a saiwd-based approach for simultaneous reconfiguration and optimal siting and sizing of wind turbines and dvr units in distribution systems

In this paper, a combination of simulated annealing (sa) and intelligent water drops (iwd) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (wt) as a distributed generation (dg) and dynamic voltage restorer (dvr) as a distributed flexible ac transmission systems (dfact) unit in a distribution system. the objectives of this research are to minimize active power loss, minimize operational cost, improve voltage stability, and increase the load balancing of the system. for evaluation purposes, the proposed algorithm is evaluated using the taipower 11.4kv real distribution network. the impacts of the optimal placement of the wt, dvr, and wt with dvr units are separately evaluated. the results are compared in terms of statistical indicators. by comparing all the testing scenarios, it is observed that the multiobjective optimization evolutionary algorithm is more beneficial than its singleobjective optimization counterpart. also, the obtained results show that the proposed saiwd method outperforms the iwd method and other intelligent search algorithms such as genetic algorithm or particle swarm optimization.