Sensors - Special Issue 2024 : Advances in Sensor Technologies for Microgrid and Energy Storage

Dear Colleagues,

With the extensive application of rooftop photovoltaic cells for supplying electrical energy for domestic as well as industrial consumption, the micro-grid is an emerging technology that is supporting significant transformation in economies and social networks worldwide. In the power system, various regional and state grid systems have begun to transition from being consumers of electricity to producing, sharing, and storing energy by deploying a smart micro-grid infrastructure.

The purpose of this Special Issue is connect researchers from various areas, all working on solving the challenges present in the application of the smart micro-grid in energy storage and monitoring, via smart sensors and sensing technology, in order to make the power supply network robust and failsafe. The aim is to discuss the following topics: (i) the development of smart sensors, sensing technology, WSN and the IoT for micro-grid and energy storage applications; (ii) recently developed machine learning and data mining techniques that can be employed to address the challenges of micro-grid integration; and (ii) practical research directions in the machine learning and artificial intelligence community in the area of micro-grid and energy storage.

Topics of interest include, but are not limited to, the following:

-Smart sensors, sensing technology, sensors network in the smart micro-grid applications.
-Hardware design of smart grids and energy storage system.
-Challenges in the design, development and integration of smart energy storage systems.
-Micro-grid identification and design.
-Micro-grid energy management and control.
-IoT-enabled smart sensor design, evaluation, and technologies for micro-grid and energy storage systems.
-Machine learning and statistical methods for data mining in the domain of the micro-grid.
-Power generation forecasts of renewable energy sources, storage and integration via micro-grids.
-Integration of renewable energy sources into existing power grid and stability analyses.
-Mining from the heterogeneous data sources of the micro-grid environment, including spatio-temporal, time-series, streaming, graph, and multimedia data.
-Optimal placement and sizing of distributed generation sources in distributed micro-grid networks.
-The analysis and design of micro-grid resilience.
-Data mining for modeling and visualizing a micro-grid problem.
-Decision-making and problem-solving networks in micro-grids.
-Expert and knowledge-based systems for micro-grid development.
-Security, privacy, and trust in micro-grid and energy storage environments.
-Lightweight encryption and decryption algorithms that ensure micro-grid network security.
-Cloud computing for IoT technology in micro-grid environments
-Blockchain-based solutions for micro-grid and energy storage environments.
-Design of next-generation systems using smart sensors for micro-grids and energy storage.
-Architectures and algorithms for micro-grids and energy storage systems.
-Automatic learning techniques in micro-grid security systems, smart grid networks and energy storage systems.

We particularly encourage the submission of articles attending to emerging topics of critical importance, such as smart sensing, wireless sensor networks, the Internet of Things, machine learning, deep learning, big data mining and analytics, smart grid systems, energy storage, renewable energy integration, heterogeneous data integration, and mining.

Prof. Dr. Aman Maung Than Oo
Prof. Dr. Subhas Mukhopadhyay
Guest Editors