scholarly journals Real Fault Location in a Distribution Network Using Smart Feeder Meter Data

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3242
Author(s):  
Hamid Mirshekali ◽  
Rahman Dashti ◽  
Karsten Handrup ◽  
Hamid Reza Shaker
Keyword(s):  
Fault Location ◽  
Network Reliability ◽  
Distribution Network ◽  
Estimation Method ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Active Power ◽  
Financial Loss ◽  
Smart Meters ◽  
The Real

Distribution networks transmit electrical energy from an upstream network to customers. Undesirable circumstances such as faults in the distribution networks can cause hazardous conditions, equipment failure, and power outages. Therefore, to avoid financial loss, to maintain customer satisfaction, and network reliability, it is vital to restore the network as fast as possible. In this paper, a new fault location (FL) algorithm that uses the recorded data of smart meters (SMs) and smart feeder meters (SFMs) to locate the actual point of fault, is introduced. The method does not require high-resolution measurements, which is among the main advantages of the method. An impedance-based technique is utilized to detect all possible FL candidates in the distribution network. After the fault occurrence, the protection relay sends a signal to all SFMs, to collect the recorded active power of all connected lines after the fault. The higher value of active power represents the real faulty section due to the high-fault current. The effectiveness of the proposed method was investigated on an IEEE 11-node test feeder in MATLAB SIMULINK 2020b, under several situations, such as different fault resistances, distances, inception angles, and types. In some cases, the algorithm found two or three candidates for FL. In these cases, the section estimation helped to identify the real fault among all candidates. Section estimation method performs well for all simulated cases. The results showed that the proposed method was accurate and was able to precisely detect the real faulty section. To experimentally evaluate the proposed method’s powerfulness, a laboratory test and its simulation were carried out. The algorithm was precisely able to distinguish the real faulty section among all candidates in the experiment. The results revealed the robustness and effectiveness of the proposed method.

scholarly journals Smart meters as a key component of modern measuring infrastructure providing observability and state estimation of low-voltage distribution networks

2018 ◽  
Vol 69 ◽  
pp. 02012
Author(s):  
Yana Kuzkina ◽  
Irina Golub
Keyword(s):  
State Estimation ◽  
Low Voltage ◽  
Distribution Network ◽  
Distribution Networks ◽  
The State ◽  
Voltage Distribution ◽  
Smart Meters ◽  
The Real ◽  
Real Distribution

The paper presents a solution to the problem of organization of a system for collecting and transmitting information about measurements from smart meters necessary for the state estimation of a low-voltage distribution network. The problems of providing the sufficiency of measurements for the observability of the network and the influence of errors in the information about load connection to phases on the quality of the observability are considered. The results of allocation of smart meters and the state estimation of the real distribution network are given.

scholarly journals Detecting the Fault Section in the Distribution Network with Distributed Generators Based on Optimal Placement of Smart Meters

2019 ◽  
Vol 19 (2) ◽  
pp. 28-34 ◽  
Author(s):  
Majid Dashtdar ◽  
Masoud Dashtdar
Keyword(s):  
Fault Location ◽  
Voltage Drop ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimal Number ◽  
Optimal Placement ◽  
Voltage Distribution ◽  
Smart Meters ◽  
Good Efficiency ◽  
Medium Voltage

AbstractOne of the most important issues in employing distribution networks is detecting the fault location in medium-voltage distribution feeders. Due to the vastness of distribution networks and growing distributed generation (DG) sources in this network, detection is difficult with the common methods. The aim of this paper is to present a method based on voltage distributed meters in a medium-voltage distribution network (by smart meters installed along the feeder) in order to detect the fault location in the presence of DG sources. Due to vastness of distribution network and cost of installing smart meters, it is not economically possible to install meters in all the Buses of the network. That’s why in this article, combination of genetic and locating algorithms and fault-based on voltage drop has been used to suggest a method to optimize the meter locations. In order to evaluate the efficiency of the method suggested, first we determine the optimal number and location of the meters and then we apply the fault that has been simulated in different Buses of the sample network, using PSCAD/EMTDC software. After results analysis, the fault location is estimated by MATLAB. Simulation results show that the fault locating method by optimal number of meters has good efficiency and accuracy in detecting faults in different spots and in different resistance ranges.

scholarly journals Home Energy Management Strategy-Based Meta-Heuristic Optimization for Electrical Energy Cost Minimization Considering TOU Tariffs

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 537
Author(s):  
Rittichai Liemthong ◽  
Chitchai Srithapon ◽  
Prasanta K. Ghosh ◽  
Rongrit Chatthaworn
Keyword(s):  
Energy Management ◽  
Energy Cost ◽  
Management Strategy ◽  
Cost Minimization ◽  
Distribution Network ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Heuristic Optimization ◽  
Energy Management Strategy ◽  
Home Energy Management

It is well documented that both solar photovoltaic (PV) systems and electric vehicles (EVs) positively impact the global environment. However, the integration of high PV resources into distribution networks creates new challenges because of the uncertainty of PV power generation. Additionally, high power consumption during many EV charging operations at a certain time of the day can be stressful for the distribution network. Stresses on the distribution network influence higher electricity tariffs, which negatively impact consumers. Therefore, a home energy management system is one of the solutions to control electricity consumption to reduce electrical energy costs. In this paper, a meta-heuristic-based optimization of a home energy management strategy is presented with the goal of electrical energy cost minimization for the consumer under the time-of-use (TOU) tariffs. The proposed strategy manages the operations of the plug-in electric vehicle (PEV) and the energy storage system (ESS) charging and discharging in a home. The meta-heuristic optimization, namely a genetic algorithm (GA), was applied to the home energy management strategy for minimizing the daily electrical energy cost for the consumer through optimal scheduling of ESS and PEV operations. To confirm the effectiveness of the proposed methodology, the load profile of a household in Udonthani, Thailand, and the TOU tariffs of the provincial electricity authority (PEA) of Thailand were applied in the simulation. The simulation results show that the proposed strategy with GA optimization provides the minimum daily or net electrical energy cost for the consumer. The daily electrical energy cost for the consumer is equal to 0.3847 USD when the methodology without GA optimization is used, whereas the electrical energy cost is equal to 0.3577 USD when the proposed methodology with GA optimization is used. Therefore, the proposed optimal home energy management strategy with GA optimization can decrease the daily electrical energy cost for the consumer up to 7.0185% compared to the electrical energy cost obtained from the methodology without GA optimization.

scholarly journals Factors Affecting the Design and Economic Operation of Distribution Networks and Its Investigation in the 0.4 KV Distribution Network of Ghazni City

2021 ◽  
Vol 3 (27) ◽  
pp. 101-115
Author(s):  
Massoud Danishmal ◽  
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Network Reliability ◽  
Distribution Network ◽  
Distribution Networks ◽  
Electricity Demand ◽  
Power Distribution Systems ◽  
Factors Affecting ◽  
Economic Operation ◽  
Selection Of

The design of power distribution systems should be such that it can technically respond to the increase in electricity demand properly and economically, optimally designed and high network reliability. In order to respond to the increase in electricity demand, load forecasting must be done so that in addition to providing the electricity needed by customers, expansion of power generation centers, expansion of substations, expansion of transformer stations and selection of their appropriate location can be done optimally. In this article, we first examine the definitions and factors that are technically and economically effective in the economic design of energy distribution systems. And in the next stage, we will see whether these above-mentioned effective factors are considered in the 0.4 kV distribution network of Ghazni city or not.

scholarly journals Online Estimation of Short-Circuit Fault Level in Active Distribution Network

2020 ◽  
Vol 10 (11) ◽  
pp. 3812
Author(s):  
Xiaohui Wang ◽  
Peng Wang ◽  
Yunbo Wang ◽  
Fang Shi
Keyword(s):  
Equivalent Circuit ◽  
Short Circuit ◽  
Distribution Network ◽  
Estimation Method ◽  
Short Circuit Current ◽  
Distribution Networks ◽  
Measurement Unit ◽  
Online Estimation ◽  
Active Distribution Network ◽  
Short Circuit Fault

The potential short-circuit current in active distribution network features time-variance with the increasing distributed generations. This feature makes the online estimation of fault level necessary. In this paper, a novel online estimation method is proposed to be implemented by either phasor measurement unit (PMU) or the measurements from protection relays. The equivalent circuit of the radial distribution network with distributed generators (DGs), e.g., wind turbines and photovoltaic cells, is derived with necessary simplifications. The natural disturbances downstream are used to evaluate the parameters of the equivalent circuit so that the potential fault level can be estimated in advance of the actual fault occurrence. A fuzzy logic identifier is presented to rank the confidence of the measurements incurred by the disturbance and to distinguish the qualified disturbance to launch the estimation. The mechanism based on multi-measurements and confidence indices was applied, to improve the accuracy. A typical distribution network in the United Kingdom (UK) with DGs was taken, as an example, to validate the proposed method under various load fluctuation. The results confirm the effectiveness of the proposed method, which is suitable for online estimation of short-circuit fault level in active distribution networks.

A Practical GIS-Based Reliability Estimation System for Large Scale Distribution Network

2012 ◽  
Vol 433-440 ◽  
pp. 1802-1810 ◽  
Author(s):  
Lin Guan ◽  
Hao Hao Wang ◽  
Sheng Min Qiu
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Network Reliability ◽  
Distribution Network ◽  
Reliability Assessment ◽  
Distribution Networks ◽  
Reliability Estimation ◽  
Assessment Model ◽  
Estimation System ◽  
The Impact

A new algorithm as well as the software design for large-scale distribution network reliability assessment is proposed in this paper. The algorithm, based on fault traversal algorithm, obtains network information from the GIS. The structure of distribution network data storage formats is described, facilitating automatic output of the feeders’ topological and corresponding information from the GIS. Also the judgment of load transfer is discussed and the method for reliability assessment introduced in this paper. Moreover, The impact of the scheduled outage is taken into account in the assessment model, making the results more in accordance with the actual situation. Test Cases show that the proposed method features good accuracy and effectiveness when applied to the reliability assessment of large-scale distribution networks.

scholarly journals New Evolutionary Technique for Optimization Shunt Capacitors in Distribution Networks

2011 ◽  
Vol 62 (3) ◽  
pp. 163-167 ◽  
Author(s):  
Ali Elmaouhab ◽  
Mohamed Boudour ◽  
Rabah Gueddouche
Keyword(s):  
Radial Distribution ◽  
Annual Cost ◽  
Distribution Network ◽  
Distribution Networks ◽  
Active Power ◽  
Power Losses ◽  
Evolutionary Technique ◽  
Active Power Losses ◽  
Shunt Capacitors

New Evolutionary Technique for Optimization Shunt Capacitors in Distribution NetworksThe paper presents a new evolutionary technique for optimizing on one part the numbers, the sizes and locations of shunt capacitors in radial distribution network in away to minimize the annual cost of active power losses with the improvement of voltage profiles of different buses. The technique is applied on 10 buses network and on IEEE 34 buses network test. The results are compared with ones of previous studies using heuristiques methods and the same network tests.

scholarly journals MACHINE LEARNING AND IOT FOR SMART GRID

2020 ◽  
Vol XLIV-4/W3-2020 ◽  
pp. 233-240
Author(s):  
M. Fouad ◽  
R. Mali ◽  
A. Lmouatassime ◽  
M. Bousmah
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Smart Grid ◽  
Power Distribution ◽  
Short Term Memory ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Smart Meters ◽  
Power Distribution Networks ◽  
Electricity Grid

Abstract. The current electricity grid is no longer an efficient solution due to increasing user demand for electricity, old infrastructure and reliability issues requires a transformation to a better grid which is called Smart Grid (SG). Also, sensor networks and Internet of Things (IoT) have facilitated the evolution of traditional electric power distribution networks to new SG, these networks are a modern electricity grid infrastructure with increased efficiency and reliability with automated control, high power converters, modern communication infrastructure, sensing and measurement technologies and modern energy management techniques based on optimization of demand, energy and availability network. With all these elements, harnessing the science of Artificial Intelligence (AI) and Machine Learning (ML) methods become better used than before for prediction of energy consumption. In this work we present the SG with their architecture, the IoT with the component architecture and the Smart Meters (SM) which play a relevant role for the collection of information of electrical energy in real time, then we treat the most widely used ML methods for predicting electrical energy in buildings. Then we clarify the relationship and interaction between the different SG, IoT and ML elements through the design of a simple to understand model, composed of layers that are grouped into entities interacting with links. In this article we calculate a case of prediction of the electrical energy consumption of a real Dataset with the two methods Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM), given their precision performances.

scholarly journals Real-Time Dynamic Behavior Evaluation of Active Distribution Networks Leveraging Low-Cost PMUs

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4999
Author(s):  
Xuejun Zheng ◽  
Shaorong Wang ◽  
Xin Su ◽  
Mengmeng Xiao ◽  
Zia Ullah ◽  
...  
Keyword(s):  
Real Time ◽  
Dynamic Behavior ◽  
Low Cost ◽  
Distribution Network ◽  
Distribution Networks ◽  
Assessment Model ◽  
The Real ◽  
Time Dynamic ◽  
Dynamic Index ◽  
Active Distribution Networks

The investigation of real-time dynamic behavior evaluation in the active distribution networks (ADNs) is a challenging task, and it has great importance due to the emerging trend of distributed generations, electric vehicles, and flexible loads integration. The advent of new elements influences the dynamic behavior of the electric distribution networks and increases the assessment complexity. However, the proper implementation of low-cost phasor measurement units (PMUs) together with the development of power system applications offer tremendous benefits. Therefore, this paper proposes a PMU-based multi-dimensional dynamic index approach for real-time dynamic behavior evaluation of ADNs. The proposed evaluation model follows the assessment principles of accuracy, integrity, practicability, and adaptability. Additionally, we introduced low-cost PMUs in the assessment model and implemented them for real-time and high-precision monitoring of dynamic behaviors in the entire distribution network. Finally, a complete model called the real-time dynamic characteristics evaluation system is presented and applied to the ADN. It is pertinent to mention that our proposed evaluation methodology does not rely on the network topology or line parameters of the distribution network since only the phasor measurements of node voltage and line current are involved in the dynamic index system. Thus, the presented methodology is well adaptive to different operation states of ADN despite frequent topology changes. The validation of the proposed approach was verified by conducting simulations on the modified IEEE 123-node distribution network. The obtained results verify the effectiveness and relevance of the proposed model for the real-time dynamic behavior evaluation of ADNs.

scholarly journals Impacts of Placement of Wind Turbine Generators with Different Interfacing Technologies on Radial Distribution Feeder Fuse-Fuse Protection Coordination Scheme.

2019 ◽  
Vol 4 (10) ◽  
pp. 59-77
Author(s):  
Kemei Peter Kirui ◽  
David K. Murage ◽  
Peter K. Kihato
Keyword(s):  
Wind Turbine ◽  
Short Circuit ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Short Circuit Current ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Coordination Scheme

The ever increasing demand on the electrical energy has led to the diversification on the electrical energy generation technologies especially from the renewable energy sources like the wind and the solar PV. Micro-grids powered by distributed generators utilizing renewable energy sources are on the increase across the globe due to the natural abundance of the resources, the favorable government policies and the resources being environmentally friendly. However, since the electrical power distribution networks have always been passive networks, the connection of the distributed generations (DGs) into the network has associated several technical implications with distribution network protection and Over-Current Protective Devices (OCPDs) miss-coordination being one of the major issues. The need for a detailed assessment of the impacts of the wind turbine generation (WTGs) on the distribution networks operations has become critical. The penetration of the WTGs into a distribution network has great impacts on the short circuit current levels of the distribution network hence eventually affecting the OCPDs coordination time margins. The factors which contribute to these impacts are: The size of the WTG penetrating the distribution network, the location at which the WTG is connected on to the network and the Type of the WTG interfacing technology used. An important aspect of the WTGs impacts studies is to evaluate their short circuit current contribution into the distribution network under different fault conditions. The magnitudes of these short circuit currents, both the three phase and the single-line-to-ground (SLG) faults, are needed for sizing the various Over-Current Protective Devices (OCPDs) utilized in protecting the distribution network. The sizing of the OCPDs entails among other procedures coordinating them with both the upstream and the downstream OCPDs so that there is sufficient time margin between their Time Current Characteristic (TCC) curves. For Fuse-Fuse protection coordination, the ANSI/NEC rules stipulate that a minimum of 0.025seconds or more time margin should be maintained between the primary/downstream fuse and the secondary/upstream/back-up fuse. Due to the topological and operational differences between the different types of WTGs interfacing technologies, the electrical generators design industry has divided wind turbine generators into four different types labeled as Type I, Type II, Type III and Type IV. This paper presents a detailed study of the impacts brought upon by integrating wind turbine generators on a conventional Fuse-Fuse protection coordination scheme. A conventional Fuse-Fuse protection coordination scheme was modeled in Electrical Transients Analysis Program (ETAP) software and WTG with different interfacing technologies connected. A study of the impacts brought by the integration of the WTGs on Fuse-Fuse Miss-coordination was performed. IEEE 13 Node Radial Distribution Test Feeder was used for the study.

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