Volume 16, Issue 5 -

Distribution systems are traditionally designed as radial passive systems fed from a single source. Protection coordination of such systems has been easily established assuming the system radiality. Insertion of distributed generators (DGs) into distribution systems makes the distribution system to be more active which causes redistribution of fault currents magnitudes and directions. This causes negative impacts on the original protection system coordination, since the distribution system losses its radiality and passiveness. Recently protection coordination in the presence of distributed generation has been paid a great attention. Researchers proposed various solutions to solve the protection coordination problem caused by adding DG into the distribution network. In this paper, the proposed solutions for the protection coordination problem considering the DG insertion will be illustrated, classified, and criticized.

This paper presents design and development of solar power monitoring and control through GSM network in rural application. This system includes a GSM mobile and GSM hardware installed at solar system with 12VDC power for solar power monitoring along with temperatures (ambient and battery). This system is designed to conceptualizing how much solar power transferred to batteries and temperature conditions for that instant of time. Hardware is developed for the continuous update to the targeted station using GSM. The developed hardware gets the signal from the installed location calculate the real time power and temperature parameters. This information transferred to targeted mobile station through GSM interface using texting service (SMS). At the receiving end, power monitoring system is used to maintain the power to batteries profile locally. An easy, cost proficient and consistent working model of whole system has been developed which may be incorporated for data acquisition. Also the same system can use for uninterrupted power supply (UPS) systems.

This paper aims to evaluate the performance of commercial power quality (PQ) instruments. By using a high precision programmable voltage and current source, five meters from different manufacturers are analyzed and compared. At first, three-phase voltage signals are applied to those PQ instruments, considering harmonic distortion, voltage dip, voltage swell, as well as unbalanced voltages. These events are measured, compared and evaluated considering the different instruments. In addition, voltage and current signals are applied under different conditions, with and without harmonic and unbalances, in order to obtain the measurements of electrical power. After analyzing the data generated in all these tests, efforts are focused on establishing a relationship between the accuracy of the measurements. Considering the percentages of errors, a score is assigned to each instrument. The tests have shown “excellent” and “good” results regarding measuring active and apparent power, as well as power factor. However, for non-active power, almost all instruments had lower performance. This work is relevant considering that Brazil is deploying standardization in terms of power quality measurements aiming towards regulatory procedures and index limits.

In the literature, several papers propose new methodologies to determine the optimal placement/sizing of medium size Distributed Generation Units (DGs), using heuristic algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). However, in all methodologies, the optimal placement solution is strongly dependent of network topologies. Therefore, a specific solution is valid only for a particular network topology. Furthermore, such methodologies does not consider the presence of small DGs, whose connection point cannot be defined by Distribution Network Operators (DNOs). In this paper it is proposed a new methodology to determine the optimal location of medium size DGs in a distribution system with uncertain topologies, considering the particular behavior of small DGs, using Monte Carlo Simulation.

This paper presents an experimental study on detection and diagnosis of broken rotor bars in Squirrel Cage Induction Motor (SQIM). The proposed scheme is based on Motor Current Signature Analysis (MCSA) which uses amplitude difference of supply frequency to upper and lower side bands. Initially traditional MCSA has been used for rotor fault detection. It provides rotor health index on full load conditions. However in real practice if a fault occurs motor can not run at full load. To overcome the issue of reduced load condition a Fuzzy Logic based MCSA has been designed, implemented, tested and compared with traditional MCSA. A simulation result shows that proposed scheme is not only capable of detecting the severity of rotor fault but also provides remarkable performance at reduced load conditions.

Among the four basic dynamic voltage restorer (DVR) topologies, the network-side shunt-connected DVR (NSSC-DVR) has a relatively poor performance and is investigated in this paper. A new configuration is proposed and implemented for NSSC-DVR to enhance its performance in compensating (un)symmetrical deep and long voltage sags and mitigate voltage harmonics. The enhanced NSSC-DVR model includes a three-phase half-bridge semi-controlled network-side-shunt-connected rectifier and a three-phase full-bridge series-connected inverter implemented with a back-to-back configuration through a bidirectional buck-boost converter. The network-side-shunt-connected rectifier is employed to inject/draw the required energy by NSSC-DVR to restore the load voltage to its pre-fault value under sag/swell conditions. The buck-boost converter is responsible for maintaining the DC-link voltage of the series-connected inverter at its designated value in order to improve the NSSC-DVR capability in compensating deep and long voltage sags/swells. The full-bridge series-connected inverter permits to compensate unbalance voltage sags containing zero-sequence component. The harmonic compensation of the load voltage is achieved by extracting harmonics from the distorted network voltage using an artificial neural network (ANN) method called adaptive linear neuron (Adaline) strategy. Detailed simulations are performed by SIMULINK/MATLAB software for six case studies to verify the highly robustness of the proposed NSSC-DVR model under various conditions.

The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel transmission lines with complex mutual coupling. The test results, considering wide variations in operating conditions of the faulted power network, indicate that the proposed adaptive relay setting provides significant improvement in the relay performance.

This paper presents the voltage stability of a DC smart grid based on renewable energy resources during grid connected and isolated modes. During the islanded mode the load shedding, based on the state of charge of the battery and distribution line voltage, was proposed for voltage stability and reservation of critical load power. The analyzed power system comprises a wind turbine, a photovoltaic generator, storage battery as controllable load, DC loads, and power converters. A fuzzy logic control strategy was applied for power consumption control of controllable loads and the grid-connected dual active bridge series resonant converters. The proposed DC Smart Grid operation has been verified by simulation using MATLAB ® and PLECS ® Blockset. The obtained results show the effectiveness of the proposed method.

In recent years, the UAV (Unmanned Aerial Vehicle) inspection for the electrical line has received increasing attentions due to the advantages of low costs, easiness to control and flexibility. The UAV can inspect the electrical tower independently and automatically by planning the flight path. But during the inspection along the path, the UAV is easily impacted by gust wind due to its light weight and small size, which always leads to the crash into the electrical tower. Thus, in this paper, a safe flight approach (SFA) is proposed to make the flight be safer during the inspection. The main contributions include: firstly, the piecewise linear interpolation method is proposed to fit the distribution curve of the electrical towers based on the GPS coordinates of the electrical towers; secondly, the no-fly zone on the both sides of the distribution curve are created, and a security distance formula (SDF) is raised to decide the width of the no-fly zone; thirdly, a gust wind formula (GWF) is proposed to improve the artificial potential field approach, which can contribute to the path planning of the UAV; finally, a flight path of the UAV can be planned using the SFA to make the UAV avoid colliding with the electric tower. The proposed approach is tested on the experiment to demonstrate its effectiveness.