OPTIMAL POWER MANAGEMENT OF DGS AND DSTATCOM USING IMPROVED ALI BABA AND THE FORTY THIEVES OPTIMIZER

In this study an improved Ali Baba and the forty thieves Optimizer (IAFT) is proposed and successfully adapted and applied to enhance the technical performances of radial distribution network (RDN). The standard AFT governed by two sensible parameters to balance the exploration and the exploitation stages. In the proposed variant a modification is introduced using sine and cosine functions to create flexible balance between Intensification and diversification during search process. The proposed variant namely IAFT applied to solve various single and combined objective functions such as the improvement of total power losses (TPL), the minimization of total voltage deviation and the maximization of the loading capacity (LC) under fixed load and considering the random aspect of loads. The exchange of active powers is elaborated by integration of multi distribution generation based photovoltaic systems (PV), otherwise the optimal management of reactive power is achieved by the installation of multi DSTATCOM. The efficiency and robustness of the proposed variant validated on two RDN, the 33-Bus and the 69-Bus. The qualities of objective functions achieved and the statistical analysis elaborated compared to results achieved using several recent metaheuristic methods demonstrate the competitive aspect of the proposed IAFT in solving with accuracy various practical problems related to optimal power management of RDN

Optimal coordination of directional overcurrent relays using PSO-TVAC considering series compensation

The integration of system compensation such as Series Compensator (SC) into the transmission line makes the coordination of directional overcurrent in a practical power system important and complex. This article presents an efficient variant of Particle Swarm Optimization (PSO) algorithm based on Time-Varying Acceleration Coefficients (PSO-TVAC) for optimal coordination of directional overcurrent relays (DOCRs) considering the integration of series compensation. Simulation results are compared to other methods to confirm the efficiency of the proposed variant PSO in solving the optimal coordination of directional overcurrent relay in the presence of series compensation

Dynamic strategy based fast decomposed GA coordinated with FACTS devices to enhance the optimal power flow

International audienceUnder critical situation the main preoccupation of expert engineers is to assure power system security and to deliver power to the consumer within the desired index power quality. The total generation cost taken as a secondary strategy. This paper presents an efficient decomposed GA to enhance the solution of the optimal power flow (OPF) with non-smooth cost function and under severe loading conditions. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two sub problems are proposed to coordinate the OPF problem under different loading conditions: the first sub problem related to the active power planning under different loading factor to minimize the total fuel cost, and the second sub problem is a reactive power planning designed based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the proposed algorithm tested on IEEE 30-Bus, 26- Bus and IEEE 118-Bus under different loading conditions and compared with global optimization methods (GA, EGA, FGA, PSO, MTS, MDE and ACO) and with two robust simulation packages: PSAT and MATPOWER. The results show that the proposed approach can converge to the near solution and obtain a competitive solution at critical situation and with a reasonable time

Fuzzy Controlled Parallel PSO to Solving Large Practical Economic Dispatch

International audienceThis paper proposes a version of fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solve large nonconvex economic dispatch problems. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules to adjust dynamically the three parameters associated to PSO mechanism search. The adaptive PSO executed in parallel based in decomposed network procedure as a local search to explore the search space very effectively. The robustness of the proposed modified PSO tested on 40 generating units with prohibited zones and compared with recent hybrid global optimization methods. The results show that the proposed approach can converge to the near solution and obtain a competitive solution with a reasonable time compared with recent previous approaches

Optimum performances for non-linear finite elements model of 8/6 switched reluctance motor based on intelligent routing algorithms

This paper presents torque ripple reduction with speed control of 8/6 Switched Reluctance Motor (SRM) by the determination of the optimal parameters of the turn on, turn off angles Theta_(on), Theta_(off), and the supply voltage using Particle Swarm Optimization (PSO) algorithm and steady state Genetic Algorithm (ssGA). With SRM model, there is difficulty in the control relapsed into highly non-linear static characteristics. For this, the Finite Elements Method (FEM) has been used because it is a powerful tool to get a model closer to reality. The mechanism used in this kind of machine control consists of a speed controller in order to determine current reference which must be produced to get the desired speed, hence, hysteresis controller is used to compare current reference with current measured up to achieve switching signals needed in the inverter. Depending on this control, the intelligent routing algorithms get the fitness equation from torque ripple and speed response so as to give the optimal parameters for better results. Obtained results from the proposed strategy based on metaheuristic methods are compared with the basic case without considering the adjustment of specific parameters. Optimized results found clearly confirmed the ability and the efficiency of the proposed strategy based on metaheuristic methods in improving the performances of the SRM control considering different torque loads