Station Transmission Research Articles

Risk assessment for gas transmission station based on cloud model based multilevel Bayesian network from the perspective of multi-flow intersecting theory

Accidents occurred in the natural gas transmission stations may result in casualties, equipment damage, property loss and even political and ecological impact. It is necessary to propose an approach for the gas transmission stations risk assessment so as to identify risk factors and prevent accidents. However, insufficient attention has been paid to the complex interactions and coupling patterns of these factors with current risk assessment methods. Hence, a novel risk analysis strategy is needed for industrial site risk assessment. Given industrial site risk factors, the multi-flow intersecting theory (MIT) is first defined to consider material, information and behavior risk analysis. Then the multilevel Bayesian network is constructed to represent these factors from different flows. To handle issues of insufficient statistical data and subjectivity associated with expert judgement, cloud model and fuzzy Bayesian are incorporated. For the defuzzification, existing cloud model is improved by introducing the similarity degree of standard cloud and evaluation cloud. Then the prior and conditional probabilities obtained from cloud model are input into Bayesian network for further reasoning and accident probability prediction. To validate the utility of the proposed method, the gas transmission startup process was chosen for risk assessment.

Electricity load forecasting in smart grid using web based geographic information systems (web GIS)

India is a developing nation and due to emerging new infrastructure in various sectors, the demand of electricity is always higher than generation. Smart Grid is an automated system which includes automation of existing electrical infrastructure into modern and controlled system with the help of IT control, Internet of Things (IoT) systems that enables real-time monitoring and control of bi-directional power flows and information flows from generation to consumption. Electricity demand is a major issue in India and with the help of these technologies the demand of electricity can be managed in reliable and economic mode. Consumers can monitor real-time energy consumption of their energy use, and this can be reflected in supply, demand and generation of energy. State utilities send their billing data to Electricity Regulatory Commission every year where billing data analysis is carried and new tariff of electricity is decided by the Regulatory Commission to all Consumers of Electricity in the State. Web based Geographical Information System (GIS) can help by mapping all electrical infrastructures on a digital map including their complete details and all consumers can be mapped. Web based GIS can help to state utilities as a tool for plan and manage their all assets by logging into the system from anywhere. Web based GIS can help to manage area wise Load Scheduling by integrating Road, Buildings, Lands, Transmission Stations, Transmission Lines, Generation Stations and consumer's detail. This system can help for Load Forecasting, Decision Making and Electricity Demand Management for State Utilities, Regulatory Body and Policy Makers towards making effective approach in Energy Conservation and Efficiency.

Power loss minimization and voltage profile improvement on electrical power distribution systems using optimal capacitor placement and sizing

Distribution system operators are having difficulties maintaining a correct voltage profile across its network. As the standard of living of its customers increases, suppressed loads tend to come up and this in turn would require and increased demand in power supply. The increase in power demand and high load density at distribution ends have been seen to have key consequences of increasing the power loss and reducing the voltage profile in power systems, which seriously jeopardizes the ability of radial distribution networks to faithfully account for the power received from transmission stations. This work is aimed at improving the power quality that gets to the end users. Shunt capacitors have been suggested to be a suitable solution to this problem as they supply the reactive power needed for compensation. As a result, the optimum placement and size of these shunt capacitors have received a great deal of attention. Despite its efficacy, meta-heuristic algorithms are seldom utilized in the Nigerian RDS (radial distribution system), since most published research instead uses analytical and numerical programming methods. As a result, this research explains how to use a Hybrid Solution (HS) of Particle Swarm Optimization (PSO and GA) to identify and size shunt capacitors for real-time power loss reduction on an 11-kV distribution feeder. The backward-forward sweep load flow method with Loss Sensitivity Factor (LSF) is used to identify suitable buses for shunt capacitor installation, and the HS algorithm is then used to estimate the optimum size. This method was discovered to decrease the system's real power loss by 54.88% while raising the minimum bus voltage magnitude to the acceptable limit and thus improving the minimum system Voltage Stability Index (VSI). Based on these findings, the suggested technique is regarded as a viable way for placement and determining the size of shunt capacitors in a real-world Radial Distribution System. The numerical results shows that the approach has a high capability of improving the voltage profile of the distribution network, leading to an improved system power quality, minimize the system losses, correct the power factor, and maximize the net savings. The numerical results were gotten by using MATLAB package.

On the Performance and Optimization of HAPS Assisted Dual-Hop Hybrid RF/FSO System

In this paper, we derive accurate outage probability and bit error rate expressions for a high altitude platform station (HAPS) assisted terrestrial communication system. In particular, HAPS is deployed as a relay node to assist two ground stations for data transmission. Each ground station-to-HAPS communication link works on a hybrid radio frequency (RF) and free space optics (FSO) mode. Selection combining is performed at the HAPS and the destination ground station to select either RF or FSO link based on the instantaneous channel signal-to-noise ratio (SNR). The accuracy of the derived outage probability and bit error rate expressions are validated with extensive computer simulations. We further develop an optimal power allocation scheme that optimizes the transmit power of source-ground-station and HAPS while satisfying practical energy consumption constraints. The derived expressions provide more insights on system design and assist analyzing HAPS-terrestrial integrated network supported by hybrid RF/FSO system.

Цифровізація процесів митного контролю та митного оформлення вантажів на залізничному транспорті

The article is devoted to the research of proposals on the organization of rational customs control, processing and passing of trains at the border transfer stations of Ukraine in the service international traffic. For quality work and fast processing of cars there is a need to improve the information component of the transportation process export and import freight flows through border transmission stations. This possibility is provided by the use of electronic declaration during the registration of international cargo operations. International transportation of goods is a necessary detail that makes it possible to realize trade relations between states. It is an effective tool of foreign economic activity, without which it would be almost impossible. The efficiency of the organization international cargo transportation significantly depends on the coordinated organization of the work the border transfer station, which carries out a complete list of operations in cooperation with customs, border and other state control services. In order to increase the technology of passing international freight flows through border transfer stations, it is necessary to introduce the latest information and control systems that will reduce the duration of train processing at border transfer stations and, as a result, reduce downtime and delayed cars. Research on the development of technologies and means electronic data exchange that provide information support for international cargo transportation is promising. The electronic data exchange system must comply with the international transport infrastructure, be based on agreed technical parameters and meet the needs of compatibility of transportation technologies as a criterion for the integration of the national transport system into the world system. It is proposed to carry out preliminary declaration of goods and processing transport documents before the departure of the train to the border transfer station to reduce the technological time of processing trains. This will reduce the processing time of the transit train by 105 minutes. The main advantages of the introduction electronic document management: simplification of document management; making effective management decisions; increasing the reliability of the processed information, reducing the downtime of cars. Thus, the introduction of the system pre-declaration of goods and processing of transport documents in the processing international freight traffic will reduce material and labor costs and speed up the passage of goods through customs clearance.

ENHANCEMENT OF ARC CONTROL AT BORIKIRI 11/33KV DISTRIBUTION STATION, PORT HARCOURT, RIVERS STATE

This research work has highlighted the benefits of enhancement of arc at Borikiri 33kV Distribution Network in Rivers State, Nigeria. The flash arc analysis was modelled and simulated using ETAP 12.6 software environment to show the sequence of operation of arc flash from the Injection substation to the Transmission Station. The analysis focus on the fault current occurred at some point once the relay protection device issued a clearing time in seconds, the circuit breaker was absolutely tripped and when an arc fault occurs, the latched fault occurred showing that a short circuit that has no electrical resistance at the point of the fault, that is characterised by an absence of arcing. The case study shows the connection between the clearing/tripping time and fault current for the prevailing and simulated case study; for the existing case study shows the minimum values and therefore the most values, once the clearing/tripping time was 0.011 sec, the fault current was 32.20 kA and when the clearing/tripping time was 0.025 sec, the fault current was 34.12 kA, the result show the behavior of the graph as linearity. The graph shows that as clearing/tripping time will increase, fault current increases slowly at first. Similarly, because the clearing/tripping time and the the} fault current will increase slowly at first, then additional rapidly, then slows down once more and reaches a most level. The simulated case study also shows the link between the fault current and clearing time shows the minimum values and the maximum values, once the clearing/tripping time was 0.062 sec, the fault current was 4.62 kA and when the clearing/tripping time was 0.26 sec, the fault current was 5.01 kA, the graph show that as clearing/tripping time increases, fault current increases slowly at first. Relationship between the incident energy, flash protection boundary and clearing time of the prevailing case study; once clearing or tripping time was zero.011 sec, the flash protection boundary was 1.03 feet, and therefore the incident energy of 0.73 cal/cm2 , according to standard for Electrical Safety, our result shows that Hazard Risk categories is 0 (HRC 0) that cause a second degree burn to unprotected skin.

Optimization of Energy Efficiency for Electric Power Distribution System Losses

Abstract: This study evaluated the existing electric power network of Mile 2 Diobu zone, Port Harcourt distribution network which consists of four (4) 11kV distribution feeders namely; Ojoto, Nsukka, Udi and Silverbird. This work considered Ojoto and Nsukka Street distribution network for improved power quality. The three (3) 33/11kv injection substations are fed from 165 MVA transmission station (PH Town) at Amadi junction by Nzimiro. Collection and analysis of data collected from the injection substations that supply electricity to mile 2 Diobu, Port Harcourt was the first consideration. The distribution network was modeled in Electrical Transient Analyzer Program (ETAP) using Newton-Raphson Load Flow equations. The simulation result of the existing condition network shows that the network has low voltage profile problem on Nsukka network and overloading of distribution transformers on Ojoto networks. The following optimization techniques are applied: up-gradation of distribution transformers, and transformer load tap changer to improve the distribution network for Mile 2 Diobu, Port Harcourt electrical power network. The simulation result of the improved distribution network for Mile 2 Diobu, Port Harcourt power network shows that the voltage profile Nsukka network has improved within the statutory limit which is between 95.0 -105.0% and the loading of the distribution transformers on Ojoto and Nsukka networks are all below 70% required capacity. Keywords: Optimization, Energy Efficiency Distribution

Review of machine learning applications to power systems studies

The complexity of electric power networks from generation, transmission and distribution stations in modern times has resulted to generation of big and more complex data that requires more technical and mathematical analysis because it deals with monitoring, supervisory control and data acquisition all in real time. This has necessitated the need for more accurate analysis and predictions in power systems studies especially under transient, uncertainty or emergency conditions without interference of humans. This is necessary so as to minimize errors with the aim targeted towards improving the overall performance and the need to use more technical but very intelligent predictive tools has become very relevant. Machine learning (ML) is a powerful tool which can be utilized to make accurate predictions about the future nature of data based on past experiences. ML algorithms operate by building a model (mathematical or pictorial) from input examples to make data driven predictions or decisions for the future. ML can be used in conjunction with big data to build effective predictive systems or to solve complex data analytic problems. Electricity generation forecasting systems that could predict the amount of power required at a rate close to the electricity consumption have been proposed in several works. This study seeks to review machine learning applications to power system studies. This paper reviewed applications of ML tools in power systems studies.

New capability for neutron transmission measurements at LANSCE: The DICER instrument

A new capability for neutron transmission measurements has been developed at the Los Alamos Neutron Science Center (LANSCE). The DICER (Device for Indirect Capture Experiments on Radionuclides) instrument is designed to tightly constrain neutron-capture cross sections for short-lived radionuclides that are beyond the reach of direct techniques, via measurement and analysis of neutron transmission resonances on these same radionuclides. The innovative DICER apparatus enables simultaneous sample-in and sample-out measurements, thus minimizing the amount of sample material needed and reducing the measurements time by half. A description of the current status of the new transmission station, along with a performance overview and results from known reactions, will be presented.

Deteksi Radar Terhadap Multi-Object Bergerak Dengan Pemrosesan Doppler

In general, Radar or Radio Detection and Ranging is an electromagnetic wave system that is useful to measure distance and answer and make maps of surrounding objects. Radar has an advantage compared to other navigation tools, which is that radar does not require a transmitter station as a transmitter. Radar has an electronic wave emission principle that emits short radio wave pulses emitted in a narrow beam by a directional antenna. In this study, a multi-object radar detection simulation was carried out using Dopler processing both MTI and PDP, which later on the radar will detect related objects. Multi-object here is a condition that is achieved when a navigation radar detects more than one object. The result of this research is a multi-object detection process using the MTI and PDP methods and the matched-filter obtained from the predetermined data. So Doppler processing aims to mitigate the clutter signal to improve the detection performance of moving targets even though there is a dominance of signals originating from stationary clutter.

Proposition of an attenuating solution for noise pollution caused by telecommunications installations and systems in urban environments

This study evaluates the noise generated by metallic cabinets of telecommunications transmission stations, before and after the implementation of a sound attenuator. The first step consisted of installing the attenuating system, which consisted of a glass wool plate on top of a metal cabinet. Then, we compared the results with a cabinet without the installation of the system. The speeds of the cooling system of the cabinets were the average and maximum. Noise measurements followed the guidelines of NBR 10151, and the acoustic descriptor used was the mean equivalent level (Leq). After verifying the effectiveness of the installation of the system in sound attenuation, several cabinets were adapted in installations located in two cities in southern Brazil. One installation was located in a residential area, with houses on its surroundings, and the other on top of a residential building. The study showed that the attenuating system was effective in reducing the noise generated by the cabinets, both at average and at maximum speed, in both locations. Although the final sound levels did not reach those recommended by the national standard NBR 10151, of acoustic comfort for communities, residents close to the facilities reported an improvement in the local acoustic environment.

Vibration characteristics analysis and structural improvement of natural gas venting ignition pipeline

In order to study the flow-induced vibration characteristics of the natural gas vent pipeline under the internal flow field, taking the gas transmission station pipeline as an example, the ANSYS Workbench software was used to establish models under two working conditions, uncoupling and fluid-solid coupling, for modal analysis, and analyze and compare the calculation results and propose a structural improvement plan. The results show that the maximum amplitude of the first three modes under the two working conditions is concentrated on the riser mouth, and the amplitude under the fluid-solid coupling condition is slightly larger than that of no coupling; the inner diameter of the pipe elbow is large and the pressure is small, and the outside diameter is small and the pressure is small. Large, this instability will increase the air pulsation of the flow field. In the improved scheme, adding a restriction on the top to increase the rigidity of the pipeline can significantly reduce the maximum amplitude of the gas pipeline; adding an orifice to eliminate air flow pulsation has a certain effect on reducing the maximum amplitude and natural frequency, and the combination of the two can make the pipeline more stable. The research results of this paper can provide improved ideas for vibration reduction at the natural gas venting operation site.

Enhanced collision resolution and throughput analysis for the 802.11 distributed coordination function

SummaryThe IEEE 802 standards rely on the distributed coordination function (DCF) as the fundamental medium access control method. DCF uses the binary exponential backoff (BEB) algorithm to regulate channel access. The backoff time determined by BEB depends on a contention window (CW) whose size is doubled if a station suffers a collision and reset to its minimum value after a successful transmission. Doubling the size of CW reduces channel access time, which decreases the throughput. Resetting it to its minimum value harms fairness since the station will have a better chance of accessing the channel compared to stations that suffered a collision. We propose an algorithm that addresses collisions without instantly increasing the CW size. Our algorithm aims to reduce the collision probability without affecting the channel access time and delay. We present extensive simulations for fixed and mobile scenarios. The results show that, on average, our algorithm outperforms BEB in terms of throughput and fairness. Compared to exponential increase exponential decrease (EIED), our algorithm improves, on average, throughput and delay performance. We also propose analytical models for BEB, EIED and our algorithm. Our models extend Bianchi's popular Markov chain‐based model by using a collision probability that is dependent on the station transmission history. Our models provide a better estimation of the probability that a station transmits in a random slot time, which allows a more accurate throughput analysis. Using our models, we show that both the saturation throughput and maximum throughput of our algorithm are higher than those of BEB and EIED.

A new look on performance of small-cell network with design of multiple antennas and full-duplex

A downlink of small-cell network is studied in this paper studies in term of outage performance. We benefit by design of multiple antennas at the base station and fullduplex transmission mode. The scenario of multiple surrounded small-cell networks is considered to look the impact of interference. We derive the closed-form expression of outage probability to show performance of mobile user. We investigate target rate is main factor affecting to outage performance. According to the considered system, simulation results indicate reasonable value of outage probability and throughput as well. Finally, Monte-Carlo simulation method is deployed to determine exactness of main results found in this article. Finally, the considered system can exhibit improved performance if controlling interference term.

Coordination of similar days and multi-objective posterior process to predict energy of transmission substation

Purpose This paper aims to present a hybrid model to mid-term forecast the load of transmission substations based on the knowledge of expert site and multi-objective posterior framework. The main important challenges in load forecasting are the different behavior of load in specific days. Regular days, holidays and special holidays, days after a holidays and days of load shifting are characterized by abnormal load profiles. The knowledge of these days is verified by expert operators in regional dispatching centers. Design/methodology/approach In this paper, a hybrid model for power prediction of transmission substations based on the combination of similar day selection and multi-objective posterior technique has been proposed. In the first step, the important data for prediction is provided. Posterior method is used in the second step for prediction that it is based on kernel functions. A multi-objective optimization has been formulated with three type of output accuracy measurement function that it is solved by non-dominated sorting genetic technique II (NSGT-II) method. TOPSIS way is used to find the best point of Pareto. Findings The presented method has been tested in four scenarios for three different transmission stations, and the test results have been compared. The presented results indicate that the presentation method has better results and is robust to different load characteristics, which can be used for better forecasting of different stations for better planning of repairs and network operation. Originality/value The main contributions of this paper can be categorized as follows: A hybrid model based on similar days selection and multi-objective framework posterior is presented. Similar day selection is done by expert site that the day type and days with scheduled repair are considered. Hyperparameters of posterior process are found by NSGT-II based on TOPSIS method.

Achieving arbitrary throughput-fairness trade-offs in the inter cell interference coordination with fixed transmit power problem

We study the problem of inter cell interference coordination (ICIC) with fixed transmit power in OFDMA-based cellular networks, in which each base station (BS) needs to decide as to which subchannel, if any, to allocate to each of its associated mobile stations (MS) for data transmission. In general, there exists a trade-off between the total throughput (sum of throughputs of all the MSs) and fairness under the allocations found by resource allocation schemes. We introduce the concept of \(\tau -\alpha -\)fairness by modifying the concept of \(\alpha -\)fairness, which was earlier proposed in the context of congestion control for packet-switched networks. The concept of \(\tau -\alpha -\)fairness allows us to achieve arbitrary trade-offs between total throughput and fairness by selecting an appropriate value of \(\alpha\) in \([0,\infty )\). We show that for every \(\alpha \in [0,\infty )\) and every \(\tau > 0\), the problem of finding a \(\tau -\alpha -\)fair allocation is NP-Complete. Further, we show that for every \(\alpha \in [0, \infty )\), there exist thresholds such that if the potential interference levels experienced by each MS on every subchannel are above the threshold values, then the problem can be optimally solved in polynomial time by reducing it to the bipartite graph matching problem. Also, we propose a simple, distributed subchannel allocation algorithm for the ICIC problem, which is flexible, requires a small amount of time to operate, and requires information exchange among only neighboring BSs. We investigate via simulations as to how the algorithm parameters should be selected so as to achieve any desired trade-off between the total throughput and fairness. Finally, we compare the performance of the proposed algorithm with those of the simulated annealing based and opportunistic subchannel allocation algorithms in terms of the total throughput, fairness index and computational complexity.

Defect Signal Detection of Station Process Pipelines Based on the BP Neural Network

In recent years, leakage, rupture, and perforation accidents in oil and gas pipelines caused by corrosion have increased significantly. Therefore, the online, nondestructive testing of oil and gas pipelines has become essential to maintain their structural integrity. Ultrasonic guided wave detection technology presents advantages, such as high detection efficiency and complete coverage of the pipeline body, which is conducive to popularization and application. This paper considered the natural gas transmission station as the research object, while ultrasonic guided wave technology was used for detection. Ultrasonic guided wave equipment was used to detect the field process pipeline and experimental pipeline, obtaining data samples of the defects and welds. Defects were automatically identified via data processing by combining the characteristic signal method and the BP neural network. The results indicated that the neural network displayed a recognition accuracy of 80.9% for the features and defects in the test samples. By combining the characteristic signal method and the BP neural network, the defect recognition technology can reduce the subjective influence of inspectors while improving recognition efficiency and accuracy.

Design of a Reduced BER Millimetre Waves Model using MIMO and OFDM Communication System

The motivation behind this paper is to present another technique for isolating remote correspondence, (for example, the 802.11a/b/g/n and cell UMTS MAC conventions) across numerous problematic correspondence joins (like Ethernet) utilizing milli meter waves MIMO correspondence. The object is to present the fitting equipment, programming, and framework design needed to give the premise to a remote framework (utilizing a 802.11a/b/g/n and cell conventions as a model) that can scale to help a huge number of clients at the same time (say in a huge place of business, super corporate retailer, and so forth) or in a little, however extremely thick correspondence RF area. Components of correspondence between a base station and a Mobile Station will be examined measurably to exhibit higher throughput, less crashes and lower bit mistake rates (BER) with the given transmission capacity characterized by the 802.11n remote detail (utilization of MIMO channels will be assessed). Another organization nodal worldview will be introduced. Elective connection layer correspondence strategies will be suggested and broke down for the impact on cell phones. The examination will depict how the calculations utilized by state machines executed on Mobile Stations and Wi-Fi customer gadgets will be impacted by new base station transmission conduct. New equipment plan strategies that can be utilized to improve this engineering just as equipment plan standards concerning the insignificant equipment practical squares needed to help such a framework configuration will be portrayed. Recreation plan and check reproduction procedures to demonstrate the plan will oblige a worthy degree of execution to meet the exacting planning as it identifies with this new framework engineering.

Particle swarm optimization assisted B-spline neural network based predistorter design to enable transmit precoding for nonlinear MIMO downlink

For the multiple-input multiple-output (MIMO) downlink employing high-order quadrature amplitude modulation signaling and with nonlinear high power amplifiers (HPAs) at base station transmitter, the existing precoding designs relying on the linear MIMO channel can no longer work. We propose an efficient and accurate predistorter design to enable transmit precoding for nonlinear MIMO downlink. Specifically, we obtain the closed-form least squares estimates of the nonlinear HPA’s amplitude and phase response using two B-spline neural networks during training. The estimated HPA’s phase response automatically yields the estimate of the predistorter’s phase response. Based on the B-spline neural network estimate of the HPA’s amplitude response, we construct a B-spline neural network model for the predistorter amplitude response, and we adopt a particle swarm optimization (PSO) algorithm to solve this highly nonlinear optimization problem. Using our accurate predistorter estimate to pre-compensate for the nonlinear distortions of the transmit HPAs, a standard full-digital transmit precoding design can readily be adopted to combat the MIMO channel interference. A simulation study is conducted to demonstrate the effectiveness of our proposed PSO assisted predistorter design.

Nonuniform SINR+Voronoi diagrams are effectively uniform

This paper concerns the behavior of an SINR diagram of wireless systems, composed of a set S of n stations embedded in Rd, when restricted to the corresponding Voronoi diagram imposed on S. The diagram obtained by restricting the SINR zones to their corresponding Voronoi cells is referred to hereafter as an SINR+Voronoi diagram.Uniform SINR diagrams, where all stations transmit with the same power, are simple and nicely structured, e.g., the station reception zones are convex and “fat”. In contrast, nonuniform SINR diagrams might be complex; the reception zones might be fractured and their boundaries might contain many singular points. In this paper, we establish the perhaps surprising fact that a nonuniform SINR+Voronoi diagram is topologically almost as nice as a uniform SINR diagram. In particular, it is convex and effectively5 fat. This holds for every power assignment, every path-loss parameter α and every dimension d≥1. The convexity property also holds for every SINR threshold β>0, and the effective fatness property holds for any β>1. These fundamental properties provide a theoretical justification to engineering practices basing zonal tessellations on the Voronoi diagram, and help to explain the soundness and efficacy of such practices.We also consider two algorithmic applications. The first concerns the Power Control with Voronoi Diagram (PCVD) problem, where given n stations embedded in some polygon P, it is required to find the power assignment that optimizes the SINR threshold of the transmission station si for any given reception point p∈P in its Voronoi cell ▪. The second application is approximate point location; we show that for SINR+Voronoi zones, this task can be solved considerably more efficiently than in the general non-uniform case.