International Journal of Smart Electrical Engineering
Volume:7 Issue: 2, Spring 2018

With the large-scale production of plug-in electric vehicles (PEVs), a new entity, the PEV fleet aggregator manages charging and discharging processes of the vehicles. The main objective of an individual aggregator in interaction with electricity markets is maximizing its profit. In this paper, the performance of this aggregator in day-ahead and real-time electricity markets, considering (a) customers’ satisfaction constraints, (b) the effects of driving patterns and real-time energy market prices uncertainties and (c) resulted effects on the network operation, is studied. Then, the capability of a bilateral contract between the aggregator and distribution system operator as a regulation for satisfying the network’s limitations is investigated. The proposed model is formulated as a two-stage stochastic programming problem and implemented in GAMS software. The findings of the study reveal the effectiveness of the proposed algorithm on maximizing the aggregator’s profit-making as well as both customers’ and Distribution System Operator’s financial and technical satisfaction.

Low voltage microgrids including sensitive loads often face unbalanced load conditions. Therefore, a compensation procedure should be carried out in order to balance and restore sensitive load’s voltage. In this paper, an effective voltage control strategy has been proposed for the autonomous operation of microgrids, under unbalanced load conditions.  The proposed strategy balances single-phase sensitive loads by compensating the unbalanced voltage drop of the impedance between the outputs of Distribution Generation (DG) to the Point of Common Coupling (PCC). In addition, this scheme has also shown to be capable of restoring sensitive loads’ voltage to nominal values. This method also shares the active and reactive load accurately between Distribution Generation (DG) units, based on their capacity. In order to evaluate the performance of the proposed control strategy, several simulations have been conducted under various states in an islanded microgrid prototype. Obtained simulation results demonstrate the effectiveness of the proposed control strategy in compensation of unbalanced load voltage and voltage restoration.

This paper discusses the Dynamic voltage restorer (DVR) operation and control for Voltage sags compensation. DVR is a series connected power electronic based device that can quickly mitigate the voltage sags in the system and restore the load voltage to the pre-fault value. Voltage sag associated with faults in transmission and distribution systems, energizing of transformers, and starting of large induction motor are considered as most important power quality disturbances (PQD). The most of the industries uses the power electronics conversion and switching for manufacturing and processing. These technologies are needs high quality and reliable power supply. Not only the industries, but also the electric power utilities and customers are becoming increasingly anxious about the electric power quality. Sensitive loads such as digital computers, programmable logic controllers (PLC), consumer electronics and variable frequency motor drives need high quality power supplies. DVR is recognized to be the best effective solution to overcome this problem. The primary advantage of the DVR is keeping the users always on-line with high quality constant voltage maintaining the continuity of production. Also, this paper simulates the DVR with the power system using MATLAB/Simulink are demonstrated to prove the usefulness of this DVR to enhance the power system quality.

Partial Discharge assessment in the insulation of high voltage equipment is one of the most popular approaches for prevention of the insulation breakdown. In the procedure of thisassessment, noise reduction of partial discharge signals to get the original PD signal for accurate evaluation is inevitable. This denoising process shall be carried out such a way that the main features of the partial discharge signal like “amplitude”, “rise time”, “energy” and etc. are kept as much as possible. Wavelet Transform and Mathematical Morphology are the useful signal processing algorithms which are exploited and proposed in literatures for noise reduction of partial discharge signals. In this paper two Wavelet based filters which have promising results are explored and finally compared with the proposed Morphologicalbased filter. Unlike the traditional morphological based filters the advantage of the proposed method is the ability of structure element length selection in a completely self-adaptive procedure.Also the results of noise reduction in different noise level are presented that the proposed method shows superiority in all circumstance.

Working memory (WM) is a part of human memory, the ability to maintain and manipulate information. WM performance is impaired in some neurological and psychiatric disorders such as schizophrenia and ADHD. Neurofeedback training is a self-regulation method which can be used to improve WM performance by changing related EEG parameters. In this paper we used neurofeedback training to improve WM performance in eight healthy individuals. The protocol was consisted of individual upper alpha up-training in parietal brain lobe of participants which is a part of fronto-parietal network and related to central executive functions of WM. Power of individual upper alpha band in channels P3 and P4 was used for neurofeedback training in five sessions. 2-back working memory test was used to measure WM performance before and after the course. Results indicated success of subjects in neurofeedback training and enhancement of individual upper alpha power in both channels (P3 and P4). Results of 2-back test indicated that improvement in response accuracy and response time of test was significant. Also the correlation between the change in power of individual upper alpha band in channel P3 and change in response time of 2-back test was significant approximately (r= -0.571 and P=0.076). In conclusion it seems that individual upper alpha neurofeedback up-training in parietal lobe is an appropriate method to improve WM performance.

In this article, an innovative supervision system will be proposed that can observe and analyze health of Circuit Breaker’s trip coil. The proposed design also logs changes in the coil's quality and informs network supervisor in case of Circuit Breaker (CB) failure. This system injects small direct currents to the Circuit Breaker connections and the trip coil to compute CB’s health and characteristics of trip coil. A large drift such as great change of resistance in coil, connections and switches characteristics can be determined as defection of Circuit Breaker. This supervision system analyzes trip coil health with a microcontroller, logs trip coil condition changes (closed or tripped), failures and CB defection in a multimedia card, shows condition of system via LEDs and LCD and sends needed information for network supervisor via SMS, Telephone line and also applies desired controls to the other appliances through three power relays. Besides, a number of these supervision systems can be networked via Ethernet to be observed and supervised with a web service program or webpage from a control room.