Intelligent priority based generation control for multi area system

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES
Prince Kumar, K. Kumar, Aashish Kumar Bohre, Nabanita Adhikary
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引用次数: 1

Abstract

ABSTRACT Increased innovation and automation for higher comfort level of living beings have stressed power sector for more units of power to be generated and supplied. To meet this demand, several generating stations are needed to be connected to supply this enormous load to end consumers. While interconnecting generated power of multi-area system, several problems are being encountered. In the current proposed work, 2-area interconnected power system has been considered and automatic generation control problem for single area loading and multi-area multi-type loading has been solved with the help of intelligent control strategy using TLBO algorithm. The proposed work has been processed and simulated in MATLAB and SIMULINK environment. Three types of loadings are considered in the proposed work. First one is single area fixed loading, second one is both area loading with different fixed load, and third one is increasing type load for fixed duration of time in single area. Based on the nature of severity of disturbances in power network, a fitness function has been designed for these multi-type of loadings to improve its transient response to avoid failure of synchronism and improve resiliency of power network to supply uninterrupted power to end consumers.
基于智能优先级的多区域系统发电控制
摘要:为了提高生活舒适度,不断增加的创新和自动化给电力部门带来了压力,使其能够生产和供应更多的电力。为了满足这一需求,需要连接几个发电站,以向最终消费者提供这一巨大负荷。在实现多区域系统发电互联的同时,也遇到了一些问题。在目前的工作中,考虑了两区域互联电力系统,并利用TLBO算法的智能控制策略解决了单区域负荷和多区域多类型负荷的自动发电控制问题。在MATLAB和SIMULINK环境中对所提出的工作进行了处理和仿真。拟建工程考虑了三种类型的荷载。第一种是单区域固定荷载,第二种是不同固定荷载的两种区域荷载,第三种是在单区域内固定时间的递增型荷载。基于电网中扰动严重性的性质,为这些多种类型的负载设计了适应度函数,以改善其瞬态响应,避免同步故障,并提高电网向终端用户提供不间断电力的弹性。
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来源期刊
Smart Science
Smart Science Engineering-Engineering (all)
CiteScore
4.70
自引率
4.30%
发文量
21
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
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