A novel iron loss reduction technique for distribution transformers based on a combined genetic algorithm-neural network approach

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 31, Issue 1, 2001, Pages 16-34

  Georgilakis, Pavlos S ^a,c   Doulamis, Nikolaos D ^b,c   Doulamis, Anastasios D ^b,c   Hatziargyriou, Nikos D ^b,c   Kollias, Stefanos D ^b,c  

^a Schneider Electric AE   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c IEEE   (Greece)

Author keywords

Core grouping process; Decision trees; Genetic algorithms; Intelligent core loss modeling; Iron loss reduction; Neural networks

Indexed keywords

CORE GROUPING PROCESS; DECISION TREES; INTELLIGENT CORE LOSS MODELING; IRON LOSS REDUCTION;

ADAPTIVE ALGORITHMS; COST EFFECTIVENESS; DECISION THEORY; GENETIC ALGORITHMS; MAGNETIC CORES; MAGNETIC LEAKAGE; MATHEMATICAL MODELS; NEURAL NETWORKS;

ELECTRIC TRANSFORMERS;

EID: 0035245093     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/5326.923265     Document Type: Article

References (32)

1. Increasing distribution transformer efficiency: Potential for energy savings
2. An equivalent magnetization surface current approach of calculation 3D-leakage fields of a transformer
3. Calculation of spatial loss distribution in stacked power and distribution transformer cores
4. Performance parameters on power transformers using 3D magnetic field calculations
5. Experimental investigation on effect of core production attributes on transformer core loss performance
6. A generalized transformer model based on the analysis of its magnetic circuit
7. Three phase transformer modeling for fast electromagnetic transients
8. Linear statistical model for the prediction of transformer iron losses
9. Statistical quality control of the transformer core production process
10. Iron loss prediction of individual cores and transformers using the linear statistical model
11. Contribution of artificial intelligence techniques in the reduction of distribution transformer iron losses
12. Creation of an efficient computer-based environment for the reduction of transformer industrial cycle
13. Quality improvement of individual cores of distribution transformers using decision trees
14. Learnability and the vapnik-chervornenkis dimension
15. Objective functions for training new hidden units in constructive neural networks
16. An adaptive least squares algorithm for the efficient training of artificial neural networks
17. Automatic learning methods to dynamic security assessment
18. Entropy and correlation: Some comments
19. An adaptively trained neural network
20. On line retrainable neural networks: Improving the performance of neural networks in image analysis problems
21. A dynamically trained neural network for machine vision applications
22. Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space, Part I: Basic properties of selection and mutation
23. Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization
24. Convergence analysis of canonical genetic algorithms