Optimal PMU location in power systems using MICA

AbstractThis study presented a modified imperialist competitive algorithm (MICA) for optimal placement of phasor measurement units (PMUs) in normal and contingency conditions of power systems. The optimal PMU placement problem is used for full network observability with the minimum number of PMUs. For this purpose, PMUs are installed in strategic buses. Efficiency of the proposed method is shown by the simulation results of IEEE 14, 30, 57, and 118-bus test systems. Results of the numerical simulation on IEEE-test systems indicated that the proposed technique provided maximum redundancy measurement and minimum request of PMUs so that the whole system could be topologically observable by installing PMUs on the minimum system buses. To verify the proposed method, the results are compared with those of some recently reported methods. When MICA is used for solving optimal PMU placement (OPP), the number of PMUs would be usually equal to or less than those of the other existing methods. Results indicated that MICA is a very fast and accurate algorithm for OPP solution

Fractional order PID controller design for LFC in electric power systems using imperialist competitive algorithm

AbstractIn this paper, fractional order PID (FOPID) controller was proposed for load frequency control (LFC) in an interconnected power system. This controller had five parameters to be tuned; thus, it provided two more degrees of freedom in comparison with the conventional PID. For proper tuning of the controller parameters, imperialist competitive algorithm (ICA) was used. ICA is a new evolutionary algorithm with proved efficiency. In this study, simulation investigations were carried out on a three-area power system with different generating units. These results showed that FOPID controller was robust to the parameter changes in the power system. Also, the simulation results certified much better performance of FOPID controller for LFC in comparison with conventional PID controllers

Effectiveness of Narrative Exposure Therapy on the Severity of Posttraumatic Stress and the Co-Morbid Symptoms of Iranian Survivors of Mina Disaster

Background: Mass gathering has not received much attention of researches as one of the potentially traumatic events in the field of psychological studies. Mina (Mecca, Saudi Arabia) disaster during 2015 hajj occurred in this context. Individuals may be at risk for posttraumatic stress disorder (PTSD), depression and somatic symptoms following traumatic events. Narrative exposure therapy (NET (has been known as a therapeutic protocol for PTSD and trauma-related disorders. The present study was carried out aimed to investigate the effectiveness of narrative exposure therapy on the severity of posttraumatic stress symptoms and the co-morbid symptoms of Iranian survivors of Mina disaster.Materials and Methods: The present study is based on single-case experimental design (SCED) with baseline. Eight Survivors of Mina disaster who met the criteria for posttraumatic stress disorder and completed inclusion criteria were randomly divided into two groups NET and control. The experimental group participant received twelve NET sessions individually. Data collection tool included PTSD Checklist for DSM-5 (PCL-5) and Beck depression inventory-II (BDI-II), patient health questionnaire 15 (PHQ-15). Data was analyzed using the cut-off point, percentage improvement index, RCI and the Hedges' g effect size.Results: Total percentage improvement of participant receiving NET for PTSD, was 68.25%, depression 63.25%, and somatic symptoms was 53.75%. All changes in the participant receiving NET were clinically significant in severity of PTSD, depression and somatic symptoms (RCI≥1.96).Conclusion: According to the results of this study, NET has a significant effect on the reduction of PTSD symptoms and its co-morbid symptoms

COVID‑19 associated rhino‑orbito‑cerebral mucormycosis, risk factors and outcome predictors; a multicentric study

Background Since the onset of the Covid-19 pandemic, an increase in mucormycosis cases has been observed in many countries, including Iran. However, the role of covid-19 and associated risk factors have not been thoroughly investigated. Objective This study is designed to identify epidemiologic characteristics, risk factors, and outcome predictors of Covid-19-Associated Rhino-Orbito-Cerebral Mucormycosis (C-ROCM). Methods Data of pathology proven Covid Associated ROCM cases were retrospectively obtained from 7 tertiary care centers throughout Iran from February 20, 2021, to July 22, 2021. Univariate and multivariate analyses were performed using binary logistic regression to assess the effects of various factors on the outcome. Results A total of 132 patients with C-ROCM were included in the study. The mean age of patients was 61.6 ± 13.9 (60.6% male). In 12 patients (9.1%), both eyes were involved. Diabetes was the mostcommon comorbidity (94.7%). The mortality rate was 9.1%, higher in males (12.5%) than females (3.8%). Severe vision impairment was seen in 58 patients (43.9%). Main factors that had a negative impact on the outcome in the univariate analysis include older age (P < 0.001), higher steroid dosage (P < 0.001), higher HbA1c level (P < 0.001), Covid-19 severity (P < 0.001), and brain involvement (P < 0.001). However, in the multivariate analysis, the effects of age (P = 0.062), steroid dosage (P = 0.226), and Covid- 19 intensity (P = 0.084) decreased, and the difference was no longer statistically significant. CRAO was a predictor of mortality in the univariate analysis (P = 0.008, OR = 4.50), but in the multivariate analysis, this effect decreased and was no longer significant (P = 0.125). Conclusion The risk of C-ROCM and its complications may increase in patients with more severe Covid-19, steroid over-prescription, ICU admission due to Covid-19, and poor glycemic control during and after Covid-19 treatment

Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm

Differential evolution (DE) algorithm is used to determine optimal location of unified power quality conditioner (UPQC) considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF) defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA) and immune algorithms (IA). Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA

A Novel Technique for Rotor Bar Failure Detection in Single-Cage Induction Motor Using FEM and MATLAB/SIMULINK

In this article, a new fault detection technique is proposed for squirrel cage induction motor (SCIM) based on detection of rotor bar failure. This type of fault detection is commonly carried out, while motor continues to work at a steady-state regime. Recently, several methods have been presented for rotor bar failure detection based on evaluation of the start-up transient current. The proposed method here is capable of fault detection immediately after bar breakage, where a three-phase SCIM is modelled in finite element method (FEM) using Maxwell2D software. Broken rotor bars are then modelled by the corresponding outer rotor impedance obtained by GA, thereby presenting an analogue model extracted from FEM to be simulated in a flexible environment such as MATLAB/SIMULINK. To improve the failure recognition, the stator current signal was analysed using discrete wavelet transform (DWT)