Industrial Feeder Research Articles

The Optimal Placement of a Photovoltaic-integrated Dynamic Voltage Restorer for the Enhancement of Power Quality within the Distribution System: A Case Study of 11Kv Simara Industrial Feeder in Nepal

The Optimal Placement of a Photovoltaic-integrated Dynamic Voltage Restorer for the Enhancement of Power Quality within the Distribution System: A Case Study of 11Kv Simara Industrial Feeder in Nepal

Power Loss Minimization and Voltage Profile Improvement on Nigeria Distribution Network Using Whale Optimization Algorithm

The power grid has significant power losses, unstable voltage, and large voltage drops during high demand due to its high resistance. One way to reduce power loss is by strategically placing and sizing Distributed Generation (DG) within the distribution network. However, improper installation of DG can increase power loss. To address this issue, various optimization techniques have been used, but finding the best solution and dealing with complex issues has been challenging. It is important to make efforts to optimally place and size DG in the distribution network to minimize power loss. To this end, a research study aimed to minimize power loss and improve the voltage profile on the DG network using the Whale Optimization Algorithm (WOA) was done. Objective functions were formulated and integrated into WOA, and power flow analysis on the standard IEEE 33-bus and 33-bus Ilorin industrial distribution feeder with and without DG was conducted using the forward and backward sweep distribution load flow algorithm. The optimal size and location of DG for power network loss reduction using sensitivity analysis (SA) and the whale optimization algorithm were determined. The results of the power flow analysis indicated that the total active losses and reactive power losses were reduced to varying extents with the integration of DG using both SA and WOA. The validation results showed that WOA is more efficient and provides high-quality solutions in terms of system loss reduction and best placement for DG in power systems compared to the application of SA. Additionally, WOA was found to offer accurate and high-quality solutions for power loss reduction compared to other existing techniques such as Loss Sensitivity Analysis (LSA), Grey Wolf Optimizer (GWO), Adaptive Shuffled Frogs Leaping Algorithm (ASFLA), and One Rank Cuckoo Search Algorithm (ORCSA). Keywords: Optimization, Distributed Generation (DG), Whale Optimization Algorithm (WOA), Sensitivity Analysis (SA)

Designing of multi-objective optimal virtual power plant model for reliability enhancement in radial network: a case study of Indian power sector

One of the major driving factors in the shifting of the present grid paradigm to an active grid network is the reliability and resiliency of the utility network. With hefty investment in the distribution network protection and maintenance, the reliability of the feeders is considerably enhanced; however, large numbers of outages are still occurring every year which caused major production loss to the manufacturing sector. In this paper, the role of the solar grid-based Virtual Power Plant (VPP) is evaluated in the state power utility for the reliability enhancement and cost minimization using a multi-objective model based on MILP optimization. A 90 bus industrial feeder having automatic reclosers, DER, and DSM is selected on which the MCS method is utilized for computing reliability indices using the utility reliability parameters. The value of reliability indices such as EENS is declined by 68% by utilizing the VPP scenario. These values of this reliability index are fed into the multi-objective model for cost minimization. After running the optimization, the results reveal that the operational and the annual energy cost are reduced by 61% and 55% respectively which advocates the VPP implementation in the utility network. Both modes of the Virtual Power Plant such as grid-connected and autonomous mode have been discussed in detail. Lastly, the results of the developed model with MILP are compared with the proprietary derivative algorithm, and it is found that the proposed MILP is more cost-effective. The overall results advocate the VPP implementation in the utility grid as the economical advantage is provided to both utility and the consumers in terms of reduction in EENS and energy charges respectively.

DESIGN AND CALIBRATION OF THE SYSTEM SUPERVISING BELT TENSION AND WEAR IN AN INDUSTRIAL FEEDER

In the paper, the issue of the supervision of belt tension and wear in industrial feeder is addressed. The designed system is based on strain gauges that are built into the roller and are subject to the belt pressure at each revolution. In order to assess the effectiveness of this system, calibration and uncertainty analysis was performed. As a result, it was demonstrated that the main source of uncertainty was the function of approximation, while the others were orders of magnitude smaller. The final function provided results with accuracy of ca. 10% of actually measured value, which was assumed to be a good result for this particular industrial application.

Feasibility of Solar Grid-Based Industrial Virtual Power Plant for Optimal Energy Scheduling: A Case of Indian Power Sector

The increased popularity of small-scale DER has replaced the well-established concept of conventional generating plants around the world. In the present energy scenario, a significant share of energy production now comes from the grid integrated DERs installed at various consumer premises. These DERs are being renewable-based generates only intermittent power, which in turn makes the scheduling of electrical dispatch a tough task. The Virtual Power Plant (VPP) is a potential solution to this challenge, which coordinates and aggregates the DERs generation into a single controllable profile. In this paper, a modified PSO-based multi-objective optimization is proposed for the VPP scheduling in distribution network applications such as energy cost minimization, peak shaving, and reliability improvement. For feasibility analysis of the VPP, a case study of state power utility is taken, which includes a 90 bus industrial feeder with grid integrated PVs as DER. The optimized results are computed in both grid-connected and autonomous mode reveal that the operating cost, peak demand, and EENS are declined by 31.70%, 23.59%, and 62.30% respectively. The overall results obtained are compared by the results obtained from other well-established optimization techniques and it is found that the proposed technique is comparatively more cost-effective than others.

Evaluasi Pengaruh Tegangan Kerja Generator terhadap Kualitas Tegangan Jaringan pada PT.PLN (Persero) Area Luwuk

One of the service quality parameters is that the voltage supplied to consumers is always at the set value, which is 20 kV for medium voltage and 380/220 Volt for low voltage, many factors can affect the magnitude of the voltage starting when the voltage is generated by the generator, the process distribution to consumers by using a conductor and the amount of load that is on the feeder. This study aims to determine how much influence the generator output voltage has on changes in voltage in the medium voltage network and how much voltage drop occurs at the JTM until it reaches the consumer. The results show that the generator output voltage will affect the base voltage, the greater the generator output voltage, the greater the base voltage and operating voltage of the system. The voltage drop along the industrial feeder before the generator voltage is increased is 281,856 Volts or if it is used as a percentage of 1.441% but when the generator output voltage is increased the voltage drop in the industrial feeder decreases by 277.016 Volts or if it is used as a percentage of 1.392%.

Voltage Control Strategy for Energy Storage System in Sustainable Distribution System Operation

Due to the increasing penetration of distributed energy resources (DERs) required for the sustainable distribution system, new voltage control strategy is needed by utilities. Traditional voltage control strategy can not support the increasing number of DERs in a coordinated and scalable manner to meet the operational voltage regulation requirement. Supported by the power electronics converter, the energy storage system can provide fast, smooth, and flexible voltage control services. In this paper, an effective and easy to implement sensitivity-based voltage control strategy is developed for the energy storage system. The developed control strategy is validated using an industrial feeder data in Northwest Washington. The proposed strategy can mitigate the voltage unbalance issue, improve the voltage profile, and correct power factors while supporting sustainable distribution system operation.

A New Approach for the Setting of Directional Overcurrent Relays by Incorporating Cascading Outages

Directional overcurrent relays (DOCRs) are the essential protective devices in distribution networks which are usually set without considering any contingencies. However, the current challenge in power systems is the existence of uncertainty and its unfavorable consequences. It sometimes appears that some elements simultaneously fail which makes other parts to be overloaded to the extent that it leads to cascading outages. Therefore, DOCRs may have mal-operation which ends in unwanted trips when there is no fault, or they may not operate in the case the fault is located within their reach point. In such cases, the coordination setting will need complex programming with many related non-linear inequality constraints. In this paper, a novel hybrid method is proposed based on multi-objective optimization including new objective functions by using the genetic algorithm (GA). Also, the cascading outages are considered in the presented method based on network data analysis. This approach is performed on distribution part of the IEEE 14-bus meshed system, and a real industrial radial feeder named TOSEE, located in Iran. The simulations have been implemented in MATLAB and PowerFactory-DIgSILENT software packages in different models, and the results are evaluated.

Resiliency-Driven Proactive Distribution System Reconfiguration With Synchrophasor Data

Measuring and enabling resiliency of electric distribution systems with increasing weather and cyber events are important. Some of the extreme events (e.g. Earthquakes, Hurricanes) and associated paths are predicted and monitored closely in advance and allow to take pre-event proactive control actions. The Distribution Phasor Measurement Units (D-PMUs) provide new opportunities and supporting such proactive actions. A synchrophasor based resiliency driven pre-event reconfiguration can ensure minimizing impact of the expected event on the power distribution system and associated performance. However, the D-PMUs will also face challenges in terms of data quality similar to the transmission PMUs. The focus of this paper is to provide data mining approaches for anomaly detection in D-PMUs and proposing resiliency-driven pre-event reconfiguration with islanding as a proactive mechanisms to minimize the impact of adverse events on system using processed synchrophasors data. Results are validated for real industrial feeders and test cases with satisfactory response.

Data-Quality Aware Distribution State Estimation Using Maximum Normal Measurement Rate

State estimation application in the distribution system is being revisited with the availability of additional sensor data enabled by the distribution automation and massive sensors installation in the electric power grid. Some of these sensor data have measurement error, data quality problems, and different reporting rate. The traditional weighted least square estimation (WLSE) method is used to find best fit between the system model and the measured data. WLSE will typically give low performance and poor accuracy when some measurements have excessively large error compared to the rest of the measurements. This work proposes a maximum normal measurement rate (MNMR) based state estimation with simultaneous bad data detection method and considering three-phase unbalanced systems. The simulation results for an IEEE test system and an industrial feeder demonstrate the MNMR-based state estimation provides better performance even in the presence of multiple bad measurement data.

Cost-effective telemetry for energy network of an electricity distribution company: part I

We present a novel application of radio frequency wireless mesh network and general packet radio service technologies in a telemetry solution to measure power flow in the energy network of an electricity distribution company. The telemetry solution utilizes some selected circuits of grid stations and calculates total power consumed, total power imported, and total power exported by the distribution company. The selection of circuits for sensors installation is the key for reducing solution cost as compared to the case when sensors are installed on all the power output points. The framework involves installation of specially developed energy sensors (smart energy meters) and data concentrator units at the selected grid stations for measurement of energy data that include active energy, reactive energy, active power, apparent power, current, voltage, and power factor. The measured data reach the data concentrator unit using a 433-MHz wireless mesh network and are transmitted to a remote power control center using general packet radio service. Energy data from different grid stations across the energy network are collected at the power control center and utilized in calculation of total power consumed, total power imported, and total power exported. The approach has been tested on two electricity distribution companies of Pakistan: the Islamabad Electric Supply Company and Peshawar Electric Supply Company. Also in this work, the result of overload detection based on a generalized likelihood ratio test for an industrial feeder of the Islamabad Electric Supply Company is included. Detection probability of 0.96 with a false alarm probability of 0.04 has been achieved for a 30-min data interval.

CFD Modeling of the Feed Distribution System of a Gas-Solid Reactor

Granular flow simulation using CFD has received a lot of attention in recent years. In such cases, CFD is either, coupled with Discrete Element Method (DEM) techniques for appropriate incorporation of inter-particle collisions, or the Eulerian CFD approach is used in which granular particles are treated as they were fluid. In the present study, a CFD analysis was performed for granular flow in an industrial screw feeder to study the choking phenomena. Eulerian multiphase flow model, also known as two-fluid model in the case of two phases, was used along with the solids closures based on Kinetic Theory of Granular Flow (KTGF). The rotating effect of the half pitch screw was incorporated by using the immersed boundary method (IMB). Variation of mass flow through change in revolution per minute (RPM) and moisture content was studied in this work. A jump condition in the axial profiles of both the solid phase volume fraction and pressure was observed near the inlet. It was found that the jump condition in solid phase volume fraction and pressure profiles reduces by increase in the RPM of the screw.

Estimation of powder mass flow rate in a screw feeder using acoustic emissions

Screw feeders are widely used in powder processes to provide an accurate and consistent flow rate of particles. However this flow rate is rarely measured or controlled. This investigation explores the use of generalised norms and moments from structural-borne acoustic emission (AE) measurements as key statistical indicators for the estimation of powder mass flow rate in a screw feeder.Experimental work was carried out acquiring AE measurements from an industrial screw feeder working with four different types of material at different dispensation rates. Signal enveloping was used in the first place to eliminate high frequency components while retaining essential information such as peaks or bursts caused by particle impacts. Secondly a set of generalised norms and moments was extracted from the signal, and their correlation with mass flow rate was studied and assessed. Finally a general model able to estimate mass flow rate for the four different types of powders tested was developed.

Characteristics of Harmonic Distortions in Residential Distribution Systems

Harmonics produced by residential loads have become an increasing concern in recent years due to the extensive adoption of power-electronic-based home appliances. This paper presents analysis on extensive field data collected from various locations of residential distribution systems in North America. The degree of cancellation of harmonic currents from different sources is determined. A comparative study on the harmonic characteristics of residential, commercial, and industrial feeders is also conducted. The results show that the harmonic current distortion levels of residential feeders are much higher than those of the industrial and commercial feeders. The third harmonic is the most pronounced component and the low-order harmonic currents from different homes tend to add to each other, i.e., the harmonic cancellation effect is much less than those claimed in the literature.

VOLTAGE COMPENSATION USING ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF RUMUOLA DISTRIBUTION NETWORK

A study of hourly voltage log taken over a period of six months from Rumuola Distribution network Port Harcourt, Rivers State indicates that power quality problems prevalent in the Network are undervoltage/voltage sags and overvoltage/voltage swells. This paper aims at addressing these power quality problems in the distribution network using artificial neural network (ANN) controller based dynamic voltage restorer (DVR). The artificial neural networks controller engaged to controlling the dynamic voltage restorer were trained with input and output data of proportional integral (PI) controller and of unit amplitude generator obtained during simulation. All simulations and modeling were carried out in MathLab/Simulink. Proposed dynamic voltage restorer was tested with replicated model of Rumuola substation by simulating with sample of average voltage for Omerelu, Waterlines, Rumuola, Shell Industrial and Barracks feeders. Simulation results showed that DVR is effective in compensating for under-voltage and over-voltage in Rumuola Distribution network Port Harcourt, Rivers State. http://dx.doi.org/10.4314/njt.v36i1.23

VOLTAGE COMPENSATION USING ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF RUMUOLA DISTRIBUTION NETWORK

A study of hourly voltage log taken over a period of six months from Rumuola Distribution network Port Harcourt, Rivers State indicates that power quality problems prevalent in the Network are undervoltage/voltage sags and overvoltage/voltage swells. This paper aims at addressing these power quality problems in the distribution network using artificial neural network (ANN) controller based dynamic voltage restorer (DVR). The artificial neural networks controller engaged to controlling the dynamic voltage restorer were trained with input and output data of proportional integral (PI) controller and of unit amplitude generator obtained during simulation. All simulations and modeling were carried out in MathLab/Simulink. Proposed dynamic voltage restorer was tested with replicated model of Rumuola substation by simulating with sample of average voltage for Omerelu, Waterlines, Rumuola, Shell Industrial and Barracks feeders. Simulation results showed that DVR is effective in compensating for under-voltage and over-voltage in Rumuola Distribution network Port Harcourt, Rivers State. http://dx.doi.org/10.4314/njt.v36i1.23

A Drop Test for Finding the most Probable Resting Orientation of a Part

The material handling is the art of moving, orienting, packing and storing the part. Industrial feeders are used to facilitate the operations by feeding the parts in a specific quantity and at a perfect orientation. It is a tedious task to obtain a particular part orientation, at the assembly station, in a short lead time. To overcome this problem, part feeders are used to segregate and orient parts prior to packing. The natural resting orientation of the part is the orientation in which the part rests on a horizontal hard surface, when dropped from a height. The most probable natural resting orientation of the part has to be identified which helps in the effective design of feeder and orienting devices. In this paper, an attempt was made to study the effect of initial orientation from different heights on natural resting orientation. Drop test was conducted at different heights with each initial orientation. The favorable orientation of the part (or) the most probable natural resting orientation is identified using drop test. In this work, most probable natural resting orientation of a typical asymmetric component, brake pad, is identified.

Predictive Reliability Assessment in the Power Distribution System

The electrical utilities are facing market conditions and therefore have to plan and operate their distribution systems in a cost effective way. This implies that the customer’s requirement on reliability i.e. availability has to be balanced towards the cost for obtaining the same. An effective way to solving this issue is by the use of quantitative assessment of reliability, i.e. reliability indices, which is based on probability theory. However these methods require input data that defines the condition for the system and its components. is to predict the future behaviour based on collected data and measured performance. The reliability assessment is normally used to evaluate performance of the distribution system network. The reliability of power Distribution system can be calculated by different reliability indices.This paper describes the reliability indices for two feeders of one is an industrial feeder and another one is an urban feeder. A software module (Reliability Assessment Module-RAM) has been used and the results of two practical distribution feeders are compared to benchmark the performance and operation of the power distribution system.

Reliability Analysis of Distribution Transformer A Case Study of Gwiwa Business Unit, Sokoto

In this paper, the reliability of 11/0.415KV town feeder transformers comprising four sub-feeders (Town, GRA, Water Works and industrial) located at Gwiwa Business Unit, Sokoto were studied. The cost implications of failed transformers were also studied, using the data collected from Central Bank of Nigeria (CBN, 2009). It was found that the total amount lost was N37,997,732.40, N16,522,245.88, N20,934,463.70 and N25,559,391.64 for Town, GRA, Water Works and Industrial respectively, over the four years. It is revealed that the approximate time any transformer under Town, GRA, Water Works and industrial feeder may be expected to function before fault or failure (Mean Time Between Failures, MTBF) is 9 months, 39 months, 20 months and 14 months respectively. It was also found that reliability of Town feeder is 52%, GRA79%, Water works 62% and Industrial feeder 50%. It was deduced that town and GRA are under semi-reliable conditions because they are subjected to load beyond their identified plate capacity.

Model based feedforward control of an industrial glass feeder

This article presents the automation of set point changes of an industrial glass feeder in container glass production. A model is proposed consisting of multiple first order partial differential equations (PDEs). Based on the derived model a feedforward control approach is presented. The approach allows for the calculation of control inputs out of reference trajectories of the system outputs and is used to perform automated set point changes with short transition time. Finally, the approach is implemented at an industrial glass feeder. Measurement results from the Thüringer Behälterglas GmbH (Schleusingen, Germany) are included.