Methods used to solve the unit commitment problem of power generating systems should give a solution which is both feasible and optimal, and should be flexible enough to be rapidly and easily reimplemented in response to a changing and unpredictable environment. An expert system is proposed which incorporates both heuristic and numerical optimization methods to achieve such a solution. The expert system acts like a preprocessor for data which is to be used by a Dynamic Programming routine to determine the most economical schedule of generating units. After the schedule has been generated, the expert system acts like a postprocessor to check the feasibility of the schedule and make recommendations for changes to achieve a better schedule.

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