Intelligent and Converged Networks

This Special Issue (SI) presents a comprehensive study and assessment of the state-of-the-art research and development related to the unique needs of electrical utility grids, including operational technology, IT, storage, processing, communication systems, technical and economic solutions for the attainment of a future electric smart grid model. A notional objective of bringing a big data framework to smart grids confronts several potential issues and pitfalls in terms of electric grid infrastructure, architecture, interfacing, standardization, protocols, security, reliability, communication, grid optimization, and sustainable strategies for smart grids.

This SI aims to present the detailed research carried out in the field of information technology and communication systems in smart cities, smart grids, and large-scale power systems. Different planning, operational and implementation aspects are fully incorporated. Moreover, this SI broadly covers the role of a big data framework for smart grids which derives useful information from past data to schedule future operations and maintenance, provides information of potential major threats, current and future trends in development and implementation, system security, architectural frameworks, various standardization levels, integrated system modelling and optimization methods, operational and economical aspects, etc. The SI examines research limitations and presents recommendations for further research to incorporate big data analytics into power system design and operational frameworks. The interactions of this framework with the smart grid as a future energy system model and related methods are extensively debated and research solutions are exposed as possible solutions in the context of reaching greater integration.

Additionally, this SI also provides a detailed state-of-the-art analysis of big data analytics and its uses in power grids, as well as problems and opportunities from the viewpoints of utilities, enterprises, and research organizations.

Current advancements towards future smart grids will necessitate the collection and analysis of data from integrated devices such as distributed storage, intelligent loads, and distributed energy resources. However, the vast volumes of data generated by smart grids must be adequately handled in order to improve a grid's efficiency, dependability, and sustainability. This is a big data problem that necessitates modern informatics approaches and cyber-infrastructure to cope with massive amounts of data and its analyses. Surprisingly, big data accurately represents the real nature of smart grids. The enormous volume of data necessitates an effective platform that propels the smart grid forward in the big data era. All these problems and their prospective solutions are being discussed in different sections of the SI.

This SI also describes how the framework has been used to display energy in two scenarios: a single house and a smart grid with over thousands of smart meters. The use of the two scenarios is to show grid status and enable dynamic demand responses implying that the same framework may be used to do more smart grid data analyses.

Topics of interests include, but are not limited to:

• Smart IoT data collection, integration and processing;
• AI-powered big data mining and analyses for IoT;
• Machine learning and deep learning for advanced IoT applications;
• Blockchain-based smart contracts and protocols for IoT;
• Intelligent prediction and recommendation for IoT decision-making;
• Novel big data analytics technology for IoT security;
• Data confidentiality and privacy protection for IoT;
• Lightweight IoT data transmission and communications;
• Authentication and access control for data usage in IoT;
• Experiments, testbeds and prototyping systems for IoT security;
• Data-driven intelligence-supported approaches and technologies;
• Data-driven intelligence-supported applications and systems;
• Green technologies;
• Sustainability;
• Artificial intelligence;
• Communications and networking;
• Convergence of communications, computing and systems;
• Relevant algorithms, approaches, analyses and modelling;
• Machine learning;
• Data analytics;
• Big data;
• Big data meets green challenges;
• Sustainability development goals;
• Energy and energy efficiency issues;
• Resource and resource efficiency issues;
• Environmental concerns and protections.

Important dates

• Deadline for submissions: 30 April 2023
• 1st round of acceptance notification: 30 May 2023
• Submission of revised papers: 15 June 2023
• 2nd round of acceptance notification: 15 July 2023
• Publication online (tentative): 15 July 2023

Guest Editors

• Prof. Yousef Farhaoui (Leading Guest Editor), FST, Moulay Ismail University, Morocco

Email: y.farhaoui@fste.umi.ac.ma

• Prof. Tanzila Saba, Prince Sultan University, Saudi Arabia

Email: tsaba@psu.edu.sa

• Prof. Anshul Verma, Institute of Science, Banaras Hindu University, India

Email: anshulverma87@gmail.com

• Prof. Hamed Taherdoost, University Canada West, Canada

Email: hamed.taherdoost@gmail.com