基于自适应遗传算法的可用传输能力计算

Available Transfer Capability Calculation Based on Adaptive Genetic Algorithm

在常用的计算可用传输能力(ATC)问题的基础之上,构建了自适应遗传算法的ATC计算的数学模型,能够满足的前提是电力系统静态安全约束,构建出使负荷节点的所有有功增量的和达到最大值时的目标函数。在传统的遗传算法中采用混沌理论,这样做的目的是自适应改进了遗传算法,主要是为了解决传统的遗传算法的不足之处,改进后的遗传算法提高了算法的鲁棒性,对于迭代计算结果突破局部收敛的能力有所提升,采用改进遗传算法求解电力系统的ATC,不但可以大大改善计算特性,也可以有效提高计算效率和计算结果的精度。最后,以IEEE-30节点标准系统为例进行验证,剖析了自适应遗传算法的性能,验证了所建数学模型和自适应遗传算法的有效性,同时分析了自适应遗传算法在电力系统中ATC研究中急需解决的问题。

In this paper, the traditional genetic algorithm is improved based on the ATC algorithm. The mathematical model of the ATC is built based on the adaptive genetic algorithm. The main premise is the static security constraints of the power system, to build the load node in the receiving area of all the active increment and reach the maximum value of the objective function. In this paper, chaos theory is used in the traditional genetic algorithm to improve the adaptive genetic algorithm, which mainly solves the shortcomings of the traditional genetic algorithm. The improved genetic algorithm improves the robustness of the algorithm tor it can solve the ATC of the power system greatly, and can not only improve the calculation performance, but also improve the calculation efficiency and the accuracy of the calculation result. Finally, this paper takes the IEEE-30 node standard system as an example to verify the performance of the adaptive genetic algorithm, and validates the validity of the mathematical model and the adaptive genetic algorithm. Meanwhile, the adaptive genetic algorithm is applied to problems urgent to be solved in the ATC research of the power system.