Abstract
The complexity of the multiperiod dynamic unit commitment problem makes it difficult or even unviable to find the global optimal solution. Ordinal optimization provides a simulation‐based approach suitable for solving this kind of problem. It uses crude models and rough estimates to derive a small set of unit commitment schemes for which simulations are necessary and worthwhile to find good enough solutions with drastically reduced computational burden. The 10–100 thermal units standard test example and the case of an actual provincial power system with 128 units verify the feasibility of ordinal optimization to solve the large‐scale dynamic unit commitment problem. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
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