Optimal distribution feeder routing and optimal substation sizing and placement using evolutionary strategies

Conference Paper · October 1994with36 Reads
DOI: 10.1109/CCECE.1994.405838 · Source: IEEE Xplore
Conference: Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
Abstract
This paper investigates the application of evolutionary strategies to the problem of optimal substation sizing and placement, and the optimal routing of power distribution feeders. The principles of evolutionary strategies are discussed and a model proposed. The success of the method is demonstrated through computer simulations
    • "@BULLET Classifying the methods based on the modeling of the distribution system @BULLET Classifying the methods based on planning interval @BULLET Classifying upon the optimization methods @BULLET Classifying based on assumed constraints Due to complex structure of distribution system, it is impossible to optimize the structure of the grid in a global manner. Thus, the system planning is divided into two subsets [1] : The first subset involves determination of location and sizing of substations (subtransmission and distribution) [2,3] . The second subset considers optimal routing of distribution feeders [4,5] . "
    Article · Mar 2009
    • "@BULLET Classifying the methods based on the modeling of the distribution system @BULLET Classifying the methods based on planning interval @BULLET Classifying upon the optimization methods @BULLET Classifying based on assumed constraints Due to complex structure of distribution system, it is impossible to optimize the structure of the grid in a global manner. Thus, the system planning is divided into two subsets [1] : The first subset involves determination of location and sizing of substations (subtransmission and distribution) [2,3] . The second subset considers optimal routing of distribution feeders [4,5] . "
    [Show abstract] [Hide abstract] ABSTRACT: This research presents an accurate comprehensive cost function for the problem of optimal location of subtransmission substations. Technical constraints and economical parameters are investigated in the modeling. Genetic algorithm is used to optimize the cost function. Coding of decision variables is done in a way that finding the correct solutions is achieved faster. For the first time in this study, free capacity of medium voltage distribution feeders is used for optimal location of subtransmission substations. Also cost of coupling to upward grid in candidate substations with considering different levels of subtransmission voltage is presented. Efficiency of the proposed algorithm is evaluated via several case studies.
    Full-text · Article · Mar 2009
    • "The ES can solve large-scale networks without simplifying the cost function and without fixing or restricting mv/lv substation locations, as in mathematic programming methods [7], widely used for planning medium-voltage (mv) distribution networks. In recent years, methods have been developed for network planning based on metaheuristic models: simulating annealing [11], [12], genetic algorithms [13], [14], evolution strategies [10], [15]–[19] and evolutionary programming [20]. In general, these works present applications for mv distributions networks, but they do not consider the simultaneous optimization of hv/mv substation locations and mv networks. "
    [Show abstract] [Hide abstract] ABSTRACT: This paper presents a method based on evolution strategies for designing large rural low-voltage (LV) distribution networks. Planning rural LV distribution networks involves radial configuration design, location of medium-voltage/low-voltage substations, and minimum cost. In this work, these goals are considered by taking into account different conductors, voltage drop and conductor capacity constraints, power losses in lines, and deterministic loads. The algorithms developed in this paper are based on evolution strategies (ES) and were implemented on large-scale rural LV distribution networks, but they could also be used in general network optimization.
    Full-text · Article · Dec 2003
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