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    Online velocity optimization of robotic swarm flocking using particle swarm optimization (PSO) method

    , Article 2009 6th International Symposium on Mechatronics and its Applications ; 2009, Article number 5164776 , 2009 , p. 5164776- ; ISBN: 978-142443481-7 Vatankhah, R ; Etemadi, S ; Honarvar, M ; Alasty, A ; Boroushaki, M ; Vossoughi, G ; Sharif University of Technology
    Abstract
    In this paper, the agent velocity in robotic swarm was determined by using particle swarm optimization (PSO) to maximize the robotic swarm coordination velocity. A swarm as supposed here is homogenous and includes at least two members. Motion and behavior of swarm members are mostly result of two different phenomena: interactive mutual forces and influence of the agent. Interactive mutual forces comprise both attraction and repulsion. To be more realistic the field of the swarm members' view is not infinity. So influence of the coordinator agent on the robotic swarm would be local. The objective here is to guide the robotic swarm with maximum possible velocity. According to equation motion... 

    Robust transmission expansion planning considering private investments maximization

    , Article 2016 IEEE International Conference on Power System Technology, POWERCON 2016, 28 September 2016 through 1 October 2016 ; 2016 ; 9781467388481 (ISBN) Ranjbar, H ; Hosseini, S. H ; Kasebahadi, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2016
    Abstract
    Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties, high investment costs, and long period investment return cause the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new approach for transmission expansion planning (TEP) in order to maximize private investment absorption. The robust optimization method is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load. The genetic algorithm (GA) is, also, utilized as the methodology to solve the... 

    Online velocity optimization of robotic swarm flocking using particle swarm optimization (PSO) method

    , Article 2009 6th International Symposium on Mechatronics and its Applications, ISMA 2009, Sharjah, 23 March 2009 through 26 March 2009 ; 2009 ; 9781424434817 (ISBN) Vatankhah, R ; Etemadi, S ; Honarvar, M ; Alasty, A ; Boroushaki, M ; Vossoughi, G. R ; Sharif University of Technology
    2009
    Abstract
    In this paper, the agent velocity in robotic swarm was determined by using particle swarm optimization (PSO) to maximize the robotic swarm coordination velocity. A swarm as supposed here is homogenous and includes at least two members. Motion and behavior of swarm members are mostly result of two different phenomena: interactive mutual forces and influence of the agent. Interactive mutual forces comprise both attraction and repulsion. To be more realistic the field of the swarm members' view is not infinity. So influence of the coordinator agent on the robotic swarm would be local. The objective here is to guide the robotic swarm with maximum possible velocity. According to equation motion... 

    A robust optimization method for co-planning of transmission systems and merchant distributed energy resources

    , Article International Journal of Electrical Power and Energy Systems ; Volume 118 , 2020 Ranjbar, H ; Hosseini, S. H ; Zareipour, H ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    This paper presents a new robust co-planning model for transmission investment and merchant distributed energy resources (DERs). The problem is formulated from the viewpoint of power system regulators and planners such that they will build the new transmission facilities and identify optimal locations to direct merchant DERs. The proposed model is a tri-level min-max-min optimization problem where the upper, middle, and lower levels are investment decision of transmission lines and DERs, worst case realization of uncertain parameters, and the best actions in order to minimize the operation costs. The model considers the uncertainties associated with future peak load and generation capacity,...