Secure service provision in smart grid communications

Smart grids are conceived to ensure smarter generation, transmission, distribution, and consumption of electricity. It integrates the traditional electricity grid with information and communication technology. This enables a two-way communication among the smart grid entities, which translates to exchange of information about fine-grained user energy consumption between the smart grid entities. However, the flow of user energy consumption data may lead to the violation of user privacy. Inference on such data can expose the daily habits and types of appliances of users. Thus, several privacy preservation schemes have been proposed in the literature to ensure the privacy and security requirements of smart grid users. This chapter provides a review of some privacy preservation schemes. The schemes operational procedure, strengths, and weaknesses are discussed. A taxonomy, comparison table, and comparative analysis are also presented. The comparative analysis gives an insight on open research issues in privacy preservation schemes.

Smart Grids (SG) may be the most significant technological change in the history of electric grids, that can help curb the looming energy crisis worldwide, with intelligent generation, transmission and distribution of energy using a robust communication network. Power lines are a very promising solution for carrying data to serve as broadband access network in the context of SG, along with the wireless communication techniques. This paper investigates the design and simulation of a digital communication system optimized for Power Line Communication (PLC) in Smart Grids. For the proposed PLC transceiver, we consider Discrete Multitone (DMT) modulation based on a modified bit loading technique for the subcarriers. Our results reveal that the proposed incremental bit loading algorithm enhances data rate, and reduces computation time, as compared to the originally proposed incremental bit loading algorithm for PLC.

Smart grid has become the hot topic to domestic and foreign about the development trend of power grid in recent years, and communication technology is foundation of the development of smart grid; the paper forecasts the smart grid communications automation and development trend.Further from intelligent dispatching center, smart grid, smart distribution grid and users, in view of the existing and emerging intelligent and automatic application were communication needs analysis, and provide a reliable basis for the smart grid communications planning.

Smart grid is an essential part of the world's changing energy landscape. The uptake of smart grid by utilities is however hampered by the perceived complexity and large capital investment required to implement resilient Information Communication Technology (ICT) and networks that can support self-healing smart grids. Furthermore, failure to meet stringent smart grid communication reliability requirements can have disastrous consequences for grid owners and users. Many of the challenges utilities face with their smart grid ICT network development plans can be attributed to a reliance on conventional designs centred on expanding network hardware infrastructure in vast grid networks. What is needed to overcome these challenges is alternative ways of designing smart grid communication networks, using software defined approaches. This paper proposes a framework that supports software defined designs by combining the principles of the Internet of Things (IoT) paradigm and Machine-to-Machine (M2M) communication. Using the frameworks of software defined systems and virtualisation, our proposed architecture aims to provide a more flexible and affordable approach to developing and maintaining grid communication networks while offering a high level of network reliability, required for various smart grid applications. An evaluation of the implementation of this architecture in a design, based on a real city distribution grid, shows that a software defined communication network is easy to implement when using virtual machines running on existing computer infrastructure and that it is capable of supporting the network functions required for improving communication reliability. We conclude that this approach can potentially promote the adoption of smart grid by utilities while offering new innovative ways for smart grid developers to improve their grid designs.

The inclusion of renewable energy in the conventional grid system and the digitalization of the various aspects of the power system have precipitated the transformation of the traditional grid system to a smart grid. Key to the implementation of the smart grid is various communication technologies. The emerging dominance of communication technologies in power systems applications is pivotal to modernizing the conventional grid system. This research presented an overview of the application of communication technologies in the digitalization of the power systems network. It reviews smart grid communication technologies, their features, relevance, and various roles being played toward delivering an effective electrical service to stakeholders. Hence, this study focused on wireless and wired communication technologies applicable to smart grid applications. Based on the review, each communication technology has its strengths and weaknesses; hence in selecting the most appropriate technology for application in a smart grid, a compromise must be made. Therefore, for choosing the most preferred communication technology in any smart grid application, it is important to deploy the efficacy of multi-criteria methods. To serve as a case study, a framework for selecting a communication technology for advanced metering infrastructure is proposed and applied. Based on the spectrum, data rate, and coverage range, the study revealed that WiMAX communication technology is the most preferred, followed by Zigbee; the least preferred communication technology for smart grid communication is Power Line Communication (PLC).

As a result of the old-style electric grid's inability to handle the extensive incorporation of renewable energy resources and distributed renewable energy resources into the electric grid. In the twenty-first century, smart grid technology has entered the picture. Because smart grids operate on two-way communication, communication and information technology are critical to the smart grid's effective operation. The advanced version of the smart grid structure is presented in this article. Furthermore, this article discusses existing and advanced communication and information technology. Finally, the manuscript discusses future research advancements in communication and the most crucial information technologies, such as the Internet of Things (IoT), cloud computing, fog and edge computing, and blockchain in the smart grid. So, the smart grid can manage the massive integration of renewable energy resources while providing customers with efficient, sustainable, and reliable power.KeywordsIoT-Internet of ThingICT-Information and Communication TechnologyCC: Cloud Computing

Smart grid technologies are expected to increase system efficiency and reliability using advancement in automation, communication, computation, and optimization. Several control algorithms have been developed or enhanced for operation and control of smart distribution grid. In recent years, volt/var control (VVC) algorithms have been proposed for energy saving in distribution systems due to advancement provided by smart grid automation and control. VVC helps to lower distribution feeder voltage to decrease energy consumption. However, quantification of this impact is hard due to several external factors such as weather and end users' behavior. On the other hand, existing evaluation methods of VVC algorithms are either not suitable for long-term study or intrusive. This paper addresses these issues by proposing a new technique to estimate “distribution system demand without smart grid implementation” utilizing “data measured from system with smart grid implementation.” Interdependence of voltage and load is considered based on estimated load characteristic. Our key contribution is developing a method for quantifying the real-time energy saving of smart grid automation and control focused on VVC and implementing in an electric utility in eastern Washington, USA. The algorithm is developed using both commercial and open-source software.

Over the last decade, Internet of Things (IoTs) have brought radical changes to the means and forms of communication for monitoring and control of a large number of applications including Smart Grid (SG). Traditional energy networks have been modernized to SGs to boost the energy industry in the context of efficient and effective power management, performance, real-time control and information flow using two-way communication between utility provides and end-users. However, integrating two-way communication in SG comes at the cost of cyber security vulnerabilities and challenges. In the context of SG, node compromise is a severe security threat due to the fact that a compromised node can significantly impact the operations and security of the SG network. Therefore, in this chapter, Key Management Scheme for Communication Layer in the Smart Grid (KMS-CL-SG) has proposed. In order to achieve a secure end-to-end communication we assign a unique key to each node in the group.

In this paper, we present a signcryption scheme called CP_ABSC based on Ciphertext-Policy Attribute Based Encryption (CP_ABE)[7] to secure the multicast communications in smart grids that require access control, data encryption, and authentication to ensure message integrity and confidentiality. CP_ABSC provides algorithms for key management, signcryption, and designcryption. It can be used to signcrypt a message based on the access rights specified by the message itself. A user can designcrypt a ciphertext if and only if it possesses the attributes required by the access structure of the data. Thus CP_ABSC effectively defines a multicast group based on the access rights of the data specified by the data itself, which differs significantly from the traditional Internet based multicast where the destination group is predetermined and must be known by the data source. CP_ABSC provides collusion attack resistance, message authentication, forgery prevention, and confidentiality. It can be easily applied in smart grids to secure the instructions/commands broadcast from a utility company to multiple smart meters (push-based multicast) and the data retrieved from a smart meter to multiple destinations (pull-based multicast). Compared to CP_ABE, CP_ABSC combines encryption with signature at a lower computational cost for signcryption and a slightly higher cost in designcryption for signature verification. We also consider the adoption of attribute-based signature (ABS), and conclude that CP_ABSC has a much lower computational cost than ABS.

The management and control of the renewable energy sources in smart grid are currently the most challenging topics in this area of research. Since renewable energy sources are potentially located away from urban areas, cellular communications are most suitable for this purpose. In this paper, we propose an LTE-based priority and delay oriented multicast scheduling technique designed specifically for smart grid management purposes. Using multicast communications in smart grid is most suitable since various messages should be sent to multiple renewable energy sources simultaneously. This is to ensure that these sources are coordinated in performing the same action within a certain time constraint to avoid any power shortages or other issues within the system. We evaluate our proposed technique and compare it with other general purpose multicast scheduling techniques. Results show that the proposed technique offers an enhanced performance over other techniques in delivering smart grid traffic while maintaining good performance for the other real-time traffic, such as voice traffic, within the network.

The smart grid will play an important role in the future city to support the diversified energy supply. Wireless communication, the most cost-effective alternative to the traditional wire-lines, promises to provide ubiquitous bi-direction information channel for smart grid devices. However, due to the complex environment that smart grid devices located in, the wireless link is easily been interfered with and therefore appears strong stochastic features. Considering different smart grid application traffics have different and strict reliability requirements, the confidence interval lower boundary is more suitable to represent the worst-case reliability of the stochastic wireless link quality and trustworthy for judging whether the link quality is qualified for the next transmission. In this paper, we propose a Long-Short-Term-Memory (LSTM) based link quality confidence interval lower boundary prediction for the smart grid. According to the analysis of the characteristics of the wireless link, we employ the wavelet denoising algorithm to decompose the signal-to-noise ratio time series into the deterministic part and the stochastic part for training two LSTM neural networks. Then, the deterministic part and the variance of the stochastic part are predicted respectively. Lastly the confidence interval boundary is calculated. To verify the performance of the proposed LQP method, real-world experiments are carried out and the results show that our method is more accurate and trustworthy in comparison with other link quality prediction methods.

This note considers the judgment in City of Cape Town v National Energy Regulator of South Africa (NERSA) and Minister of Energy (unreported case number 51765/17 of 11 August 2020), which attracted much attention for its challenge of the constitutionality of section 34 of the Electricity Regulation Act, 4 of 2006. Although the question of constitutionality was not discussed in the judgment, it is argued that this was an oversight and a missed opportunity to unpack the role of municipalities in the provision of sustainable electricity services. Further, the note considers the challenges of intergovernmental relations in co-operative government (from a conceptual and practical perspective) and concludes that this case highlights the importance of good relations between organs of State, especially where contentious but important issues have arisen.

With the rapid development of national economy, our demand for power resources has also increased rapidly. The traditional power grid can not be achieved operational status of equipment for effective monitoring and control, we will not be able to ensure the quality and quality of electricity service. Cloudbased build smart grid information platform enables gathering the parameter of grid operation state, greatly increasing the economic efficiency of power enterprises. Firstly, cloud computing and smart grid briefly described, and then pointed out that cloud computing applications in the smart grid information platform, and specialized of cloud-based smart grid information platform, in order for the power grid enterprises to enhance their level of service and provide effective reference. KEYWORD: cloud computing; smart power grids; information platform; Application 4th International Conference on Mechanical Materials and Manufacturing Engineering (MMME 2016) © 2016. The authors Published by Atlantis Press 202 3 THE MAIN PROBLEM IS STILL THE SMART GRID INFORMATION PLATFORM FACING The transition to a cloud computing data center. Our data center because of the different regions and the degree of information presents different characteristics, some data centers already have a basic cloud computing capabilities, but most data centers still remain in the initial level, to ensure the normal operation of the existing data center power under the premise, gradual transition to cloud computing data center in order to meet future requirements of the development of smart grid. Restricting data transmission problem. State Grid Corporation between provincial branches and there are a lot of data needs to be transmitted, will bring massive data transmission efficiency decreases, taking into account the load balancing device between the cloud node, thus building a wide area network channels to resolve data transmission problem. Security of data transmission. Data Center for Cloud Computing power companies to build internal private cloud, capable of self-maintenance and management, system wide area network data transmission services, according to the third security zone defined security partition, and install proprietary equipment production area and external public network isolation . 4 CLOUD COMPUTING APPLICATIONS IN THE SMART GRID INFORMATION POLICY PLATFORM Integrate and optimize the management of heterogeneous resources. Among the smart grid systems, data resources, information systems between various platforms and mutually dispersed, severe heterogeneity, thus leading to the integration of the quality of information sharing to increase difficulty, unable to effectively improve network management efficiency for the power distribution system electrical work quality management and marketing operations system maintenance upgrade will not be able to effectively meet demand (Jie Yang, 2014). Cloud computing technology enables the power system to effectively integrate the various business data and computing resources on the basis of information for business collaboration platform built on effective, able to satisfy the huge demand for smart grid information resource sharing. Cloud computing network virtualization and application virtualization technology, the server virtualization technology and other resources to achieve each service abstraction, and then realize the difference between the system and the software effectively eliminated by the appropriate method to achieve the effective integration of information resources, and then to optimize the management, greatly improving the efficiency of heterogeneous resources management applications. Distributed storage and management of large volume of data. After application of smart grid information platform construction, customer service requests varied, huge data volume information brought it to the storage and management of data provides a great challenge. Cloud computing technology in general face amount of data each smart grid system and unit collected using forms distributed storage of data to achieve the effective storage, greatly to ensure the security and reliability of data storage. GFS effective use of technology with each node, the master server is responsible for the effective management of the whole file system, the file system and complete the work of the metadata stored in the data block is the main server for data storage block sliced, and by saving three or more redundant backup storage. At the same time, client access and complete access to the main block server information. Fast Power System Parallel Computation and Treatment. Smart grids and information platform for the large volume of data to provide stable operation of the power grid data base, but more critical is the analysis and design of each system operating data, planning and decision-making, and even failures and transient stability, state estimation and intelligent a variety of computing and content analysis and decision-making process, its huge computing needs, general computing system can not reach its goal (Wang, Mengxue, 2015). Cloud computing technology through parallel computing technology has greatly enhanced parallel processing capability of the power system, which provides parallel programming model makes more simple and efficient parallel algorithms. MapReduce as Google made an important parallel programming model, and its role in large data sets in parallel computing plays a very prominent. Parallel processing job results by the client to achieve effective user submitted, via decomposition automated master role, the corresponding task scheduling to working nodes and nodes work completed by the specific calculations and perform the appropriate task. 5 SMART GRID INFORMATION PLATFORM CLOUD COMPUTING ANALYSIS Cloud Computing Smart Grid Information Platform Architecture. Smart grid technology information platform architecture cloud computing include the following several levels and aspects (Yan Cui, 2015): First, that the platform infrastructure layer is the integration of the various hardware resources and related management capabilities of virtualized using virtual technology to achieve the corresponding hardware devices such as computers and network storage devices abstraction, and then complete the automation and optimization of resource data and load management; secondly, the main platform for the integration of the various layers of software

Smart grids (SG) are electricity grids that communicate with each other, provide reliable information, and enable administrators to operate energy supplies across the country, ensuring optimized reliability and efficiency. The smart grid contains sensors that measure and transmit data to adjust the flow of electricity automatically based on supply/demand, and thus, responding to problems becomes quicker and easier. This also plays a crucial role in controlling carbon emissions, by avoiding energy losses during peak load hours and ensuring optimal energy management. The scope of big data analytics in smart grids is huge, as they collect information from raw data and derive intelligent information from the same. However, these benefits of the smart grid are dependent on the active and voluntary participation of the consumers in real-time. Consumers need to be motivated and conscious to avail themselves of the achievable benefits. Incentivizing the appropriate actor is an absolute necessity to encourage prosumers to generate renewable energy sources (RES) and motivate industries to establish plants that support sustainable and green-energy-based processes or products. The current study emphasizes similar aspects and presents a comprehensive survey of the start-of-the-art contributions pertinent to incentive mechanisms in smart grids, which can be used in smart grids to optimize the power distribution during peak times and also reduce carbon emissions. The various technologies, such as game theory, blockchain, and artificial intelligence, used in implementing incentive mechanisms in smart grids are discussed, followed by different incentive projects being implemented across the globe. The lessons learnt, challenges faced in such implementations, and open issues such as data quality, privacy, security, and pricing related to incentive mechanisms in SG are identified to guide the future scope of research in this sector.

The most advanced power grid design, known as a ‘smart power grid’, integrates information and communication technology (ICT) with a conventional grid system to enable remote management of electricity distribution. The intelligent cyber‐physical architecture enables bidirectional, real‐time data sharing between electricity suppliers and consumers through smart meters and advanced metering infrastructure (AMI). Data protection issues, such as data tampering, firmware exploitation, and the leakage of sensitive information arise due to the smart power grid's substantial reliance on ICT. To maintain reliable and efficient power distribution, these issues must be identified and resolved quickly. Intrusion detection is essential for providing secure services and alerting system administrators in the case of adversary attacks. This paper proposes an intrusion classification scheme that identifies several types of cyber attacks on modern smart power grids. Grey‐Wolf metaheuristic optimization‐based feature selection is used to learn non‐linear, overlapping, and complex electrical grid properties. An extended deep‐stacked ensemble technique is advanced by putting predictions from weak learners (CNNs) into a meta‐learner (MLP). The outcomes of this approach are explained and confirmed using explainable AI (XAI). The publicly available dataset from Mississippi State University and Oak Ridge National Laboratory (MSU‐ORNL) is used to conduct experiments. The experimental results show that the proposed method achieved a peak accuracy of 96.6% while scrutinizing the original MSU‐ORNL data feature set and a maximum accuracy of 99% when analysing the selected feature set. Therefore, the proposed intrusion classification scheme may protect smart power grid systems against cyber security attacks.