基于遗传算法的分布式发电机组集成配电网配置优化

R. Syahputra, I. Soesanti
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摘要

化石燃料的局限性使得可再生能源系统越来越受欢迎。发电厂通常被集成到一个称为分布式发电机(DG)的配电网络中。配电网中DG的集成使配电网方案发生了变化。我们需要在DG在场的情况下做一些重新规划,以改善分销网络的性能。本文讨论了应用遗传算法(GA)方法进行优化,以提高网络性能。DG的存在使配电网更具活力。具有避免局部极小值能力的遗传算法是解决现有问题的有效方法。系统在IEEE 69总线网络模型上进行了测试。结果表明,遗传算法在提高母线电压质量的同时,能够实现配电网的优化,显著降低了电力损耗。
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An Optimization of Power Distribution Network Configuration with Distributed Generator Integration Using Genetic Algorithm
The limitations of fossil fuels make renewable energy system increasingly popular. The power plant is usually integrated into an electric power distribution network called a distributed generator (DG). The integration of DG in the distribution network makes the network scheme change. We need to do some re-planning with the presence of DG to improve distribution network performance. This paper discusses applying the genetic algorithm (GA) method for optimization to improve the network performance. The presence of DG makes the distribution network more dynamic. The GA method with the ability to avoid local minima is the answer to the existing problems. The system test was carried out on an IEEE 69-bus network model. The results showed that the GA method was able to produce distribution network optimization with a significant reduction in power losses while at the same time increasing the quality of the bus voltage.
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