Analysis and Development of Energy Management: Automotive and Stationary Applications
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".
Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 21288
Special Issue Editor
Interests: modelling and control of fuel cell systems (PEMFC, SOFC); electrolysers (PEM, SOEC) and redox flow batteries; hydrogen storage and transport; energy management systems: automotive applications; stationary applications; hybrid systems; combined heat and power systems
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Special Issue Information
Dear colleagues,
Energy consumption is growing day by day; in parallel, there is a transition to cleaner energy production systems. The new energy generation and consumption systems are increasingly complex, since they have a distributed nature, behavior that is not totally predictable, and hybrid characteristics, since different sources of energy usually coexist. Additionally, energy storage elements play a very important role. At present, there are a large number of them with very different characteristics. Handling these scenarios is a challenging problem.
Energy management systems play a decisive role in these new energy scenarios. Its correct operation is key to profit from available energy and minimize the use of fossil fuel.
The literature describes different ways to develop energy management systems; the main ones are heuristics, intelligent control, and optimal and predictive control, among others. An element that is usually present in all these algorithms is the technique for predicting generation and energy consumption. This prediction plays a key role in the optimal functioning of energy management systems.
In this special section, we intend to show energy management techniques applied to different energy systems.
Prof. Dr. Ramon Costa-Castelló
Guest Editor
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Keywords
- energy system modeling
- production/consumption prediction
- model predictive control in energy system
- heuristics in energy systems
- energy systems optimal control