Renewable energies have a significant portion in supplying energy demands in modern distribution networks. Due to the wide use of power electronic devices, these networks may have power quality problems. The unpredictable nature of renewable energies, besides the effect of non‐linear loads brings out serious planning and operating challenges for distribution systems. Basicly, harmonic distortion is a severe problem for both electric efficiency and power energy customers. This study proposes an optimal scheduling strategy for wind turbine's integrated distribution networks with non‐linear loads using a multi‐objective individualized instruction mechanism teaching‐learning‐based optimization algorithm and the best solution is selected via the TOPSIS technique. In the proposed strategy, energy storage systems are optimally scheduled besides wind turbines, and reactive power compensators. Also, to use the distribution network more efficiently, an optimal network reconfiguration is applied. The wind turbine's output and load demands have probabilistic nature. The proposed scheme reduces the total harmonic distortion as well as total costs. The efficacy of the proposed management scheme is investigated using the IEEE standard 33 bus distribution network. Also, the performance of the multi‐objective individualized instruction mechanism teaching‐learning‐based optimization algorithm is compared with the multi‐objective particle swarm optimization algorithm.

The interconnections of power systems are extended to improve operating conditions and increase their adequacy and security. Furthermore, with the increasing penetration of renewable energy sources such as wind turbines (WTs), probabilistic assessment of these systems' performance is very important, especially in risk management, bidding strategies, and operational decisions. Interline power flow controller (IPFC) is one of the flexible AC transmission system (FACTS) devices, which can increase power transfer capability and maximize the use of the existing transmission network. In the structure of the IPFC, there are two converters whose settings should be determined optimally to get the maximum benefit from it. This paper introduces a probabilistic multi-objective optimization method for the allocation of the IPFC to reduce the active power losses and improve the power flow index (PFI) of the lines with considering the IPFC cost using the multiobjective particle swarm optimization (MOPSO) algorithm. The uncertainties are taken to account in loads and wind speed of WTs. Also, the k-means-based data clustering method (DCM) is used for the probabilistic assessment of this problem for the first time, and its performance is compared with the Monte Carlo simulation (MCS) method. The efficiency of the proposed approach is investigated on the IEEE 30-bus test system.

Summary In recent years, harmonic distortion has sharply increased because of injecting harmonic components caused by using nonlinear loads in the distribution system. Uncontrolled harmonic distortion can bring damage to equipment of the power system, reduce the power system efficiency, and interrupt protection and measurement devices. This parameter can be managed using various resources and control programs in active distribution networks. This paper presents active distribution networks (ADNs) with multiple objective particle swarm optimization (MOPSO) algorithm using the technique for order of preference by similarity to ideal solution (TOPSIS) framework in the presence of nonlinear loads. The presented planning model manages the sample network to minimize the total harmonic distortion (THD) of the system while minimizing the operational and investment costs. Four active management schemes, network reconfiguration, distributed generation (DG) dispatch, demand‐side management (DSM), and reactive power compensation are considered for this purpose. Optimal sizing and siting of the energy storage system (ESS) is used to reduce peak load and operational costs. The IEEE 33 node distribution network is used to verify the proposed planning model.

Background and Aim: Considering the great advances and extensive use of cell phones and its effects on the human communications and interactions, investigation of potential negative effects of cell phones on the users' health is necessary. The aim of this study was to determine the effect of the distance between cell phones and brain tissue on the temperature of the central and gray matters of the brain, because of the heat generated by radiofrequency waves. Methods: This was an experimental study. Cow brain tissue was analyzed in a compartment with three depths of 2 mm, 12 mm and 22 mm, and at the distances of 4 mm and 4 cm from a cell phone, for 15 minutes. Lutron thermometer was used to measure the tissue temperature. Data analysis performed by using Lutron and MATLAB software packages. Results: Temperature increase was more at the distance of 4 mm and in the depths of 2, 12, and 22 mm compared to that at the distance of 4 cm. Also temperature increase after removal of the confrontation was more than the baseline temperature at both distances which was higher at the distance of 4 mm. Conclusion: Decreased distance between brain tissue and cell phone can increase the tissue temperature. Increasing the cell phone distance from the brain tissue can result in slower trend in temperature increase and decreased collective temperature after discontinuing the confrontation. ‫کردستان‬ ‫پزشکی‬ ‫علوم‬ ‫دانشگاه‬ ‫علمی‬ ‫مجله‬ / ‫سوم‬ ‫و‬ ‫بیست‬ ‫دوره‬ / ‫تیر‬ ‫و‬ ‫خرداد‬ 7931 / 54 -91 93 ‫فرکانسی‬ ‫رادیو‬ ‫امواج‬ ‫اثر‬ ‫بررسی‬ ‫کردستان‬ ‫پزشکی‬ ‫علوم‬ ‫دانشگاه‬ ‫علمی‬ ‫مجله‬ / ‫سوم‬ ‫و‬ ‫بیست‬ ‫دوره‬ / ‫و‬ ‫خرداد‬ ‫تیر‬ 7931 ‫فروهر‬ ‫فرهاد‬ ‫مجد‬ 54 ‫پزشکی‬ ‫علوم‬ ‫دانشگاه‬ ‫علمی‬ ‫مجله‬ ‫کردستان‬ / ‫سوم‬ ‫و‬ ‫بیست‬ ‫دوره‬ / ‫تیر‬ ‫و‬ ‫خرداد‬ 7931

The aim of this research is to codify scenario-based strategies in the Land and Housing Organization that has been done with drawing pictures of the future. In the present study, we used Schwartz and simultaneous methods in order to determine the strategies. The present study has been done in the year 2015 within the time horizon of 10 years. The statistical population included all senior municipal managers and experts in the Land and Housing Organization of Mashhad city (27 persons) which 15 persons selected purposefully.In the present study, the required information has been collected through library studies and semi-structured interview, trends, and uncertainty factors have been identified. Then, the impact/uncertainty matrix was drawn. Specifying dimensions by using simultaneous (combined) method, four scenarios of high impact-high uncertainty, low impact-high uncertainty, high impact-low uncertainty, low impact-low uncertainty were codified and four strategies of (