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[Other systemsGASATS_Hybrid_Algorithms_for_Reactive_Power_Optimi

Description: 关于电力系统无功优化方面的论文,使用GA/SA/TS三种混合的方法进行优化。-With regard to reactive power optimization papers, the use of GA/SA/TS hybrid three optimization methods.
Platform: | Size: 432128 | Author: xiaofang | Hits:

[Mathimatics-Numerical algorithmsGA

Description: 基于人工免疫算法的变电站电压无功综合控制-Based on artificial immune algorithm integrated voltage and reactive power control
Platform: | Size: 2048 | Author: 许水燕 | Hits:

[AI-NN-PRga

Description: 求解电力系统无功优化的改进遗传算法程序,程序效率高,推荐-Solving reactive power optimization of improved genetic algorithm
Platform: | Size: 4096 | Author: 常安 | Hits:

[AI-NN-PRga

Description: 用遗传算法解决无功优化问题的MATLAB源程序-Using genetic algorithms to solve reactive power optimization MATLAB source
Platform: | Size: 2048 | Author: 蔡峰 | Hits:

[Software EngineeringTuned-statcom-for-voltage-control-a-reactive-powe

Description: In this paper Static Synchronous Compensator (STATCOM) is used for voltage stability and the compensation of reactive power. The STATCOM contains an Insulated Gate Bipolar Transistor (IGBT) based voltage source converter for voltage control and reactive power compensation. The STATCOM is used to control the reactive power with the voltage source converter in combination with a DC voltage source. The values of the DC link capacitor and battery source were optimized using the Genetic Algorithm technique and the simulations results for the same were observed under the inductive as well as capacitive load conditions. The comparison of voltage compensation for various conditions show that the performance of STATCOM tuned with GA was the best and closest to the nominal value of voltage. The simulation is done in MATLAB for STATCOM and Voltage Source Converter (VSC).
Platform: | Size: 391168 | Author: alok | Hits:

[AI-NN-PRga

Description: 用遗传算法进行无功优化,IEEE33节点实例-Reactive power optimization using genetic algorithm, the the IEEE33 nodes instance
Platform: | Size: 5120 | Author: liuheng | Hits:

[matlabjiyu-GA-wugongyouhua

Description: 基于MATLAB遗传算法的无功优化程序,有一定的实用性-MATLAB genetic algorithm-based reactive power optimization procedures, there is a certain practicality
Platform: | Size: 8192 | Author: getao | Hits:

[Software EngineeringGA-on-pso-

Description: 基于遗传算法的电力系统无功优化的C语言程序-Power system based on genetic algorithm optimization of reactive C language program
Platform: | Size: 12288 | Author: wanghan | Hits:

[Energy industryDSP1

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 | Hits:

[Othermatlab-daima

Description: 包括:6机组系统的分布式梯度算法代码;基于GA的21节点无功优化;基于GA的二次型优化;matlab高级指令;依据matpower进行潮流计算中JJ矩阵的求解。-Comprising: a distributed gradient algorithm code 6 Unit System optimization based on GA 21 nodes reactive power quadratic optimization based on GA matlab advanced instruction matpower flow calculation based on the JJ matrix solver.
Platform: | Size: 9216 | Author: 曹驰 | Hits:

[matlabyichuansuanfawugong

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 | Hits:

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