This paper proposes a generalized soccer league optimization (SLO) based load flow (LF) method suitable for both transmission and distribution systems. The LF problem is formulated as an optimization problem of lowering the sum of squares of active and reactive power mismatches at all busses, while taking the net corrections of bus voltage angles and magnitudes as unknown decision variables. The formulated problem is then solved using SLO, a population-based algorithm imitated from the behavior of team players of soccer league competition. The performances in respect of accuracy, robustness to different line r/x ratios, and computational efficiency are studied on six standard IEEE transmission and distribution systems and the results are presented.

This paper presents an efficient power flow (PF) for distribution networks (DN). The proposed PF method uses basic circuit laws in deriving the final PF expression and appears like the classical Gauss-Seidel PF algorithm of transmission systems. It possesses the advantages of forward and backward sweeps (FBS) based PF methods but avoids the FBS and formation of a Jacobian matrix. It primarily depends on a constant transformation matrix, formed only once from the network topology and feeder parameters. The transformation matrix relates the node currents with effective feeder voltage drops, and helps to compute the node voltages directly from the given set of load powers. The proposed PF was studied on 15, 33 and 69 node DNs, and the study exhibited that the performances in terms of accuracy, robustness to different r/x ratios of distribution lines and computational efficiency of the proposed method are superior to those of existing methods.

Purpose The purpose of the paper is to develop a simple, efficient and robust power flow (PF) method for ill-conditioned distribution networks (DNs). Design/methodology/approach It first formulates the PF problem as an optimization problem of minimizing the node power mismatches, while treating the corrections of node voltages as problem variables and then uses soccer game optimization (SGO), an artificial intelligent algorithm simulating the behavior of soccer game players in scoring goals, in solving the formulated PF problem. Findings It studies the performances of the developed method on four standard test DNs and exhibits that the method is superior in respect of accuracy, robustness and computational speed than those of existing methods. Originality/value It suggests a novel and new PF method using SGO and portrays that the proposed method is as accurate as any other PF method, robust like non-Newton type of PF methods and faster than Newton type of PF methods.

Distribution power flow (DPF) and distribution generation (DG) placement are important problems in modern distribution systems (DSs). The DPF problem is modelled as an optimization problem of minimizing the node power mismatches, while considering the corrections of node voltages as solution variables. The node locations and DG ratings of DG placement (DGP) problem are considered as optimization parameters with an objective of minimizing the network loss (NL). The soccer game optimization (SGO) models the movements of soccer game players by "move-off" and "move-forward" phases, and has the drawback of performing simple arithmetic average for representing random stochastic movements of players during its "move-forward" phase. This paper endeavours to first remodel the move-forward phase by adapting Levy Flight mechanism to simulate the random jumping action of players to a long distance in getting the ball and scoring a goal, and then develop new modified SGO (MSGO) based methods for solving the formulated DPF and DGP problems. The simulation study exhibited that the proposed DPF method is 751 and 666 times faster than the NR PF technique and the DGP method is able to save the NL by 65% and 69% for 33 and 69 node systems respectively.

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