Title :
A multi-stage intelligent system for unit commitment
Author :
Ouyang, Z. ; Shahidehpour, S.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
fDate :
5/1/1992 12:00:00 AM
Abstract :
A heuristic approach to power system generation scheduling is discussed. The proposed short-term unit commitment employs a multistage neural network expert system approach to achieve real-time processing results. The operating constraints are presented as, heuristic rules in the system where a feasible solution is obtained through inference. The neural networks are used at the preprocessor and postprocessor stages. At the preprocessor stage, a load pattern matching scheme is used to retrieve an optimal schedule that represents the closest solution to the given load profile from the database. At the postprocessor stage, a trained neural network performs considerable adjustments to achieve the optimal solution
Keywords :
expert systems; inference mechanisms; load dispatching; load distribution; neural nets; optimisation; power system analysis computing; real-time systems; scheduling; database; expert system; heuristic rules; inference; load pattern matching; neural network; optimisation; postprocessor; power system analysis computing; power system generation scheduling; preprocessor; real-time processing; scheduling; unit commitment; Databases; Expert systems; Information retrieval; Intelligent systems; Neural networks; Optimal scheduling; Pattern matching; Power generation; Power systems; Real time systems;
Journal_Title :
Power Systems, IEEE Transactions on