Intelligent Subset Selection of Power Generators for Economic Dispatch
This addresses the need for sustainable and economical power generation, but appears incremental as it applies deep learning to a known domain-specific task.
The paper tackles the problem of optimal generator subset selection for economic dispatch by simulating grid conditions and training a deep learning model, achieving highly encouraging results.
Sustainable and economical generation of electrical power is an essential and mandatory component of infrastructure in today's world. Optimal generation (generator subset selection) of power requires a careful evaluation of various factors like type of source, generation, transmission & storage capacities, congestion among others which makes this a difficult task. We created a grid to simulate various conditions including stimuli like generator supply, weather and load demand using Siemens PSS/E software and this data is trained using deep learning methods and subsequently tested. The results are highly encouraging. As per our knowledge, this is the first paper to propose a working and scalable deep learning model for this problem.