Dear Colleagues,

Today, the energy network is a complex structure, with extreme events triggered by natural disasters or user actions occurring and causing a temporary shortage or excess of power. Moreover, user actions lead to a peak demand event, and institutions managing energy networks try to react to any situations on an ongoing basis. However, the variety of energy appliance and generations from renewable energy sources complicates the process of energy management in a classic way. Attempts are underway to balance the energy demand and supply through the use of various types of algorithms. There are also problems with maintaining an appropriate energy quality, which must also be solved with the use of smart devices and various control algorithms. In addition, modern devices such as static compensators, smart transformers and energy storage are applied in the power grid. Controlling these devices also requires the use of advanced control algorithms and algorithms for selecting the place of their installation and parameters. Among other things, heuristic algorithms are used to solve NP-difficult problems. Artificial intelligence is also used, and all new control methods are based on managing the smart appliances group and intelligent energy storage.

This Special Issue is dedicated to interdisciplinary research in the area of elastic energy management systems and power quality in smart grids. This Special Issue covers topics including, but not limited to, the following:

• Energy management systems;
• Energy storage systems;
• Power quality;
• Hybrid electric vehicles;
• IoT—Internet of Things (industrial Internet of Things);
• Deep learning (artificial intelligence);
• Load forecasting;
• Distributed and network measurement systems;
• Energy parameter monitoring systems (smart metering);
• Application of IT tools in measuring instruments and systems;
• Sensors and measuring transducers: concepts, structures and research;
• Smart metering and smart grid;
• Systems embedded in measuring equipment;
• Cloud computing and machine learning;
• HVAC;
• Cyber physical systems;
• Big data analysis in smart grid applications;
• Renewable energy sources;
• Power converter control algorithms in smart grid applications.

Prof. Dr. Paweł Szcześniak
Dr. Piotr Powroźnik
Guest Editors

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