Collective and Computational Intelligence Techniques in Energy Management

Dear Colleagues,

During the previous decades, the increasing demand in the power sector was addressed mainly with generation capacity expansion. However, due to various factors such as installation, operation & maintenance costs, fuel unavaibility, enviromental limitations and others, the practice of building new plants is a not always conisidered as a cost-effective option. Energy management is an another way to cope with the rapidly increment of demand in the various sectors. Energy management is a general term that includes a family of methods that aim to reduce and/or modify the demand according to various targets set, such as generation cost reduction, congestion management in transmission systems, optimal generation resource allocation, bill savings for consumers and others. It is related with energy savings, energy efficiency and energy conservation. In regulated energy markets, usually a vertically integrated utility is responsible for the implementation of energy management methods. However, since many markets have been transforming to new competitive landscapes, energy management occupies regulatory authorities, utilities, transmission and distribution system operators, retailers, energy service companies, prosumers and others.

Energy management is a cornerrstone of the energy policies in many countries. This is evident by the large number of related research, innovation and demonstration projects, incentives, market regulations and others. In energy intensive industries, efficient energy management and energy audits have become very important and necessary respectively. In energy sector future projection studies, energy management is always taken into account. Thus, it holds and will continually to play a crucial role in modern day energy sectors.

Collective and compuational intelligence is a topic with numerous applications in scientific and engineering problems. It is a challenging task to explore the potential of collective and computational intelligence techniques for the design, implementation and evaluation of energy management methods in generation, transmission and distribution of electricity.

In this context, the main scope of this Special Issue is to collect new methods applicable in energy management in modern energy sectors. Review papers are welcomed. Multi-disciplinary research and cutting-edge approaches are invited in order to address the challenges raised by modern power systems and deregulated energy markets.

Prof. Dr. Georgios C. Christoforidis
Asst. Prof. Dr. Ioannis Panapakidis
Guest Editors

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• Computational intelligence methods for monitoring, control and optimization in generation, transmission and distribution systems
• Applied soft computing in control of energy management systems in industrial sector and buildings
• Energy management in hybrid power generation systems through artificial intelligence
• Demand side management in buildings and industries
• Bio-inspired and metaheuristics based algorithms in optimization of energy managements systems
• Energy efficiency, energy savings and demand response
• Big data analytics and data mining in energy management systems
• Deep learning and reinforcement learning for automated control in smart homes and smart buildings
• Energy management of renewable energy systems with storage
• Intelligent techniques in the energy management of microgrids and nanogrids with increased renewable energy sources penetration