A multi-stage intelligent system for unit commitment Export

@article{citeulike:715642, 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}, author = {Ouyang, Z. and Shahidehpour, S. M.}, citeulike-article-id = {715642}, citeulike-linkout-0 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=141769}, journal = {Power Systems, IEEE Transactions on}, keywords = {energy, expert-systems, neural-nets, not-helpful, unit-commitment}, number = {2}, pages = {639--646}, posted-at = {2006-06-29 13:13:13}, priority = {2}, title = {A multi-stage intelligent system for unit commitment}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=141769}, volume = {7}, year = {1992} }

TY - JOUR ID - citeulike:715642 L3 - citeulike-article-id:715642 N2 - 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 IS - 2 JF - Power Systems, IEEE Transactions on EP - 646 TI - A multi-stage intelligent system for unit commitment VL - 7 SP - 639 KW - energy KW - expert-systems KW - neural-nets KW - not-helpful KW - unit-commitment AU - Ouyang, Z AU - Shahidehpour, SM PY - 1992/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=141769 ER -