Security Aspects of Smart Meter Infrastructures

This paper describes the importance of the interoperability in smart metering systems for modern distribution system operators. The lack of interoperability significantly increases the costs of smart metering system implementation for distribution system operators, especially the costs of purchasing new equipment. The replacement, cleanup and maintenance of electricity meters produced by different manufacturers, which are not interoperable, are also much more complex and expensive. Furthermore, without the interoperability, the system cannot be observable, i.e. the observability exists only for some particular segments of the system. This prevents many functionalities of distribution management system. In terms of interoperability, smart metering systems have gone through four different stages. A comparison of the system implementation costs for these four stages is presented for distribution system operator of Serbia.

Smart metering systems are electronic systems that measure the electricity consumption, ensuring a secure two-way transmission of information to the end customer and providing more information than a conventional meter, using electronic communication. This type of smart metering technologies has been implemented in three pilot projects from a Romanian region, in order to ensure the collection, analysis and processing of electricity specific data, as well as the connection/disconnection of each consumer. The implementation of smart meters in the three pilot areas led to a more accurate recording of final electricity consumption and a detailed monitoring of the electricity consumption by types of consumption profiles, as well as the electricity technical power losses (ETL) indicator. This paper aims to analyze the evolution of electricity technical losses registered by smart metering systems in each of the three pilot projects and also for the whole region in a certain period, in order to demonstrate the need and importance of monitoring this type of power losses and to find the best methods to reduce them, using smart metering. The results showed that the cost of electricity for the technical power losses in the chosen area is very high. In order to reduce these costs, a number of measures for ETL optimization and reduction were proposed.

Smart meters (SMs) can play a key role in monitoring vital aspects of different applications such as smart grids (SG), alternative currents (AC) optimal power flows, adversarial training, time series data, etc. Several practical privacy implementations of SM have been made in the literature, but more studies and testing may be able to further improve efficiency and lower implementation costs. The major objectives of cyberattacks are the loss of data privacy on SM-based SG/power grid (PG) networks and threatening human life. As a result, losing data privacy is very expensive and gradually hurts the national economy. Consequently, employing an efficient trust model against cyberattacks is strictly desired. This paper presents a research pivot for researchers who are interested in security and privacy and shade light on the importance of the SM. We highlight the involved SMs’ features in several applications. Afterward, we focus on the SMs’ vulnerabilities. Then, we consider eleven trust models employed for SM security, which are among the common methodologies utilized for attaining and preserving the data privacy of the data observed by the SMs. Following that, we propose a comparison of the existing solutions for SMs’ data privacy. In addition, valuable recommendations are introduced for the interested scholars, taking into consideration the vital effect of SM protection on disaster management, whether on the level of human lives or the infrastructure level.

Cross-border energy trading activity via interconnection has received much attention in Southern Asia to help the South Asian Association for Regional Cooperation (SAARC) region’s energy deficit states. This research article proposed a smart metering system to reduce energy losses and increase distribution sector efficiency. The implementation of smart metering systems in utility management plays a pivotal role in advancing several Sustainable Development Goals (SDGs), i.e.; SDG (Affordable and Clean Energy), and SDG Climate Action. By enabling real-time monitoring, accurate measurement, and data-driven management of energy resources, smart meters promote efficient consumption, reduce losses, and encourage sustainable behaviors among consumers. The adoption of a smart metering system along with Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis, socio-economic analysis, current challenges, and future prospects was also investigated. Besides the economics of the electrical distribution system, one feeder with non-technical losses of about 16% was selected, and the cost–benefit analysis and cost–benefit ratio was estimated for the SAARC region. The import/export ratio is disturbing in various SAARC grids, and a solution in terms of community microgrids is presented from Pakistan’s perspective as a case study. The proposed work gives a guidelines for SAARC countries to reduce their losses and improve their system functionality. It gives a composite solution across multi-faceted evaluation for the betterment of a large region.

Data classification of users’ electricity consumption provides an in-depth analysis for users’ electricity consumption status, which plays a vital role in the management and distribution of electric energy. So, some data classification methods have been proposed to solve the classification problem of electricity consumption data. However, plaintext-based data classification may bring about the privacy leakage of electricity consumption data. In this paper, we propose a privacy-preserving classification scheme for electricity consumption data under fog computing-based smart metering system, which is based on convolutional neural network (CNN) model with fully homomorphic method (CKKS). The target of our proposed scheme is to solve the leakage problem of private electricity consumption data during the classification procedure. In our scheme, an improved K-means-based labeling algorithm is constructed to process historical electricity consumption data, which is used as the sample data to train the CNN classification model by cloud server. Also, the fog nodes are only permitted to obtain the related ciphertext parameters of the trained CNN model, and perform the classification of ciphertext-based electricity consumption data generated by fully homomorphic method. Based on the classical testing data, the experimental results show that our proposed classification scheme can provide the high classification accuracy of electricity data while protecting the privacy of electricity data.

Smart metering is an essential feature of smart grids, allowing residential customers to monitor and reduce electricity costs. Devices called smart meters allows residential customers to monitor and reduce electricity costs, promoting energy saving, demand management, and energy efficiency. However, monitoring a households' energy consumption through smart meters poses serious privacy threats, and have thus become a major privacy issue. Hence, a significant amount of research has appeared recently with the purpose of providing methods and mechanisms to reconcile smart metering technologies and privacy requirements. However, most current approaches fall short in meeting one of several of the requirements for privacy preserving smart metering systems. In this paper we show how Intel SGX technology can be used to provide a simple and general solution for the smart metering privacy problem that meets all these requirements in a satisfactory way. Moreover, we present also an implementation of the proposed architecture as well as a series of experiments that have been carried out in order to assess how the proposed solution performs in comparison to a second implementation of the architecture that completely disregards privacy issues.

In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details.

Presents a collection of slides covering the following topics: energy market competition; energy consumption; carbon reduction; government policy; data security; stakeholder workshops; consumer engagement and smart metering system.

Smart metering systems often utilize Power Line Communication (PLC) for bidirectional data exchange between smart energy meters and data concentrators. Electromagnetic interference generated by power electronic converters have been found as a main cause of communication errors in PLC data transmission. In this paper novel, modified pseudo-random pulse width modulation technique was developed to significantly reduce PLC frame error rate caused by interference generated by power electronic converters. Moreover, cyber–physical system has been presented as a case study providing high flexibility in controlling the switching rate of change of the modulation. As a general contribution, in the paper has been proposed the concept of electromagnetic interference noise shaping to broaden the possibility of preventing and mitigating non-compatibility scenarios between power electronic converters and telecommunications devices. The experimental results might be useful for system integrators involved in assurance of electromagnetic compatibility of power electronic interfaces and PLC based smart metering systems.

Smart metering systems obtain fine-grained consumption data of their users. This allows for effective load balancing, but at the same time threatens consumers' privacy. Since the electricity provider only needs the characteristics of a region, not individuals, approaches like one by Marmol et al. suggest to aggregate data to protect consumer privacy. However, an implementation of such an approach also has to consider the legal and regulatory situation. In Germany, the technical guideline TR-03109 issued by the Federal Office for Information Security specifies demands which have to be fulfilled so that a smart meter gateway can be certified for use. These specifications imply limitations to the protocol design. Within this paper, we discuss the applicability of the method presented by Marmol et al. under consideration of the German Smart Metering guideline. Where conformity is not given, we offer a solution to overcome these restrictions by adapting their method and introduce a third party aggregator who does not have to be trusted. Our method comes with additional communication effort but behaves well in terms of memory and computational overhead. The achieved privacy level outreaches a purely pseudonymous value transmission. Also it does not contradict the postulations of TR-03109, making it an applicable choice for privacy protection in real-world smart metering systems.

Advanced smart meters generate meter readings in a time unit less than a second. Fine-grained meter readings enable various smart grid applications, such as load monitoring, automatic billing, and power generation planning. However, those meter readings threaten individuals' privacy by revealing details of one's daily activities. The time granularity of smart meters is often much finer than the one a smart grid application demands. Thus, the storage and access control mechanisms of meter readings are critical to balancing privacy requirements and application functionalities. Previous studies address the issue by considering a locally trusted storage device and using cryptographic primitives. We consider a storage outsourcing scenario, where the external storage environment is semi-trusted. We construct a privacy preserving metering system by using a trusted platform module in a smart meter and pseudorandom number generators inside the module. Our system guarantees the secure storage of meter readings and supports multiple time granularities. In our system, a user grants a service provider an access right over meter readings at a time granularity S. The granted service provider is only allowed to get the power consumption at a time unit of the granted time granularity. Our system provides a simple yet very practical solution to the privacy preserving smart metering system. Moreover, we provide a privacy model to capture the privacy requirement and show that our system is privacy preserving against honest-but-curious service providers.

The design and implementation studies of a remote monitoring system are presented in this study. The proposed design is improved in terms of smart metering infrastructure based on current, voltage, and power measurements. The communication among the photovoltaic (PV) panels and host PC is performed by designed ZigBee transceiver system. Sensing circuits are very important devices to measure for both current and voltage magnitudes of electrical systems. The measured data are processed by the microcontroller unit (MCU) and are modulated after signal processing operations for wireless transmission. Although the transceiver is configured to execute bi-directional communication, unidirectional data flow is performed where the smart metering system transmits data to monitoring substructure. The monitoring software is also implemented in the context of the presented study. The Visual Studio.Net software development kit is used to design and to code the software. The performed experimental studies showed that the proposed real time monitoring and smart metering system could be exploited to monitor current, voltage and power magnitudes of the PV panels in an efficient way.

Smart metering techniques successfully transmit the electric meter readings from consumers to the operator within the given time constraints. Such techniques require huge energy for transmitting the large-size of data to the long distance. This poster proposes a smart metering system that consumes low energy and less time to transmit electric meter readings successfully. We first propose a lightweight compression model to compress the data at Edge device that is near to the consumer. Next, we transmit the compressed data to the operator using Long-Range network. Finally, we successfully decompress the data at the operator by using a large-size decompression model. Preliminary experimental comparisons with a recent state-of-the-artwork show that the lightweight compression-based system gives better performance with respect to delay and energy.

Smart metering is a subject that attracts much more attention. Smart metering is obtaining many benefits in a lot of aspects. Many smart metering projects are going on many countries, such as UK, Italy, the USA and other countries. Some planning studies list in this paper show that smart metering is technically feasible. Many benefits are available, especially on improving the energy efficiency. The future smart metering system will rely on policies and governmental fiscal stimuli. However cyber security requirement will be an issue. Smart metering deserves a big attention.

In this chapter, a survey of protocols for privacy-preserving data aggregation in smart metering systems is presented. They are necessary to protect customers'profiles from adversaries, who can predict customers' behaviour and manipulate them. The state of the art covers the entire cycle of a smart grid with real-time consolidated consumption, billing processes and verifications. However, the real-time consolidated consumption is public in the best protocol. In this work, we find an improved protocol that can hide real-time consolidated consumptions keeping them accessible only to the public utility. In addition, a complexity analysis of algorithms is presented and a simulation with millions of real-world measurements collected by thousands of smart meters is run to validate the theoretical evaluation. Furthermore, the improved protocol slightly outperforms the state of the art in the encryption algorithm, which runs in constrained smart meters. Moreover, such techniques can be applied in several other research areas.