Recent and prospective developments in power system control centers: Adapting the digital twin technology for application in power system control centers

Brosinsky, Christoph; Westermann, Dirk; Krebs, R.

doi:10.1109/energycon.2018.8398846

Cited by 123 publications

(53 citation statements)

References 37 publications

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“…The data collected can be used for data analytics and monitoring. The scope for Digital Twins is becoming more viable as the development of smart cities increases connectivity and the amount of usable data [19] [20] [21] [22].…”

Section: ) Smart Citiesmentioning

confidence: 99%

Digital Twin: Enabling Technologies, Challenges and Open Research

et al. 2020

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Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

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Section: ) Smart Citiesmentioning

confidence: 99%

Digital Twin: Enabling Technologies, Challenges and Open Research

et al. 2020

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“…In a major shift of research trends, the development of digital twin (DT) has effortlessly increased the connectivity between the physical environment, their data, and virtual machines. This technique created an approach for synchronization, monitoring, and other services of the energy systems in real time through a computerized and virtual world modeling [168,169]. This approach is supported with a visualization software [170], and uses intelligent analytics along with the real-time data [169,171] to gather the information about the system operating state [172].…”

Section: Application Of Ai For Reliabilitymentioning

confidence: 99%

A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems

et al. 2021

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The use of artificial intelligence (AI) is increasing in various sectors of photovoltaic (PV) systems, due to the increasing computational power, tools and data generation. The currently employed methods for various functions of the solar PV industry related to design, forecasting, control, and maintenance have been found to deliver relatively inaccurate results. Further, the use of AI to perform these tasks achieved a higher degree of accuracy and precision and is now a highly interesting topic. In this context, this paper aims to investigate how AI techniques impact the PV value chain. The investigation consists of mapping the currently available AI technologies, identifying possible future uses of AI, and also quantifying their advantages and disadvantages in regard to the conventional mechanisms.

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“…Современные цифровые технологии дают возможность построения развитых моделей энергетических установок, позволяющих комплексно решать задачи диагностики и управления. Один из способов формирования таких моделей может быть основан на концепции цифровых двойников, дающих возможность получать все необходимые данные, характеризующие функционирование физического объекта или системы [15][16][17][18][19]. Цифровой двойник включает детальную математическую модель, параметры которой уточняются с помощью информации, поступающей от измерительно-информационных систем.…”

Section: Introductionunclassified

Algorithms for Creating the Digital Twin of a Distributed Generator

Bulatov

Kryukov

2020

Journal of Siberian Federal University. Engineering &Amp; Technologies

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The article describes the concept of a digital twin of a distributed generator (DG) implemented on the basis of a salient-pole synchronous generator. The structure of the digital twin is presented in the form of a hierarchical fuzzy model built on the experimental data. For building fuzzy models of individual elements and links of a generator, software algorithms for optimization of the membership functions of term sets and the numbers of knowledge base rules are proposed. The results of experiments on obtaining an optimized neuro-fuzzy model for regulating the rotation speed of the generator rotor are presented. A comparative analysis of the oscillograms of the output signal of the optimized fuzzy model showed a sufficiently high accuracy when using the subtractive clustering method to build a fuzzy logic system. This approach made it possible to significantly reduce the number of term sets and the amount of the fuzzy model rules. The proposed algorithms can be used in further research aimed at industrial implementation of DG digital twins, as well as for solving the problem of tuning automatic regulators of low-power synchronous generators

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Recent and prospective developments in power system control centers: Adapting the digital twin technology for application in power system control centers

Cited by 123 publications

References 37 publications

Digital Twin: Enabling Technologies, Challenges and Open Research

Digital Twin: Enabling Technologies, Challenges and Open Research

A Review on Artificial Intelligence Applications for Grid-Connected Solar Photovoltaic Systems

Algorithms for Creating the Digital Twin of a Distributed Generator

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