基于改进遗传算法的可用传输能力对比研究

根据可用传输能力（ATC）问题求解的特点,构建了基于标准遗传算法的ATC优化模型。目标函数为在满足系统的静态安全约束条件的基础上,使受电区域所有负荷节点有功功率增量累加达到最大。并通过对传统遗传算法的改进,采用了自适应遗传算法,并引入了混沌理论,加入了三角函数选择算子,有效改善了ATC的求解特性。最后,以IEEE-30节点系统为例,对遗传算法的性能进行剖析,验证了文中所建模型和算法的有效性。

Comparative Study of Available Transfer Capacity Based on Improved Genetic Algorithm

According to the features of available transfer capacity（ATC）,an ATC optimization model is constructed based on standard genetic algorithm.Considering the static safety constraints of power system,the objective function is the incremental cumulative maximum to all load node active power of the power-receiving area.Through improving the traditional genetic algorithm,the adaptive genetic algorithm and chaos theory are used,and using the trigonometric function selection operators the solution features of ATC are improved.At last,taking IEEE-30 bus system for example,the performance of genetic algorithm is analyzed,and it proves that both the proposed model and method are effective.