利用带有中性系数的几何程序设计选择伊拉克城市变电站 (TS) 的最佳供电半径

Ahmed K. Essa, Montifort Blessings Andrew Mitungwi, Tuweh Prince Gadama, Ahmed A. Salama
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引用次数: 0

摘要

由于电力系统的规模、复杂性、地理分布以及不可预见事件的影响,各种电力系统问题中存在着众多的不确定性,这使得基于脆集理论的传统数学工具难以对许多电力系统问题产生影响并加以解决。因此,作为数学不确定性技术的一个新分支,中性专家系统方法随着电力系统的发展应运而生,并在正确联系后被证明是成功的。专家通常使用模糊语言或中性语言来描述他们的经验知识,如 "很有可能"、"很有可能"、"如果 x 较大,则 y 很有可能发生"、"x 不应小于 a "等。为了设计变电站的最佳供电半径,本文提出了一种创建初等和二重中性几何编程问题的新方法。文章还提供了一个数值示例,以评估近似最优经济供电半径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Choosing Optimal Supply Radius of Transformer Substations (TSs) in Iraq’s Cities Using Geometric Programming with Neutrosophic Coefficients
Numerous uncertainties exist in various electricity power system problems due to the size, complexity, geographical distribution, and influence of unforeseen events in these systems, making it difficult for traditional mathematics tools based on crisp set theory to have an impact on and solve many power system problems. As a new branch of mathematical uncertainty techniques, the neutrosophic expert systems approach has therefore emerged with the development of electric power systems and has proven successful when correctly linked. The expert typically uses ambiguous or neutrosophic language to describe their empirical knowledge, such as "very likely," "quite likely," "if x is large, then y is very likely to occur," "x should not be less than a," etc. To design an optimal radius of power supply in the electrical transformer substation, this article presents a new method for creating primal and dual neutrosophic geometric programming problems. It also provides a numerical example to evaluate the approximate optimal economic power supply radius.
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