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Dear Colleagues,

It is hard to imagine a modern world without artificial intelligence. Currently, artificial intelligence surrounds us at every step. Its application is increasing not only in traditional application areas, but also in newer areas, including energy management systems, renewable energy conversion systems, electric aircraft, aviation, electric vehicles, unmanned propulsion systems, robotics, etc. One of the fundamental techniques used in applications of artificial intelligence are neural networks. Their properties show that they are a very good tool for all applications, also in energy management systems. They belong to the group of algorithmic methods used in solving complex non-linear problems. Neural networks are used in cases of partial or complete lack of knowledge of the rules describing objects or processes. The growing application of artificial intelligence, including neural networks, has accelerated research in the area of state monitoring and fault tolerance of all energy management systems, leading to the development of more reliable diagnostic techniques and more fault-tolerant systems. The changing approach to preferred energy sources, related to climate change, presents us with challenges related to the greater fluctuation of available production when generating energy from renewable sources. The available power output varies over time and may even drop to zero for extended periods of time. When increasing the share of renewable energy sources, this should be taken into account and various actions should be taken to limit the impact of these fluctuations on the comfort of energy consumers and to ensure that their needs are met. Geopolitical factors are also significant.
Thanks to the application of neural networks, it is possible to predict the energy consumption in a household or household network with a high degree of probability, which enables proper management of energy consumption. Neural networks are also able to model and predict the possibilities of energy generation by renewable energy sources based on weather data, which can help ensure the comfort of energy consumers and secure the satisfaction of their needs.

This special edition aims to present and disseminate the latest advances in the theory, design, modeling, application, control and monitoring of energy systems using artificial intelligence, including neural networks.
Topics of interest for publication include, but are not limited to:
•    Neural Network for Predicting in Energy Systems;
•    Energy management systems algorithms;
•    Predicting in Energy systems;
•    Energy consumption/production analysis, modeling and prediction by means of neural networks;
•    Energy-related services (e.g., prediction);
•    Data processing in Energy Management Systems;
•    Neural network models and relations in Energy Management Systems;
•    Novel applications in Energy Management Systems;
•    Advanced modelling approaches of Energy Systems;
•    User-oriented Energy Management Systems designs;
•    IoT—Internet of Things (industrial Internet of Things);
•    Deep learning (artificial intelligence);
•    Load forecasting;
•    Renewable energy sources;

More information 

Dr. Lukasz Sobolewski
Dr. Piotr Powroznik
Guest Editors