Application of AI, IoT, and Blockchain in Smart Grids with Distributed Energy Resources

Dear Colleagues,

In the last decade, the smart grid concept has become well known for the digitalization of the energy sector. A smart grid is an energy network/grid enabling a two-way flow of energy and data. It represents an unprecedented opportunity to move the energy industry into a new era of efficiency, availability, and reliability that will contribute to solving both environmental and economic issues. Smart grid has facilitated the integration of distributed energy resources (DERs) into power systems. In addition, the demand response has been used under the smart grid concept. However, communication between all the available components in smart grids is a major challenge. Hence, big data analysis and the internet of things (IoT) are more important than ever before for the development of smart grids.

Artificial intelligence (AI) is an important technology driver for smart grids. AI techniques have attracted much attention for data analysis and decision making in smart grids. The outstanding features of these techniques make them a powerful tool for solving complex engineering problems with large state spaces. AI can provide unique solutions for power grid balance, energy consumption analysis, and energy production. AI techniques enable decision making with speed and accuracy. To this end, they use massive amounts of data to create intelligent algorithms that can handle tasks requiring human intelligence. The most common methods for achieving AI systems are fuzzy logic, expert systems, neural networks, and natural language processing.

Topics of interest for this Special Issue include, but are not limited to, the following:

• AI for transactive energy
• Energy management by blockchain in smart grids
• Planning and operation of smart grids
• Demand response for increasing the penetration level of DERs
• AI for optimization of smart grids
• Internet of things in smart grids operation
• AI for peer-to-peer energy sharing
• Intelligent control of microgrids
• Resiliency, reliability, and security enhancement of smart grids
• AI for energy demand and generation forecasting in the power market
• AI for battery lifetime estimation in smart grids
• Smart grid flexibility improvement by AI
• AI application for electric vehicle integration in smart grid
• AI for integration of distributed energy resources

Dr. Rahmat Khezri
Dr. Amin Mahmoudi
Dr. Ali Bidram
Dr. Mostafa Shaaban
Dr. Solmaz Kahourzade
Guest Editors

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