A chaotic equilibrium optimization for temperature-dependent optimal power flow

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES

Smart Science Pub Date : 2023-02-07 DOI:10.1080/23080477.2023.2171696

T. M. Dao, Truong Hoang Bao Huy, Duy-Phuong N. Do, Dieu Ngoc Vo

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引用次数: 4

Abstract

ABSTRACT Optimal power flow (OPF) is one of the common problems in power systems. In general, the branch resistance of the system is assumed to be constant with respect to temperature variation in conventional optimal power flow. However, the temperature correlation of the branch resistance should be taken into account to enhance the accurate calculation of the power flow and branch losses. This paper suggests a new and efficient method, which is chaotic equilibrium optimization (CEO) to deal with the temperature-dependent optimal power flow (TDOPF) problem. The CEO is validated on IEEE 30-bus and 118-bus networks with different objective functions, including generating fuel cost, total active power losses, voltage profile enhancement, voltage stability improvement, and emission reduction. Furthermore, the temperature effect on the TDOPF problem is also analyzed. In the case of fuel cost optimization in the 30-bus network, fuel cost increases from 799.85 $/h to 802.9474 $/h when the temperature increases from 0°C to 100°C, corresponding to a fuel cost increase of 0.04% for each 10°C. From the obtained outcomes, the efficacy of the CEO has been proven in finding accurate solutions for the TDOPF problem. GRAPHICAL ABSTRACT

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温度相关最优潮流的混沌平衡优化

最优潮流(OPF)是电力系统中常见的问题之一。在传统的最优潮流中，通常假定系统支路电阻相对于温度变化是恒定的。但是，为了提高对潮流和支路损耗的准确计算，需要考虑支路电阻的温度相关性。本文提出了一种新的、有效的解决温度相关最优潮流问题的混沌平衡优化方法。该算法在IEEE 30总线和118总线网络上进行了验证，具有不同的目标函数，包括发电燃料成本、总有功损耗、电压分布增强、电压稳定性改善和减排。此外，还分析了温度对TDOPF问题的影响。以30总线网络的燃油成本优化为例，当温度从0℃升高到100℃时，燃油成本从799.85美元/h增加到802.9474美元/h，相当于每升高10℃，燃油成本增加0.04%。从获得的结果来看，CEO在寻找TDOPF问题的准确解决方案方面的有效性得到了证明。图形抽象

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Science Engineering-Engineering (all)

CiteScore

4.70

自引率

4.30%

发文量

期刊介绍： Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials