The development of renewable energy sources, distributed generation, energy storage and nonlinear controllable loads in modern distribution networks has led to the consideration of the state estimation in intelligent and active distribution networks. The performance of the Energy Management Central's distribution network depends on the results of the state estimation. In this paper, two-stage estimation with the network reduction process is proposed. The number of distribution network meter is low, so obtaining accurate initial information from network conditions improves performance state estimation. The initial state estimation with the network reduction process to obtain accurate initial data is performed. The initial data are used as a measure to improve the performance of secondary estimation. This method solves the problem of scarcity of accurate measurements and improves the accuracy of the state estimation in distribution network. The results of the proposed methodology are demonstrated on the 69 nodes of IEEE  standard distribution network.

Wind powers are very unstable in voltage fluctuations, especially in short circuit error and sharp and sudden voltage drops, which one of its main reasons is the use of induction generators in these power plants and thus need to reactive power and high magnetizing current. To improve the ride_through voltage from WECS in error conditions and damping the oscillations of the induction generator rotor, a UPFC is used the controller FOPID is used in UPFC controllers for the first time. Since FOPID has two parameters more than IOPID, it has recently attracted much attention (needing more work and research motivation) as it gives more flexibility to a control system designing and a better opportunity to adjust the system dynamics, especially, if a system is to be controlled be a fractional system. The investigations indicate that controller FOPID adjusted by presented PSO algorithm, show improved dynamic performance than traditional PID and feedback controller in a wide range of operating conditions.