Description: 粒子群加连续潮流法，能优化变压器分接头，进行多变量优化，使系统非常稳定-PSO plus continuous power flow, transformer taps can be optimized, multi-variable optimization, making the system very stable Platform: |
Size: 31744 |
Author:周礼 |
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Description: 以网损为目标函数，对IEEE-33节点系统进行电容的位置寻优和容量寻优以及变压器分接头的寻优。-The net loss for the objective function, IEEE-33 node system capacitance position optimization and capacity optimization and transformer taps optimization. Platform: |
Size: 93184 |
Author:King |
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Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorithms in improving the classification accuracy of SVM for
condition assessment of power transformer. Platform: |
Size: 985088 |
Author:pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applic Platform: |
Size: 1890304 |
Author:pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorit Platform: |
Size: 930816 |
Author:pse |
Hits:
Description: This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are particle swarm optimization algorithm (PSO) and genetic
algorithm optimization (GA). These two optimization algorothms
are used for efficiently and effectively determine the optimal
parameters for SVM. The resulatant two hybrid algorithms, i.e.
SVM-PSO and SVM-GA can improve the performances of the
original SVM algorithm on classifying the incipient faults in
power transformers. Extensive case studies and statistic
comparison among the original SVM, SVM-PSO, and SVM-GA
over multiple datasets are also provided. Calculation results may
demonstrate the effectiveness and applicability of the two hybrid
algorithms in improving the classification accuracy of SVM for
condition Platform: |
Size: 670720 |
Author:pse |
Hits:
Description: IEEE六节点无功优化算法的matlab程序，以整个系统有功网损作为优化目标，通过改变节点注入无功以及变压器变比来求解所对应的有功网损，从而达到优化目标-IEEE six-node reactive power optimization algorithm matlab program, active power loss to the entire system as the optimization objectives, as well as injecting reactive power transformer to solve than the corresponding active power loss by changing the node, so as to optimize target Platform: |
Size: 2048 |
Author:邓立华 |
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Description: The paper presents an in situ parameter estimation method to determine the equivalent circuit parameters of the three-winding
transformer (TWT). The suggested method also estimates geometrically a complex parameter that is mutual leakage between
secondary and tertiary windings, which would be useful in transient studies. Beside the saturation effect of the transformer is taken
into account by estimating a highly nonlinear parameter that is magnetizing circuit reactance. Different search based optimization
tools are applied for parameter estimation among which the results obtained using genetic algorithm is found to be encouraging.
Load test data at one particular operating point namely supply voltage, load currents, input power, and load impedance is suffi cient
to estimate the parameters. Platform: |
Size: 129024 |
Author:fouzirock |
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Description: In this file Dynamic simulation of the IEEE 14 bus test case network, with
physical synchronous machine models and photovoltaic inverters (renewable sources).is done in eigenvalue m file. A delta delta transformer modeling is done in the deltadelta simulink model. An optimization in the presence of demand response and wind power with real time pricing method is done in the RTPdemandwind file. The bnn2013anew simulink model is a model of AC grid with Dc load. Platform: |
Size: 54272 |
Author:vivi68
|
Hits:
Search - transformer optimization