遗传算法作为电力系统建模计算的工具

IF 0.4 Q4 MATHEMATICS, APPLIED
R. Solopov, A. Samulchenkov, Vladislav I. Ziryukin
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引用次数: 1

摘要

进化建模是人工智能的研究领域之一,其本质是从自然系统的存在、变异性和发展角度对计算过程的解释和整体计算算法构建的最终形式。由于自然选择原理的基本应用,所有的进化建模方法都具有最优化的性质。遗传算法(GA)是最常用的进化建模方法之一。它是以进化和自然选择的原理为基础,在保留生物术语的简化形式理论的基础上,自适应地寻找解决方案的方法。其实质是综合考虑遗传影响和外部环境的分析,在进化过程中通过适应度函数的值来确定最适合的个体(解)。尽管是生物学术语,遗传算法是一种通用的计算工具,可用于解决广泛的复杂问题,包括电力工业。由于电网络数学模型是一个高阶非线性方程组,考虑了所考虑对象的物理性质所施加的所有限制,因此作者考虑了在计算电网络稳态的框架中使用遗传算法的问题。由于运行电网的复杂性,其求解是一个相当费力的优化问题。该系统的正确求解是SS EN计算中最关键的阶段。这就是寻找SS - EN计算最优方法任务的重要性和紧迫性的原因。本文介绍了一种分析装置的研制成果,使利用基于专用软件的遗传算法求解电网稳态模式计算问题成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithm as a tool for modeling calculations of electric power systems
Evolutionary modeling is one of the areas of artificial intelligence, which essence is the computational processes interpretation and the final forms of integral computational algorithms construction from their existence, variability and development the points of view in natural systems. All evolutionary modeling methods are of an optimization nature due to the basic use of the theory of natural selection principles. One of the most common methods of evolutionary modeling is the genetic algorithm (GA). It is the method of adaptive search for solutions based on the principles of the evolution and the natural selection with the preservation of biological terminology in a simplified form theories. Its essence is to determine the most fit individual (solution) by the value of its fitness function during evolution, considering the analysis of the heredity influences and the external environment. Despite the biological terminology, genetical algorithms are a universal computational tool that can be used to solve a wide range of complex problems, including the electric power industry. The authors considered the issue of the genetic algorithm use in the framework of calculating the steady state of the electrical network (SS EN), since the mathematical electrical network model is a system of high-order nonlinear equations, where all the restrictions imposed by the physical properties of the object under consideration are taken into account. Its solution is a rather laborious optimization problem, due to the operating electrical networks complexity. The correct solution of this system is the most critical stage in the calculation of the SS EN. It is the reason for importance and urgency of the search for SS EN calculating optimal methods task. This paper presents the development results of an analytical apparatus that made it possible to search for a solution to the problem of calculating electrical networks steady-state modes using the genetic algorithm based on special software.
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CiteScore
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