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.

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Optimal placement of FACTS devices attempts to improve power transfer, minimize active power loss, enhance voltage profile and improve voltage stability, thereby making the operation of power systems more flexible and secured. The classical methods experience difficulties in solving the FACTS placement problem (FPP) with discontinuous functions and may diverge or result oscillatory convergence. Besides the number of FACTS devices for placement should be given as an input while solving the problem. The solution methods then attempts to forcefully place all the specified number of devices in the power system, but in reality, the system may require an optimal number of FACTS for placement. The application of swarm-intelligence based optimization algorithms strives to overcome the drawbacks of classical methods. This paper presents a new solution method for FACTS placement problem using improved harmony search optimization (IHSO) with a newly suggested dissonance mechanism that avoids badly composed music, with a view of avoiding the sub-optimal solutions. Besides, the method requires to specify only the maximum number of FACTS devices for placement and places only the optimal number of devices within the specified maximum number of devices. The paper also includes simulation results of three IEEE test systems for exhibiting the superiority of the proposed method.

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.

Placement of thyristor-controlled series compensator (TCSC) devices at appropriate lines reduces the net transmission loss (NTL) through injecting suitable series voltage in the transmission lines. The classical approaches for placing TCSCs in the power network may not provide optimal solution and face intricacies in solving the problem with multifarious constraints and vehemently place all the allotted TCSCs in the network. This paper presents a method employing improved harmony search optimization (MHSO), an evolutionary algorithm, for solving TCSC problem (TCSCP) and places the vital number of SVCs from the allotted ones. This paper presents the solution of TCSCP problem of 14, 30 and 57 bus systems and compares the performances in various aspects with existing TCSCP 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.

Purpose Optimal placement of static VAR compensator (SVC) devices not only improves the voltage profile (VP) but also reduces the active power loss (APL) and enhances the voltage stability (VS) through injecting appropriate VARs at optimal buses. The traditional mathematical methods may not provide global best solution and pose difficulties in handling multi-objective SVC placement (SVCP) problem with complex constraints and forcefully place all the given number of SVCs in the system without assessing their real requirements in enhancing the chosen performances. The purpose of this paper is to formulate the SVCP as a multi-objective optimization problem and solve it using a metaheuristic algorithm for global best solution. Design/methodology/approach The proposed SVCP method uses improved harmony search optimization (IHSO) with dissonance-avoiding mechanism for obtaining the global best solution through driving away the solution from the sub-optimal traps. In addition, the method uses a self-adaptive technique for optimally tuning the IHSO parameters and places only the required number of SVCs from the given number of SVCs. Findings This paper presents the results of the proposed method for 14, 30 and 57 bus systems and exhibits that the proposed method outperforms the existing SVCP methods in achieving the desired performances. Originality/value This paper proposes a new self-adaptive IHSO based SVCP method for optimally placing only the required number of SVCs with a goal of attaining the global best performances.

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