1 Department of Electrical Engineering, Shiraz University 2 Department of Electrical Engineering, University of Eyvanekey Corresponding Author: Mohsen Khorasany Abstract—Nowadays limitation of energy sources has increased the demands for using Distributed Generation (DG) in electricity generation. One of the most important issues about DG is allocation size and place of DG in the network to ach...

This work presents an investigation into the use of swarm intelligence techniques for control doubly fed induction generator under unbalanced grid voltages. Swarm is a concept that was introduced in late 20th century but has since undergone constant evolution and modifications. Similarly, recently come intense investigation. Owing to direct connection DFIG, voltage harshly impacts its output po...

We propose a new approach called PESA (Prioritized replay Evolutionary and Swarm Algorithms) combining prioritized of reinforcement learning with hybrid evolutionary algorithms. hybridizes different swarm algorithms such as particle optimization, evolution strategies, simulated annealing, differential evolution, modular to account for other three by storing their solutions in shared memory, the...

Due to an anticipated increase in air traffic during the next decade, air traffic control in busy airports is one of the main challenges confronting the controllers in the near future. Since the runway is often a bottleneck in an airport system, there is a great interest in optimizing the use of the runway. The most important factors in aircraft landing modeling are time and cost. For this reas...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

The purpose of this study is to optimize the stock price forecasting model with meta-innovation method in pharmaceutical companies.In this research, stock portfolio optimization has been done in two separate phases.The first phase is related to forecasting stock futures based on past stock information, which is forecasting the stock price using artificial neural network.The neural network used ...

A particle swarm optimization based simultaneous learning framework for clustering and classification (PSOSLCC) is proposed in this paper. Firstly, an improved particle swarm optimization (PSO) is used to partition the training samples, the number of clusters must be given in advance, an automatic clustering algorithm rather than the trial and error is adopted to find the proper number of clust...

In this paper, the theory and modeling of large scale photovoltaic (PV) in the power grid and its effect on power system stability are studied. In this work, the basic module, small signal modeling and mathematical analysis of the large scale PV jointed multi-machine are demonstrated. The principal portion of the paper is to reduce the low frequency fluctuations by tuned stabilizer in the atten...

To more effectively solve the complex optimization problems that exist in nonlinear, high-dimensional, large-sample and systems, many intelligent methods have been proposed. Among these algorithms, particle swarm (PSO) algorithm has attracted scholars’ attention. However, traditional PSO can easily become an individual optimal solution, leading to transition of process from global exploration l...