Description: a powerful approach to find the
optimal size and location of distributed generation units in a
distribution system using Genetic Optimization algorithm (GA).
The total active and reactive power losses are minimized and
voltage profile is improved. GA fitness function is introduced
including the active power losses, reactive power losses and the
cumulative voltage deviation variables with selecting weight of
each variable. GA fitness function is subjected to Voltage
Constraints, active and reactive power losses constraints Platform: |
Size: 2048 |
Author:saeed |
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Description: 遗传算法无功优化，与理论分析结果相比，窗函数法设计一个数字带通FIR滤波器。- Genetic algorithm based reactive power optimization, Compared with the results of theoretical analysis, A window function design FIR digital band-pass filter. Platform: |
Size: 4096 |
Author:曹金章 |
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Description: 遗传算法无功优化，与理论分析结果相比，多机电力系统仿真及其潮流计算。- Genetic algorithm based reactive power optimization, Compared with the results of theoretical analysis, Multi-machine power system simulation and flow calculation. Platform: |
Size: 7168 |
Author:drthicy |
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Description: 主要是基于mtlab的程序，遗传算法无功优化，与理论分析结果相比。- Mainly based on the mtlab procedures, Genetic algorithm based reactive power optimization, Compared with the results of theoretical analysis. Platform: |
Size: 7168 |
Author:fouliejen |
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Description: matlab上实现的前推回代算法，结合遗传算法，有效的电网系统无功功率的优化问题，采用的模型是22节点的电力系统模型。-Matlab implementation of the forward and backward generation algorithm, combined with genetic algorithm, an effective power system reactive power optimization problem, the model is a 22 node power system model. Platform: |
Size: 1165312 |
Author:Jorge |
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Description: 遗传算法(genetic algorithm，GA)是一种近年来发展起来的基于自然选择规律的进化算法，本程序利用改进型遗传算法对电力系统进行无功优化，与遗传算法进行比较，通过实际算例分析及MATLAB编程结果运行，成功解决了无功优化问题，并验证了改进型遗传算法的优越性。(The genetic algorithm (genetic algorithm GA) is an evolutionary algorithm based on natural selection rules developed in recent years, the improved genetic algorithm to optimize the reactive power of power system by using this program are compared with the genetic algorithm, through the example analysis and MATLAB programming results of operation, successfully solved the problem of reactive power optimization, and verify the superiority of the improved genetic algorithm.) Platform: |
Size: 58368 |
Author:naijgnaw1978
|
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Search - reactive power optimization with genetic algorithm