Is learning for the unit commitment problem a low-hanging fruit?

The blast wave of machine learning and artificial intelligence has also reached the power systems community, amid frenzy methods black-box tools that have been left in its wake, it is sometimes difficult to perceive a glimmer Occam’s razor principle. In this letter, we use unit commitment problem (UCP), an NP-hard mathematical program fundamental system operations, show simplicity must guide any strategy solve it, particular those are based on from past UCP instances. To end, apply naive algorithm produce candidate solutions show, using variety realistically sized systems, able find optimal or quasi-optimal with remarkable speedups. best our knowledge, first work technical literature quantifies how challenging solution actually for real-size systems. Our claim thus sophistication method be backed up statistically significant improvement results letter.