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Titlebook: Computational Intelligence in Power Engineering; Bijaya Ketan Panigrahi,Ajith Abraham,Swagatam Das Book 2010 Springer-Verlag Berlin Heidel

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樓主: broach
21#
發(fā)表于 2025-3-25 07:20:33 | 只看該作者
22#
發(fā)表于 2025-3-25 08:47:06 | 只看該作者
Robust Design of Power System Stabilizers for Multimachine Power Systems Using Differential Evolutiltimachine power systems. The eigenvalue analysis and the nonlinear simulation results show the robustness and the effectiveness of the DEPSSs to damp out the local as well as the interarea modes of oscillations and work effectively over a wide range of loading conditions.
23#
發(fā)表于 2025-3-25 14:23:20 | 只看該作者
Neural Network Ensemble for 24-Hour Load Pattern Prediction in Power System,al predictor has the form of another neural network. The developed system of prediction was tested on the real data of the Polish Power System. The results have been compared to the appropriate values generated by other methods.
24#
發(fā)表于 2025-3-25 19:20:03 | 只看該作者
A Metaheuristic Approach for Transmission System Expansion Planning, results for three sample test system are obtained to show the potential of the tested algorithm. The results obtained with HS are compared with basic binary GA to confirm the effectiveness of HS in terms of solution quality and number of fitness function evaluations required.
25#
發(fā)表于 2025-3-25 22:07:10 | 只看該作者
M. A. Dutrée,R. A de Man,M. A. Jebbinkand binary assumptions about state of the system, i.e. either in success state or in failed state. Hence classical reliability models are also known as probabilistic binary state (PROBIST) model [1-3].
26#
發(fā)表于 2025-3-26 01:27:41 | 只看該作者
27#
發(fā)表于 2025-3-26 04:50:58 | 只看該作者
28#
發(fā)表于 2025-3-26 09:07:15 | 只看該作者
29#
發(fā)表于 2025-3-26 14:44:47 | 只看該作者
30#
發(fā)表于 2025-3-26 16:59:38 | 只看該作者
An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration,better edges during hypermutation. An added innovation is the use of the pheromones to obtain quick solutions to restore the distribution system under contingency situations. The hybrid approach has been successfully implemented on two test networks. The results obtained demonstrate the efficacy of the algorithm.
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