The main goal of this task force is to promote the research on Computational Intelligence methods for their application to the energy production and consumption domain.
Sustainability is of great importance due to increasing demands and limited resources worldwide. In particular, in the field of energy production and consumption, methods are required that allow to produce (renewable) energy in an efficient way, as well as to develop methods for the efficient usage of energy. The vast extension of energy sources and the growing information structure allow a fine screening of energy resources, but also require the development of tools for the analysis and understanding of huge datasets about the energy grid. Key technologies in future ecological, economical and reliable energy systems are energy prediction of renewable resources, prediction of consumption as well as efficient planning and control strategies for network stability.
The arising problems can typically not be solved with traditional approaches, which is one of the reasons why computational intelligence methods have taken over a key role for planning, optimizing and forecasting sustainable systems. Typically, these approaches make use of domain knowledge in order to achieve the required goal. However, even in the case that explicit domain knowledge is not available, computational methods can also handle large raw numerical sensory data directly, process them, generate reliable and just-in-time responses, and have high fault tolerance.
The scope of this task force includes the following topics:
- Algorithms for modeling, control and optimization
- Prediction of wind and photovoltaic energy
- Prediction and monitoring of energy consumption
- Communication and control
- Demand side management
- Distributed energy resources
- Methods and algorithms for real-time analysis
- Planning, operation and control
- Network Restoration
- Plug-in vehicles
- Renewable energy
- Smart micro-grids
- Smart sensing