Improve Network Reliability Research Articles

Multi-objective optimal power flow considering voltage stability index and emergency demand response program

In this paper, optimal power flow problem has been implemented and evaluated simultaneously with the emergency demand response program (EDRP), considering the economic and environmental aspects, as well as the voltage stability enhancement of power system. Moreover, employing DRPs is a way to control customers’ electric energy consumption and to improve network reliability. The EDRP is one of the various demand response programs that provides incentives for participants in the program to reduce their consumption during peak hours or shift to off-peak hours. In order to solve the multi-objective function and achieve optimal compromise, the multi-objective Non-Dominated Sorting Genetic Algorithm II was used in this study. The proposed model was implemented on a 30-bus IEEE system. The results show that the proposed model is very effective in reducing fuel costs, emission and improving voltage stability.

Analysis of asynchronous distributed multi-master parallel genetic algorithm optimization on CAN bus

Industrial optimization problems are usually difficult to solve due to complexity and high number of constraints. Evolutionary algorithms are a conventional method to solve these problems. However, many industrial applications are real-time or we need to find a feasible optima solution in a limited time. Parallel genetic algorithm is a method to utilize properties of the genetic algorithm and parallel processing and implementation of a fast evolutionary algorithm. Controller Area Network (CAN) protocol is widely used in various industries such as automotive, medical, aerospace. In this paper, we implement a multiple-population coarse-grained parallel genetic algorithm on CAN bus to improve speed and performance of the conventional genetic algorithm which is asynchronous distributed multi-master. Evaluation criteria such as speed up, efficiency, serial fraction and reliability are calculated for the proposed parallel processing which is used for optimization problem of five benchmark functions. And finally, this structure is compared with the master–slave model. The proposed structure is created conditions for improving network reliability with very low cost of communication.

Fault Prediction of Distribution Network Based on Support Vector Machine

With the increasing demand for reliability of distribution network in modern society, fault prediction plays an important role in operation, maintenance and reliability improvement of distribution network. In view of the fact that there are many factors affecting the distribution network fault and there are strong uncertainties, a fault prediction method based on support vector machine(SVM) is proposed in this paper. Firstly, the influencing factors of distribution network faults are analyzed. Then, the optimal input variables are obtained by feature selection of the relevant variables. Finally, based on the proposed fault classification method, SVM with particle swarm optimization(PSO) parameters are used to predict distribution network fault. The validity of the proposed method is verified by simulation experiments with actual data.

Relay Node Placement in Wireless Sensor Networks: From Theory to Practice

The increasingly wide utilization of Wireless Sensor Networks (WSNs) in industrial applications outstands the significance of the Delay Constrained Relay Node Placement (DCRNP) problem. Existing algorithms to the DCRNP problem are designed based on the ideal geometric disk wireless channel model, and no real-world deployments are performed to verify the effectiveness of these algorithms. However, the unreliable and unpredictable wireless links in WSNs may lead these algorithms to fail in practice. Therefore, we first conduct extensive real-world deployments under the guidance of existing algorithms to evaluate their performance and to gain some insights for designing practical deployment algorithms. The results exhibit that the WSNs built by existing algorithms have a favorable performance in end-to-end delay but a poor performance in reliability, which is mainly due to the lack of methods ensuring high-quality links. To this end, we first devise a Set-Covering-based Algorithm (SCA) which figures out the DCRNP problem while ensuring the quality of each link better than a given threshold. As our experiments also show that the fault-tolerant topology can significantly improve network reliability, we then design a $k$ k -Set-Covering-based Algorithm ( $k$ k SCA) to build fault-tolerant WSNs based on the methodology of SCA. Furthermore, the elaborate analysis proves that both SCA and $k$ k SCA are polynomial-time algorithms, and their approximation ratios are both O( $\ln n$ ln n ), where $n$ n is the number of sensor nodes. Finally, extensive experiments are performed under the guidance of SCA and $k$ k SCA to demonstrate the effectiveness of these two algorithms.

Adaptive and Fault-Tolerant Data Processing in Healthcare IoT Based on Fog Computing

In recent years, healthcare IoT have been helpful in mitigating pressures of hospital and medical resources caused by aging population to a large extent. As a safety-critical system, the rapid response from the health care system is extremely important. To fulfill the low latency requirement, fog computing is a competitive solution by deploying healthcare IoT devices on the edge of clouds. However, these fog devices generate huge amount of sensor data. Designing a specific framework for fog devices to ensure reliable data transmission and rapid data processing becomes a topic of utmost significance. In this paper, a Reduced Variable Neighborhood Search (RVNS)-based sEnsor Data Processing Framework (REDPF) is proposed to enhance reliability of data transmission and processing speed. Functionalities of REDPF include fault-tolerant data transmission, self-adaptive filtering and data-load-reduction processing. Specifically, a reliable transmission mechanism, managed by a self-adaptive filter, will recollect lost or inaccurate data automatically. Then, a new scheme is designed to evaluate the health status of the elderly people. Through extensive simulations, we show that our proposed scheme improves network reliability, and provides a faster processing speed.

Characteristic Analysis of Various Importance Indices for Effective Highway Network Reliability Improvement

Characteristic Analysis of Various Importance Indices for Effective Highway Network Reliability Improvement

Adaptive Coding and Modulation for Robust Optical Access Networks

We introduce adaptive coding and modulation (ACM) to direct-detection passive optical networks (PONs) operating beyond 10 Gb/s per wavelength to allow each user to transmit at the highest possible bit rate and improve network reliability. Current fixed-rate PONs must allocate significant power margin to ensure reliable long-term operation over channels that vary over time and between users. Introducing adaptive-rate transceivers with ACM is a promising low-cost solution to increasing the overall capacity of optical access networks. The proposed ACM scheme uses two-, three-, or four-level pulse-amplitude modulation (2-, 3-, or 4-PAM) at a fixed symbol rate with direct detection and low-density parity check (LDPC) codes derived from a mother code by shortening and puncturing, decoded using fixed-initialization normalized min-sum decoding. The scheme supports received optical powers spanning a 10-dB range at bit rates of 20–54 Gb/s. In a PON with 64 users transmitting at a symbol rate of 30 Gbaud and a maximum transmission distance of 25 km, the ACM scheme demonstrates more than 3 dB improvement in overall optical power budget. For a fixed margin, ACM can increase throughput up to 60% compared to fixed-rate transmission, from 25 Gb/s to 39.7 Gb/s, or from 37.5 Gb/s to over 50 Gb/s, depending on the received optical power.

Enhanced Underwater Balanced Co-operative Routing Protocol

Underwater wireless sensor networks (UWSNs) is an developing area for research in the wireless sensor networks (WSN) area. The normal method is to adapt for underwater use presently accessible terrestrial architectures and well-proven architectures. Underwater Wireless Sensor Networks (UWSNs) have drawn a lot of concentration to help multiple applications such as tracking pollution, tsunami warnings, offshore exploration, tactical tracking, etc. For many applications, the efficiency and reliability of the network in terms of high performance, energy conservation, low bit error rate (BER) and reduced delay are prerequisites. However, UWSN's unique characteristics such as low bandwidth available, big delay in propagation, extremely vibrant network topology, and high probability of error pose many difficulties in the development of effective and reliable communication protocols. Therefore, in this proposed work, along with its mathematical model, we suggest a protocol that focuses on improving network reliability and effectiveness through cooperative routing and sink mobility. For reliable data transmission, cooperative transmission is well known. Based on their residual energy data and depth , prospective relay and target nodes for cooperative routing are chosen in this algorithm. Data from the source node is transferred in a cooperative way to the target node via the relay node. Mobile Sinks collect information straight from the nodes of the location. We consider as selection parameters the depth threshold of the source node, the residual energy of the destination nodes/ potential relay and the SNR of the relating source node to the potential relay / destination node. In this work, two distinct selection criteria for partner nodes are also introduced and contrasted. Partner node selection (relay / destination node) for cooperative routing should be carried out on the grounds of a certain criterion in order to achieve efficient outcomes. Based on the extensive simulations carried out in MATLAB, we note that our suggested method increases performance in terms of energy efficiency, network life and decreases BER relative to the existing depth-based routing protocols.

Optimal design of solar–wind hybrid system-connected to the network with cost-saving approach and improved network reliability index

In this paper, the optimal design of a grid-connected the hybrid energy system for a sample area in the north Iran is studied. A new innovative cost-based objective function is proposed which is combination of life cycle cost and reliability cost. Also, loss of power supply probability (LPSP) criteria, is considered as constraint for ensuring at the same time certain level of system reliability. Designing process is implemented in such a way that the total cost of the system reaches its minimum. For this purpose, a modified version of Bee algorithm has been proposed to achieve this goal. In order to carry out studies, the actual sample system, whose data has been available, has been studied. The results indicate the good performance of proposed hybrid system to reduce system cost.

Dual-Hop TDA-MAC and Routing for Underwater Acoustic Sensor Networks

This article investigates the application of underwater acoustic sensor networks (UASNs) for large scale monitoring of the ocean environment. The low propagation speed of acoustic waves presents a fundamental challenge for medium access control (MAC)—coordinating the access of multiple nodes to the shared acoustic communication medium. In this article, we propose sequential dual-hop transmit delay allocation MAC (SDH-TDA-MAC)—a centralized MAC and routing protocol that facilitates efficient dual-hop scheduling in UASNs without the need for clock synchronization among the sensor nodes. BELLHOP-based simulations of a 100 node network reveal that SDH-TDA-MAC can achieve full network connectivity with 16-dB lower transmit power, compared with the single-hop TDA-MAC protocol. This provides considerable energy savings, while still providing network goodput in excess of 50% of the channel capacity. We also present a method of incorporating routing redundancy into the SDH-TDA-MAC protocol that achieves a good tradeoff between the network throughput and reliability. For example, in a channel with 10% probability of link outage, incorporating double routing redundancy into SDH-TDA-MAC increases the packet delivery ratio from 81% to 95%, a significant improvement in network reliability, while still achieving the network goodput of 22% of the channel capacity, considerably higher than typical MAC protocols designed for UASNs. In summary, the high network goodput, low transmit power compared with the single-hop approach, no requirement for clock synchronization, and robust packet delivery via route diversity make SDH-TDA-MAC an efficient, reliable, and practical approach to data gathering in UASNs.

Co‐optimising distribution network adequacy and security by simultaneous utilisation of network reconfiguration and distributed energy resources

With the evolution of smart grids, penetration of distributed energy resources (DERs) in the distribution networks has become ever-increasing problem. To improve network reliability, the complexity of the two important aspects of adequacy and security must be well assessed. There is a trade-off between adequacy of DERs, and the distribution network security, i.e. improving the adequacy can reduce the security. In this study, enhancement of the distribution network adequacy and security is proposed. In this regard, capacity of simultaneous reconfiguration and DERs sizing are utilised to improve the adequacy and security of an active distribution network. In the reconfiguration process, graph theory concept is adopted to implement a fast reconfiguration method. Since DERs are active, a combined bus and line security index is used to overcome security concerns of their existence. The IEEE 33-bus distribution network as a widely used standard test system in reconfiguration studies, and a practical 83-bus distribution network of Taiwan Power Company (TPC) which is a part of a real distribution network, are used to test the performance of the proposed method. The simulation results demonstrate the performance of the proposed framework.

Reliability Assessment of Distribution Networks with Optimal Coordination of Distributed Generation, Energy Storage and Demand Management

Modern power distribution networks assume the connection of Distributed Generators (DGs) and energy storage systems as well as the application of advanced demand management techniques. After a network fault these technologies and techniques can contribute individually to the supply restoration of the interrupted areas and help improve the network reliability. However, the optimal coordination of control actions between these resources will lead to their most efficient use, maximizing the network reliability improvement. Until now, the effect of such networks with optimal coordination has not been considered in reliability studies. In this paper, DGs, energy storage and demand management techniques are jointly modelled and evaluated for reliability assessment. A novel methodology is proposed for the calculation of the reliability indices. It evaluates the optimal coordination of energy storage and demand management in order to reduce the energy-not-supplied during outages. The formulation proposed for the calculation of the reliability indices (including the modelling of optimal coordination) is described in detail. The methodology is applied to two distribution systems combining DGs, energy storage and demand management. Results demonstrate the capability of the proposed method to assess the reliability of such type of networks and emphasise the impact of the optimal coordination on reliability.

Optimal placement of data concentrators for expansion of the smart grid communications network

Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high-performing, reliable, and resilient power system. Three network design formulations based on mixed-integer linear and non-linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much-improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality-of-service in the event of an outage. Analysis of multi-period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.

Reliability-aware ring protection link selection in Ethernet ring mesh networks

Ring topology is an appropriate solution to be applied on the carrier Ethernet networks due to its high switching speed when one of the links fails. Meanwhile, the ITU-T G.8032 Ethernet ring protection (ERP) recommendation was developed to compete with the switching speed of synchronous digital hierarchy (SDH)/synchronous optical networking (SONET) rings. Nevertheless, ERP has emerged some new optimization issues that the most important of which is to find the ring protection link (RPL). In addition, this issue should also satisfy the network reliability requirements as a key performance parameter. To cope with this problem, in this paper, a new approach is proposed. The main idea behind the proposed approach is to analyze the impact of network links on the overall network reliability. In this regard, the proposed approach consists of five steps: (1) computing the reliability equation for the network through the spanning tree set method, (2) calculating the reliability importance for each link through the Birnbaum importance measure, (3) sorting links based on reliability importance by investigating numerical results, (4) selecting the most appropriate links as RPL per ring by taking into account two modes of working and protection, and finally (5) choosing a ring hierarchy based on the selected RPLs. Performance evaluations demonstrate that the proposed approach provides significant improvement in network reliability compared to the representative approaches.

Optimal fuzzy switch placement to increase automation level of electric distribution network considering asset management principles

Since distribution sector is inherent into high amount of failures, distribution companies (DISCOs) are responsible of attaining an acceptable value for the reliability indices and otherwise they will face up to complaints. So they are usually obligated by regulators to invest on reliability improvement of network. But this investment on reliability is usually from the DISCO’s viewpoint and is also irrespective of customer satisfaction level. In other words, customers are not at the same level of sensitivity to interruptions but DISCO improves the reliability of network without considering the differences in importance degree of loads and their level of reliability requirement. On the other hand DISCOs attempt to reduce their investment costs as much as possible. This paper introduces a novel approach in the field of joint switch placement that can reduce the switch cost from the perspective of asset management policies. To this end, two switch placement plannings in different types of strategies are performed to compare their results. Firstly as witch placement is performed based on reducing the total energy not supplied (ENS) of the system. Then by revising the strategy, a fuzzy switch placement is performed from the DISCO’s point of view which just considers the total ENS of load points most sensitive to interruptions known as important or critical loads. Furthermore, by meeting the related constraints, the reliability of low sensitive customers is disregarded. This is a load importance based planning which can result in switch cost reduction relative to the amount achieved in previous strategy and implies the management of risks associated with reliability and respective constraint. Fuzzy method and new switching mechanism in fuzzy environment of network are implemented to modeling and controlling the risks associated to ENS of critical loads and also the ENS of system.

A new on-line technique to identify fault location within long transmission lines

Identification of fault location within transmission lines is essential in order to restore service rapidly, reduce unplanned outage time, minimise revenue loss, and improve network reliability. Several transmission line fault-locating techniques based on travelling waves, apparent impedance and direct circuit analysis have been introduced in the literatures. However, these methods are either impractical or too expensive to implement. In this paper, a new online technique is introduced to accurately detect the fault location within transmission lines. The technique relies on constructing a voltage-current (V-I) locus diagram that could be measured at every power frequency cycle to provide up-to-date condition state of the line. The technique does not call for special equipment as it utilises the existing metering or protection devices connected to the sending and receiving ends of the transmission line to monitor the voltage and current at both ends. To assess the robustness of the proposed technique, various types of faults have been simulated on transmission lines of various lengths and voltage levels using DIgSILENT PowerFactory software. Variations in load conditions, effect of fault resistance, different line configurations are also investigated. Results reveal the ability of the proposed technique to detect fault locations in transmission lines with high accuracy. In contrary with existing fault-locating techniques that are only employed to identify the location of faults after their occurrence, the proposed technique has the potential to detect high impedance faults. Thus an early warning signal can be issued to avoid any catastrophic consequences. The proposed technique is cost effective and easy to implement for new and existing transmission line installations.

TOSG: A Topology Optimization Scheme With Global Small World for Industrial Heterogeneous Internet of Things

In Industrial Internet of Things (IIoT), sensor nodes are vulnerable to withstand node failures due to energy exhaustion or external attacks, which leads to the low connectivity of networks. In this situation, how to improve network reliability has became a crucial problem. Adding a small amount of shortcuts to build a small world model in IIoT not only can reduce the delay, but also increases the reliability of networks. In this paper, we propose a Topology Optimization Scheme with Global Small World (TOSG) based on ant colony for IIoT. First, according to the number of appearing on the all shortest paths obtained by the ant colony optimization algorithm, we give the definition of importance for each node. The node with the highest importance in the communication range of a node is defined as an important node. We can find the important nodes in the network topology so that some shortcuts can be created between them to build a global small world model. The experiment results show that the TOSG model has a smaller average shortest path length and higher reliability compared with Greedy Model with Small World properties and Directed Angulation toward the Sink Node Model.

Utilizing Demand Response to Improve Network Reliability and Ageing Resilience

Increasing operation flexibility and resilience at uncertainties is an everlasting challenge for existing power networks. Emergency loadings and probabilistic thermal ratings are traditionally deployed on overhead lines (OHLs) to provide network operators with such flexibility. The challenge is to quantify the impact of these operating practices on the OHL conductor ageing risks, but only a few investigations exist on potential solutions to enhance flexibility whilst minimizing ageing risks by employing demand response. This paper presents a probabilistic modeling approach that uses a two-objective optimization function to minimize network's OHLs ageing and maximize its reliability at uncertainties by utilizing the available demand response at emergencies. Hence, the proposed optimization provides the operator with the flexibility to tradeoff between ageing and reliability costs against demand response costs. A predefined expected equivalent network ageing index is formulated to relate component ageing with available network demand response. The study of the proposed framework on the 24-bus IEEE-RTS resulted in more than 30% reduction of the network's expected energy not supplied and interruption costs, whilst halving the overall network ageing. Demand response, thus, can have a significant impact on reducing ageing and maintenance costs at critical lines.

Overhead lines Dynamic Line rating based on probabilistic day-ahead forecasting and risk assessment

Dynamic Line Rating is a technology devised to modify an overhead line’s current-carrying capacity based on weather observation. The benefits of this modification may include reduced congestion costs, an increased renewable energy penetration rate, and improved network reliability. DLR is already well developed, but few papers in the literature investigate DLR day-ahead forecasting. The latter is central to DLR development since many of the decisions related to grid management are taken at least on a day-ahead basis. In this paper, two problems related to DLR forecasts are dealt with: how to achieve precise, reliable calculations of day-ahead forecasts of overhead line ampacity and how to define a methodology to calculate safe rating values using these forecasts. On the first point, four machine-learning algorithms were evaluated, identifying the best approach for this problem and quantifying the potential performance. On the second point, the developed methodology was tested and compared to the current static line rating approach.

Perancangan dan Analisa Implementasi LTE Home pada Jaringan 4G LTE di Frekuensi 2300 Mhz

Design and analysis of lte home implementation on 4g lte networks in 2300mhz frequency . The demand for data connections for customers is currently increasing. FTTx as one of the Fix broadband technology (FBB) has several weaknesses, especially when applied to rural areas. LTE Home as a smart home technology is a form of WTTx 4G LTE technology service that is expected to be able to meet the data needs of customers. This study aims to design and analyze the implementation of LTE home by measuring the value of QoS Class Identifier (QCI) and the value of Radio Frequency Key Performance Indicator (RF KPI) to improve network reliability for voice and data communication services. Some parameters measured are packet loss, delay, jitter, throughput for QCI values and Radio Signal Received Power (RSRP) and Radio Signal Received Quality (RSRQ) for RF KPI values.The results of RF KPI Measurement show that the value for RSRP is -89dBm. This value is quite good because it matches the predetermined KPI standard, which is between -70 to -90 dBm. For RSRQ values obtained for -11dBM, this result is classified as good according to the KPI standard which is <-8 dBm. These results indicate that the quality of 4GLTE network services provided for LTE Home implementation services has met RF KPI standard values. Whereas for the QCI parameters obtained results that both voice call and video streaming, the value still meets the standard Good for the User Experience KPI (QCI) value that is packet loss <5%, delay <150 ms and jitter <75 ms Key w ord s: LTE home, RF KPI. QCI, RSRP, RSCP,packet loss, jitter