Intelligent Energy Utilization Analysis Using IUA-SMD Model Based Optimization Technique for Smart Metering Data

Smart metering has gained considerable attention as a research focus due to its reliability and energy-efficient nature compared to traditional electromechanical metering systems. Existing methods primarily focus on data management,rather than emphasizing efficiency. Accurate prediction of electricity consumption is crucial for enabling intelligent grid operations,including resource planning and demandsupply balancing. Smart metering solutions offer users the benefits of effectively interpreting their energy utilization and optimizing costs. Motivated by this,this paper presents an Intelligent Energy Utilization Analysis using Smart Metering Data(IUA-SMD)model to determine energy consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing,feature extraction,and classification,with parameter optimization. We employ the extreme learning machine(ELM)based classification approach within the IUA-SMD model to derive optimal energy utilization labels. Additionally,we apply the shell game optimization(SGO)algorithm to enhance the classification efficiency of the ELM by optimizing its parameters. The effectiveness of the IUA-SMD model is evaluated using an extensive dataset of smart metering data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving a maximum accuracy of65.917% and a minimum MSE of0.096. These results highlight the potential of the IUA-SMD model for enabling efficient energy utilization through intelligent analysis of smart metering data.

Technologies Behind the Smart Grid and Internet of Things: A System Survey

Electric smart grids enable a bidirectional flow of electricity and information among power system assets.For proper monitoring and con-trolling of power quality,reliability,scalability and flexibility,there is a need for an environmentally friendly system that is transparent,sustainable,cost-saving,energy-efficient,agile and secure.This paper provides an overview of the emerging technologies behind smart grids and the internet of things.The dependent variables are identified by analyzing the electricity consumption patterns for optimal utilization and planning preventive maintenance of their legacy assets like power distribution transformers with real-time parameters to ensure an uninterrupted and reliable power supply.In addition,the paper sorts out challenges in the traditional or legacy electricity grid,power generation,transmission,distribution,and revenue management challenges such as reduc-ing aggregate technical and commercial loss by reforming the existing manual or semi-automatic techniques to fully smart or automatic systems.This article represents a concise review of research works in creating components of the smart grid like smart metering infrastructure for postpaid as well as in prepaid mode,internal structure comparison of advanced metering methods in present scenarios,and communication systems.

Ensemble Voting-Based Anomaly Detection for a Smart Grid Communication Infrastructure

Advanced Metering Infrastructure(AMI)is the metering network of the smart grid that enables bidirectional communications between each consumer’s premises and the provider’s control center.The massive amount of data collected supports the real-time decision-making required for diverse applications.The communication infrastructure relies on different network types,including the Internet.This makes the infrastructure vulnerable to various attacks,which could compromise security or have devastating effects.However,traditional machine learning solutions cannot adapt to the increasing complexity and diversity of attacks.The objective of this paper is to develop an Anomaly Detection System(ADS)based on deep learning using the CIC-IDS2017 dataset.However,this dataset is highly imbalanced;thus,a two-step sampling technique:random under-sampling and the Synthetic Minority Oversampling Technique(SMOTE),is proposed to balance the dataset.The proposed system utilizes a multiple hidden layer Auto-encoder(AE)for feature extraction and dimensional reduction.In addition,an ensemble voting based on both Random Forest(RF)and Convolu-tional Neural Network(CNN)is developed to classify the multiclass attack cate-gories.The proposed system is evaluated and compared with six different state-of-the-art machine learning and deep learning algorithms:Random Forest(RF),Light Gradient Boosting Machine(LightGBM),eXtreme Gradient Boosting(XGboost),Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and bidirectional LSTM(biLSTM).Experimental results show that the proposed model enhances the detection for each attack class compared with the other machine learning and deep learning models with overall accuracy(98.29%),precision(99%),recall(98%),F_(1) score(98%),and the UNDetection rate(UND)(8%).

A Prepaid Smart Metering Scheme Based on WiMAX Prepaid Accounting Model

Prepaid energy meters have been widely adopted by utilities in different countries across the world as an innovative solution to the problem of affordability and consumption management. However, the present smart card based systems have some inherent problems like added cost, low availability and lack of security. In the future Smart Grid paradigm, use of smart meters can completely overhaul these prepaid systems by introducing centralized accounting, monitoring and credit-control functions using state-of-the-art telecommunication technologies like WiMAX. In this paper we pro-pose a prepaid smart metering scheme for Smart Grid application based on centralized authentication and charging using the WiMAX prepaid accounting model. We then discuss its specific application to Demand Response and Roam-ing of Electrical Vehicles.

Embedded TLS 1.2 Implementation for Smart Metering & Smart Grid Applications

Digital networked communications are the key to all Internet-of-Things applications, especially to smart metering systems and the smart grid. In order to ensure a safe operation of systems and the privacy of users, the transport layer security(TLS) protocol, a mature and well standardized solution for secure communications, may be used. We implemented the TLS protocol in its latest version in a way suitable for embedded and resource-constrained systems. This paper outlines the challenges and opportunities of deploying TLS in smart metering and smart grid applications and presents performance results of our TLS implementation. Our analysis shows that given an appropriate implementation and configuration, deploying TLS in constrained smart metering systems is possible with acceptable overhead.

Exploiting the Cellular Infrastructure for Data Transmission in Smart Metering Systems

To implement the access and backhaul networks for Smart Metering (SM) systems various technologies are combined with the existing communications infrastructure. This paper deals with data transmission in SM systems, focusing on how the existing cellular networks infrastructure is employed to implement SM access communication networks. The analysis aims at analyzing the role of the cellular communications infrastructure taking into account the spatial distribution and installation points of the smart meters, the urban and topological characteristics of the SM deployment areas and the common practice so far followed by the utilities. It is demonstrated that cellular communications, either exclusively or combined with power line communications, enable immediate and scalable deployment of SM access communication networks at low installation cost, thus constituting the basic option for the implementation of smart metering.

New Hybrid IoT LoRaWAN/IRC Sensors:SMARTWater Metering System

The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste management.This ongoing development is further pushed forward by the gradual deployment of 5G networks.With 5G capable smart devices,it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive IoT.Massive-IoT(low-power wide area network-LPWAN)enables improved network coverage,long device operational lifetime and a high density of connections.Despite all the advantages of massive-IoT technology,there are certain cases where the original concept cannot be used.Among them are dangerous explosive environments or issues caused by subsurface deployment(operation during winter months or dense greenery).This article presents the concept of a hybrid solution of IoT LoRaWAN(long range wide area network)/IRC-VLC(infrared communication,visible light communication)technology,which combines advantages of both technologies according to the deployment scenario.

An Ad-Hoc Low Cost Wireless Sensor Network for Smart Gas Metering

The monitoring of power consumption has become of a great interest in recent years as well as the innovative technologies available to realize Wireless Sensor Networks (WSNs) have experienced a great growth. While smart metering technologies for electric energy are already established, as sensors power supply comes directly from power lines, WSN nodes for gas metering should necessarily be equipped with long life batteries. The presented work describes a new prototypal low cost WSN designed ad hoc for gas smart metering. The network has a star topology: each sensor node can be completely integrated with standard reed relay gas meter, and it is capable to measure the gas consumption. The information is sent to the central node (the Access Point, AP) through an RF links. The sensor nodes have been designed with custom electronics and a proprietary firmware, in order to work with a common 3.6 V lithium battery which is able to ensure a life period of about 10 years for each node. Only the AP must be connected directly to electric power. The AP is connected through the RS-232 interface to a control embedded PC equipped with a LAMP (Linux, Apache, MySQL, PHP) framework: it stores all the information coming from each node in a coherent database and allows authorized users to check the network status using a web interface. The WSN is self-learning and it is capable to detect new nodes joining the network without altering the normal operative flow. Moreover e-mail and SMS alerts can be activated to alert if a node is disconnected from the network or some problems occur. A first prototype of the WSN has been already tested achieving good results.

Secure Communication Networks in the Advanced Metering Infrastructure of Smart Grid

In this paper,a security protocol for the advanced metering infrastructure(AMI) in smart grid is proposed.Through the AMI,customers and the service provider achieve two-way communication.Real-time monitoring and demand response can be applied because of the information exchanged.Since the information contains much privacy of the customer,and the control messages need to be authenticated,security needs to be ensured for the communication in the AMI.Due to the complicated network structure of the AMI,the asymmetric communications,and various security requirements,existing security protocols for other networks can hardly be applied into the AMI directly.Therefore,a security protocol specifically for the AMI to meet the security requirements is proposed.Our proposed security protocol includes initial authentication,secure uplink data aggregation,secure downlink data transmission,and domain secrets update.Compared with existing researches in related areas,our proposed security protocol takes the asymmetric communications of the AMI and various security requirements in smart grid into consideration.

ECC技术在大容量智能Smart Media卡上的应用

分析了Smart Media(SM)智能卡的使用现状,特别是大容量SM卡数据存储系统的关键技术问题。提出利用ECC编码技术在SM卡实现DOS文件系统的ECC编码,从而解决大容量SM卡在实际应用中的关键技术问题。

Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

One of the major concerns for the utilities in the Smart Grid(SG)is electricity theft.With the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously possible.For this purpose,we have taken historical data of energy thieves and normal users.To avoid imbalance observation,biased estimates,we applied the interpolation method.Furthermore,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.By proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time complexity.To minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark scheme.Our proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,respectively.Furthermore,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.

Investigation of Bandwidth Requirement of Smart Meter Network Using OPNET Modeler

Smart meter networks are the backbone for smart electrical distribution grid. Smart meter network requires the bidirectional communications medium and interoperability capability. As thousands of meters are interconnected in the smart meter network, it is vital to select an appropriate communication bandwidth to facilitate real-time two-way information flows and this will also allow further uptake of greenhouse-friendly technology options and enhance energy security. Optimized Network Engineering Tools (OPNET) Modeler is one of most powerful simulation tools for the analysis of communication networks. In this paper, several models of different structured smart meter networks were developed with network parameters which were connected with different communication links such as 10 BaseT and 100 BaseT in order to measure propagation delay, throughput, and utilization of the network. It was found that the propagation delay decreases with higher bandwidth. The other network parameters, namely network utilization and network throughput were also analysed. Based on the investigation, it is recommended that the 100 BaseT communication link is suitable for the smart meter network. The outcome of this paper provided a guideline to the future smart meter network developer so as to avoid catastrophic challenges faced by some of the distribution companies.

Genetic Algorithm-Based Redundancy Optimization Method for Smart Grid Communication Network

This paper proposes a redundancy optimization method for smart grid Advanced Metering Infrastructure(AMI) to realize economy and reliability targets.AMI is a crucial part of the smart grid to measure,collect,and analyze data about energy usage and power quality from customer premises.From the communication perspective,the AMI consists of smart meters,Home Area Network(HAN) gateways and data concentrators;in particular,the redundancy optimization problem focus on deciding which data concentrator needs redundancy.In order to solve the problem,we first develop a quantitative analysis model for the network economic loss caused by the data concentrator failures.Then,we establish a complete redundancy optimization model,which comprehensively consider the factors of reliability and economy.Finally,an advanced redundancy deployment method based on genetic algorithm(GA) is developed to solve the proposed problem.The simulation results testify that the proposed redundancy optimization method is capable to build a reliable and economic smart grid communication network.

An Overview of the Smart Grid in Great Britain

This paper presents an overview of the current status of the development of the smart grid in Great Britain(GB).The definition,policy and technical drivers,incentive mechanisms,technological focus,and the industry's progress in developing the smart grid are described.In particular,the Low Carbon Networks Fund and Electricity Network Innovation Competition projects,together with the rollout of smart metering,are detailed.A more observable,controllable,automated,and integrated electricity network will be supported by these investments in conjunction with smart meter installation.It is found that the focus has mainly been on distribution networks as well as on real-time flows of information and interaction between suppliers and consumers facilitated by improved information and communications technology,active power flow management,demand management,and energy storage.The learning from the GB smart grid initiatives will provide valuable guidelines for future smart grid development in GB and other countries.

Costs and Benefits of Smart Grids on Liberalized Markets

The discussion about smart grid(SG) implementation is mostly focused on pilot projects.These projects are necessary for mapping of particular technical devices of advanced metering management(AMM) which is needed for successful SG and whole functional SG system operation.According to our opinion,for the next step of SG implementation,the participation of effective market design would be quite necessary.In other words,pilot project which is operated regardless to the market conditions and special SG tariff is incomplete and could be irrelevant for further evaluation of feasibility.With regard to above mentioned facts,the detailed cost-benefit-analysis(CBA) is needed to establish the correct methodology for evaluation of SG implementation effectiveness.Related aspects are mentioned and discussed in this paper,in which the particular cost and benefits as well as feedback that occurs as the reaction on implementation are summarized and quantified.

A Key Management Scheme for ZigBee in AMI of Smart Grid

Advanced metering infrastructure( AMI) is a critical part of the smart grid,and ZigBee is playing an increasingly important role in AMI.The cyber security is the prerequisite to ensure the reliable operation of AMI.To guarantee the ZigBee communication security in AMI,a key management scheme based on the elliptic curve cryptosystem( ECC) is proposed.According to the ways of information transformation in AMI,the scheme is categorized as unicast communication key management process and multicast communication key management process.And in the scheme,the selection of elliptic curve,the calculation of ZigBee node's ECC public key and private key,the establishment and distribution of the link key in unicast communication,and the establishment and distribution of the network key in multicast communication are elaborated.The analysis results show that the proposed key management scheme is secure,and consumes less memory and energy,thus,can meet the demands of communication security of AMI.

Privacy Preservation of Smart Meters Based on Identity Authentication

Smart meters provide a lot of convenience for both power supply and consumption. Due to the frequent transmission of information, it brings great challenges to the privacy preservation of the user’s household power consumption data in the smart grid. In order to achieve the anonymity of smart meters. A smart meter privacy preservation scheme based on identity authentication is proposed. The third-party certification authority is introduced in this scheme;it issues pseudonym certificates to realize the identity privacy preservation of smart meters. The masking technology with the Advanced Encryption Standard algorithm is used for data aggregation. The results show that our scheme reduces the computational cost and the communication overhead.

Design of Real-time Electricity Prices and Wireless Communication Smart Meter

Under the background of smart grid’s real-time electricity prices theory, a real-time electricity prices and wireless communication smart meter was designed. The metering chip collects power consumption information. The real-time clock chip records current time. The communication between smart meter and system master station is achieved by the wireless communication module. The “freescale” micro controller unit displays power consumption information on screen. And the meter feedbacks the power consumption information to the system master station with time-scale and real-time electricity prices. It results that the information exchange between users and suppers can be realized by the smart meter. It fully reflects the demanding for communication of smart grid.

An Anti-Eavesdropping Method in Data Collection of Smart Meter

At present, DL/T 645-2007 communication protocol is used to collect data for smart meters. However, in the beginning, this protocol is not designed to be a secure protocol and only the function and reliability were taken into account. Plaintext is used in the protocol for data transmission, as a result, attackers can easily sniff the information and cause information leakage. In this paper, man-in-the-middle attack was used to verify that the smart meter data acquisition process was vulnerable when facing third-party attacks, and this can result in data eavesdropping. In order to resist such risks and prevent information being eavesdropped, a real ammeter communication experimental environment was built, it realized two-way identity authentication between data acquisition center and ammeter data center. At the same time, RSA (Rivest-Shamir-Adleman) was used to encrypt the meter data, which encrypted the collection, storage process of meter data and ensured the confidentiality and integrity of the meter data transmission. Compared with other methods, this method had obvious advantages. The analysis showed that this method can effectively prevent the data of smart meters from being eavesdropped.