M ; Sharif University of Technology
    IEEE Computer Society  2017
    Abstract
    This paper deals with energy management of microgrids during unscheduled islanding events, initiated by disturbances in the main grid. In these situations, the main challenge is uncertainty about duration of disconnection from the main grid. In order to tackle this issue, a stochastic framework is proposed for optimal scheduling of microgrid resources over this period. The presented framework addresses the prevailing uncertainties of islanding duration as well as prediction errors of demand and renewable power generation. According to this framework, the probability distribution of islanding duration needs to be estimated, instead of predicting its exact value. The objective is to minimize... 

    Distributionally robust chance-constrained generation expansion planning

    , Article IEEE Transactions on Power Systems ; Volume 35, Issue 4 , 2020 , Pages 2888-2903 Pourahmadi, F ; Kazempour, J ; Ordoudis, C ; Pinson, P ; Hosseini, S. H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    This article addresses a centralized generation expansion planning problem, accounting for both long- and short-term uncertainties. The long-term uncertainty (demand growth) is modeled via a set of scenarios, while the short-term uncertainty (wind power generation) is described by a family of probability distributions with the same first- and second-order moments obtained from historical data. The resulting model is a distributionally robust chance-constrained optimization problem, which selects the conventional generating units to be built among predefined discrete options. This model includes a detailed representation of unit commitment constraints. To achieve computational tractability,...