Application of neural networks in generation scheduling with fuzzy data
- Illinois Inst. of Tech., Chicago, IL (United States). Dept. of Electrical and Computer Engineering
In this paper a new method which is noted as FANN+ES is proposed to solve unit commitment problems. We adopt an artificial neural network (ANN) enhanced by the fuzzy set concept to obtain an initial solution near the optimal operating point, and use an expert system (ES) to refine the initial solution. The ANN in this study is a three-layer network with back-propagation and supervised learning schemes. The training information in ANN is the typical daily unit commitment schedule. As the output of ANN consists of various possibilities for unit states and the load curve contains forecasting errors, the fuzzy set concept is employed successfully in this algorithm. The fuzzy variables are load demands, strategy costs and ANN output unit combinations. The application of expert system which has 26 rules in the knowledge base is an efficient way to improve the initial solution and obtain an economical operation schedule. Although the inclusion of fuzzy set will increase the execution time of the analytical methods for unit commitment it can be merged with the training process of ANN which is off-line and yet provide the scheduling output in seconds. The case studies indicate that the FANN ES can present a more economical solution than ANN ES, without increasing the computation time.
- OSTI ID:
- 5080201
- Report Number(s):
- CONF-9104106-; CODEN: PAPWA
- Journal Information:
- Proceedings of the American Power Conference; (United States), Vol. 53; Conference: 53. annual American power conference, Chicago, IL (United States), 29 Apr - 1 May 1991; ISSN 0097-2126
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
LOAD MANAGEMENT
COMPUTERS
POWER SYSTEMS
ALGORITHMS
ARTIFICIAL INTELLIGENCE
ELECTRIC POWER
EXPERT SYSTEMS
MATHEMATICAL LOGIC
NEURAL NETWORKS
SCHEDULES
ENERGY SYSTEMS
MANAGEMENT
POWER
240100* - Power Systems- (1990-)
990200 - Mathematics & Computers