scholarly journals State Characteristic Clustering for Nonintrusive Load Monitoring with Stochastic Behaviours in Smart Grids

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ruotian Yao ◽  
Hong Zhou ◽  
Dongguo Zhou ◽  
Heng Zhang
Keyword(s):  
Smart Grids ◽  
Mean Shift ◽  
Stable State ◽  
Limited Information ◽  
State Characteristic ◽  
Stable States ◽  
Smart Meters ◽  
Characteristic Space ◽  
Time Series Dataset ◽  
Load Monitoring

Integrating the nonintrusive load monitoring (NILM) technology into smart meters poses challenges in demand-side management (DSM) of the smart grid when capturing detailed power information and stochastic consumption behaviours, due to the difficulties in accurately detecting load operation states in real household environments with the limited information available. In this paper, a state characteristic clustering (SCC) approach is presented for promoting the performance of event detection in NILM, which makes full use of multidimensional characteristic information. After identifying different types of state domains in an established multidimensional characteristic space, we design a sliding window difference search method (SWDS) to extract their initial clustering centre. Meanwhile, the mean-shift updating and iterating procedures are conducted to find the potential terminal stable state according to the probability density function. The above control strategy considers the transient events and stable states in a time-series dataset simultaneously, which thus allows the exact state of complex events to be obtained in a fluctuating environment. Moreover, a multisegment computing scheme is applied for fast computing in the state characteristic clustering process. Experiments of three different cases on both our real household dataset and REDD public dataset are provided to reveal the higher performance of the proposed SCC approach over the existing related methods.

scholarly journals Evaluation of a LoRa Mesh Network for Smart Metering in Rural Locations

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 751
Author(s):  
Anup Marahatta ◽  
Yaju Rajbhandari ◽  
Ashish Shrestha ◽  
Ajay Singh ◽  
Anup Thapa ◽  
...  
Keyword(s):  
Smart Grids ◽  
Cost Effective ◽  
Energy System ◽  
Mesh Network ◽  
Smart Metering ◽  
Monitoring And Control ◽  
Smart Meters ◽  
Load Monitoring ◽  
Iot Devices ◽  
And Control

Accompanying the advancement on the Internet of Things (IoT), the concept of remote monitoring and control using IoT devices is becoming popular. Digital smart meters hold many advantages over traditional analog meters, and smart metering is one of application of IoT technology. It supports the conventional power system in adopting modern concepts like smart grids, block-chains, automation, etc. due to their remote load monitoring and control capabilities. However, in many applications, the traditional analog meters still are preferred over digital smart meters due to the high deployment and operating costs, and the unreliability of the smart meters. The primary reasons behind these issues are a lack of a reliable and affordable communication system, which can be addressed by the deployment of a dedicated network formed with a Low Power Wide Area (LPWA) platform like wireless radio standards (i.e., LoRa devices). This paper discusses LoRa technology and its implementation to solve the problems associated with smart metering, especially considering the rural energy system. A simulation-based study has been done to analyse the LoRa technology’s applicability in different architecture for smart metering purposes and to identify a cost-effective and reliable way to implement smart metering, especially in a rural microgrid (MG).

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 487 ◽  
Author(s):  
Mahmoud Elsisi ◽  
Karar Mahmoud ◽  
Matti Lehtonen ◽  
Mohamed M. F. Darwish
Keyword(s):  
Machine Learning ◽  
Smart Grids ◽  
Industry 4.0 ◽  
Learning Algorithm ◽  
Cyber Physical Systems ◽  
The Internet ◽  
Smart Meters ◽  
Industrial Environment ◽  
Physical Systems ◽  
Smart Machines

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.

scholarly journals Event Matching Classification Method for Non-Intrusive Load Monitoring

2021 ◽  
Vol 13 (2) ◽  
pp. 693
Author(s):  
Elnaz Azizi ◽  
Mohammad T. H. Beheshti ◽  
Sadegh Bolouki
Keyword(s):  
Energy Management ◽  
Low Frequency ◽  
Training Dataset ◽  
Mode Transition ◽  
Smart Meters ◽  
Available Energy ◽  
Consumption Values ◽  
Load Monitoring ◽  
Transition Times ◽  
Event Based

Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The proposed algorithm (i) filters power signals and accurately detects all events; (ii) extracts specific features of appliances, such as operation modes and their respective power intervals, from their power signals in the training dataset; and (iii) labels with high accuracy each detected event of the aggregated signal with an appliance mode transition. The algorithm is validated using REDD with the results showing its effectiveness to accurately disaggregate low-frequency measured data by existing smart meters.

scholarly journals Path-dependent institutions drive alternative stable states in conservation

2018 ◽  
Vol 116 (2) ◽  
pp. 689-694 ◽  
Author(s):  
Edward W. Tekwa ◽  
Eli P. Fenichel ◽  
Simon A. Levin ◽  
Malin L. Pinsky
Keyword(s):  
Renewable Resources ◽  
Path Dependence ◽  
Alternative Stable States ◽  
Stable State ◽  
Empirical Support ◽  
Stable States ◽  
Alternative Stable State ◽  
Important Challenge ◽  
Quantitative Analyses ◽  
Path Dependent

Understanding why some renewable resources are overharvested while others are conserved remains an important challenge. Most explanations focus on institutional or ecological differences among resources. Here, we provide theoretical and empirical evidence that conservation and overharvest can be alternative stable states within the same exclusive-resource management system because of path-dependent processes, including slow institutional adaptation. Surprisingly, this theory predicts that the alternative states of strong conservation or overharvest are most likely for resources that were previously thought to be easily conserved under optimal management or even open access. Quantitative analyses of harvest rates from 217 intensely managed fisheries supports the predictions. Fisheries’ harvest rates also showed transient dynamics characteristic of path dependence, as well as convergence to the alternative stable state after unexpected transitions. This statistical evidence for path dependence differs from previous empirical support that was based largely on case studies, experiments, and distributional analyses. Alternative stable states in conservation appear likely outcomes for many cooperatively managed renewable resources, which implies that achieving conservation outcomes hinges on harnessing existing policy tools to navigate transitions.

Design and Characterization of Single Beam for Latching Electrothermal Microswitch

2012 ◽  
Vol 468-471 ◽  
pp. 286-289
Author(s):  
Ying Zhang ◽  
Hong Wang ◽  
Yan Wang ◽  
Sheng Ping Mao ◽  
Gui Fu Ding
Keyword(s):  
Mechanical Performance ◽  
Stable State ◽  
Cantilever Beams ◽  
Analysis Software ◽  
Stable States ◽  
Element Analysis ◽  
Single Beam ◽  
Fabrication And Characterization ◽  
Continuous Power

This paper presents the design, fabrication and characterization of single beam for latching electrothermal microswitch. This microswitch consists of two cantilever beams using bimorph electrothermal actuator with mechanical latching for performing low power bistable relay applications. A stable state can be acquired without continuous power which is only needed to switch between two stable states of the microactuator. The single beam is discussed mainly to judge the possibility of realizing the designed function. First, reasonable shape of the resistance is designed using finite element analysis software ANSYS. Then, mechanical performance was characterized by WYKO NT1100 optical profiling system, the tip deflection of single beam can meet the designed demand.

Vulnerabilities and Threats in Smart Grid Communication Networks

2021 ◽  
pp. 1508-1535
Author(s):  
Yona Lopes ◽  
Natalia Castro Fernandes ◽  
Tiago Bornia de Castro ◽  
Vitor dos Santos Farias ◽  
Julia Drummond Noce ◽  
...  
Keyword(s):  
Smart Grid ◽  
Communication Networks ◽  
Smart Grids ◽  
Electrical Network ◽  
Physical Security ◽  
Smart Meters ◽  
Interconnected System ◽  
Other Information ◽  
Data Volume ◽  
Active Attacks

Advances in smart grids and in communication networks allow the development of an interconnected system where information arising from different sources helps building a more reliable electrical network. Nevertheless, this interconnected system also brings new security threats. In the past, communication networks for electrical systems were restrained to closed and secure areas, which guaranteed network physical security. Due to the integration with smart meters, clouds, and other information sources, physical security to network access is no longer available, which may compromise the electrical system. Besides smart grids bring a huge growth in data volume, which must be managed. In order to achieve a successful smart grid deployment, robust network communication to provide automation among devices is necessary. Therefore, outages caused by passive or active attacks become a real threat. This chapter describes the main architecture flaws that make the system vulnerable to attacks for creating energy disruptions, stealing energy, and breaking privacy.

Implementation of Load Control for Smart Metering in Smart Grids

2022 ◽  
pp. 127-164
Author(s):  
Abdelmadjid Recioui ◽  
Fatma Zohra Dekhandji
Keyword(s):  
Smart Grids ◽  
Control Process ◽  
Electrical Energy ◽  
Load Control ◽  
Smart Meters ◽  
Cumulative Energy ◽  
Photovoltaic Panel ◽  
Labview Software ◽  
Data Acquisition Card ◽  
Cost Calculations

The conventional energy meters are not suitable for long operating purposes as they spend much human and material resources. Smart meters, on the other hand, are devices that perform advanced functions including electrical energy consumption recording of residential/industrial users, billing, real-time monitoring, and load balancing. In this chapter, a smart home prototype is designed and implemented. Appliances are powered by the grid during daytime, and a photovoltaic panel stored power during the night or in case of an electricity outage. Second, consumed power from both sources is sensed and further processed for cumulative energy, cost calculations and bill establishment for different proposed scenarios using LABVIEW software. Data are communicated using a USB data acquisition card (DAQ-USB 6008). Finally, a simulation framework using LABVIEW software models four houses each equipped with various appliances. The simulator predicts different power consumption profiles to seek of peak-demand reduction through a load control process.

Automated modal parameters identification of bistable composite plate using two-stage clustering of operational modal testing

2020 ◽  
pp. 002199832090308
Author(s):  
Mahdi Ghamami ◽  
Hassan Nahvi ◽  
Vahid Yaghoubi
Keyword(s):  
Analytical Method ◽  
Composite Plate ◽  
Ritz Method ◽  
Stable State ◽  
User Interaction ◽  
Modal Testing ◽  
Modal Parameters ◽  
Identification Algorithm ◽  
Stable States ◽  
Modal Parameters Identification

In recent years, smart structures have attracted much interest as morphing structures. One of the simplest types of these structures is bistable composite plate, which has many applications in aerospace, structures, actuators, etc. On the other hand, inverse problem theory provides conceptual ideas and methods for the practical solution of applied problems. These methods are opposite of the forward problem and define a model of the system based on output or observations. In this paper, a modified identification algorithm is used to determine the modal parameters of a bistable composite plate based on vibrational signals. Both analytical and experimental approaches have been considered and analytical method has been used to investigate the accuracy of identification algorithm, which has been performed based on experimental measurement. In the analytical method, static and free vibration behaviors of a cross-ply bistable composite plate are studied by the Hamilton's principle and the Rayleigh–Ritz method. The experimental approach is performed by an operational modal testing, which is a nondestructive test. The identification process does not require user interaction and the process uses only a single dataset and there is no need to repeat the test or data collection. The advantages of the proposed algorithm is the ability to determine the modal parameters of each stable state with high accuracy and robustness. A comparison of the natural frequencies shows that the identification of both stable states has been successful and the estimated modal parameters are in good agreement with the analytical and experimental results.

scholarly journals Attitudes and Opinions of Social Media Users Towards Smart Meters’ Rollout in Turkey

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 732 ◽  
Author(s):  
Yash Chawla ◽  
Anna Kowalska-Pyzalska ◽  
Burcu Oralhan
Keyword(s):  
Social Media ◽  
Social Interactions ◽  
Smart Grids ◽  
Consumer Acceptance ◽  
Smart Meters ◽  
Online Questionnaire ◽  
Current Transmission ◽  
The Government ◽  
Energy Companies ◽  
Digital Channels

Increasing the efficiency of electricity transmission is nearing the top of the agenda in many countries around the world. Turkey, the world’s most newly industrialized country, is no different. Modernizing the current transmission grids to smart grids (SG) and the national rollout of smart meters (SM), are some of the measures taken by the government to meet the growing demand for electricity. Consumer acceptance and engagement are among the most important elements for the success of SG and SM, however, there have not been much studies done among Turkish electricity consumers. This purpose of this study is to fill this void, by detailing the attitudes, awareness and expectations among Turkish citizens regarding SM and listing recommendations for energy companies based on the findings. Through an online questionnaire, responses from 504 social media users were collected and analyzed. Results show that the consumers are open towards the acceptance of SM, but there is a need to raise awareness and knowledge through proper communication channels. The study has also revealed that a range of conventional and digital channels need to be actively used in order to enhance consumer willingness to accept SM. Increasing social interactions regarding SM is one of the key recommendations detailed by the authors.

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