Application of Scaling Genetic Algorithms Using MapReduce in Optimizing the Configuration of PMU

作者：Liu Zhi Jian^*; Wang Ming Yu; Wang Dong Dong

来源：China International Conference on Electricity Distribution (CICED), 2016-08-10 to 2016-08-13.

• Genetic algorithm
• state estimation
• Map/Reduce
• Optimal configuration
• PMU

Because the structure of power system is getting larger and more complex, the configuration of PMU become a more complicated problems. Some algorithms are used to optimize the configuration schemes and achieves anticipated goals , however some of them can not improve the measurement accuracy and increase the computational efficiency at the same time. In order to enhance the precision of state estimation and the efficiency of optimal configuration, this paper models genetic algorithm into the MapReduce model, so the MapReduce genetic algorithm(MRGA) possesses some parallel computing performance, such as scalability, better fitness convergence and so on. MRGA is implemented on computing clusters of Hadoop to search the optimal configuration of PMU. Meanwhile, this feasibility and the computing performance of MRGA is verified by IEEE14-node system, IEEE118-node system, and Wp2383-node system. This method has significant advantages in the installed PMU number, the diversity of solution, the astringency and the practicability.

• 出版日期2016
• 单位昆明学院