Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

SECURING THE INTEGRITY OF THE POWER DISTRIBUTION SYSTEM FOR SMART GRID APPLICATIONS

The distribution system is one of the main components in a smart grid, readings are transferred from the distribution substations to the control center. Compromising transferred system data will result in drawing wrong conclusions about current operation status at the control center. Which leads to sending wrong operational commands that may result in very serious consequences. Firstly, we propose a scalable communications architecture for future smart grid distribution systems (i.e. Security Aware Distribution System Architecture - SADSA). The architecture is adaptable to use Wi-Fi or other technologies to transfer smart grid information. The architecture is studied from various angles. Both communication and cybersecurity challenges are extracted. In addition, the work provides a detailed discussion on how the proposed architecture meets National Institute of Standards and Technology (NIST) cybersecurity requirements for smart grids. Secondly, we propose the False Data Injection Prevention Protocol - FDIPP, the protocol prevents packet injection, duplication, alteration and node replication. In other words, it guarantees both system and data integrity. The protocol was analyzed using formal security analysis. Furthermore, Network Simulator 2 is used to evaluate both SADSA and FDIPP. The simulation is used to measure the delay and security overhead introduced from FDIPP and the proposed architectur

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain

The role of the RPL routing protocol for smart grid communications

Advanced communication/networking technologies should be integrated in next-generation power systems (a.k.a. smart grids) to improve their resilience, efficiency, adaptability, and sustainability. Many believe that the smart grid communication infrastructure will emerge from the interconnection of a large number of small-scale networks organized into a hierarchical architecture covering larger geographic areas. In this article, first we carry out a thorough analysis of the key components of the smart grid communication architecture, discussing the different network topologies and communication technologies that could be employed. Special emphasis is given to the advanced metering infrastructure, which will be used to interconnect the smart meters deployed at customers\u27 premises with data aggregators and control centers. The design of scalable, reliable, and efficient networking solutions for AMI systems is an important research problem because these networks are composed of thousands of resource-constrained embedded devices usually interconnected with communication technologies that can provide only low-bandwidth and unreliable links. The IPv6 Routing Protocol for Low Power and Lossy Networks was recently standardized by the IETF to specifically meet the requirements of typical AMI applications. In this article we present a thorough overview of the protocol, and we critically analyze its advantages and potential limits in AMI applications. We also conduct a performance evaluation of RPL using a Contiki-based prototype of the RPL standard and a network emulator. Our results indicate that although average performance may appear reasonable for AMI networks, a few RPL nodes may suffer from severe unreliability issues and experience high packet loss rates due to the selection of suboptimal paths with highly unreliable links