Development of methods for minimizing energy losses in electrical networks

Chernykh, A. G.; Barykina, Y N; Morozevich, O A

doi:10.1088/1755-1315/1070/1/012006

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…• Forecasting tasks that will allow you to collect meteorological information, determine the state of power equipment, change consumption, etc [11].…”

Section: Fig 2 Energy Tasks Of Artificial Intelligence In the Energy ...mentioning

confidence: 99%

Applications of artificial intelligence methods in the energy sector

Barykina,

Zakharov,

Yuan

et al. 2023

BIO Web Conf.

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The article describes the relevance of application of artificial intelligence technologies in the energy sector. The theoretical and practical research was conducted to summarize and substantiate the classification of artificial intelligence methods used in the energy sector. It includes three groups of methods. The analysis of domestic and foreign practice of applying artificial intelligence methods in the energy sector allowed for the identification of energy tasks that can improve the efficiency of energy enterprises. The artificial intelligence technologies should be used along with energy transformation, digital transformation, and integration of energy sectors. These processes are described in the article. A deep analysis of the application of artificial intelligence methods and tasks in the energy sector was conducted and examples of applications of artificial intelligence technologies were provided.

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“…• Forecasting tasks that will allow you to collect meteorological information, determine the state of power equipment, change consumption, etc [11].…”

Section: Fig 2 Energy Tasks Of Artificial Intelligence In the Energy ...mentioning

confidence: 99%

Applications of artificial intelligence methods in the energy sector

Barykina,

Zakharov,

Yuan

et al. 2023

BIO Web Conf.

View full text Add to dashboard Cite

show abstract

“…On the other hand, given the policies implemented by the regulatory entities of the electrical sector, the values regarding energy losses in distribution networks must be continuously reduced by utilities to improve the quality, and the distribution efficiency of electrical energy [6,7]. To this effect, utilities need to design efficient maintenance and operation plans that allow for reaching the expected energy losses with minimal investment costs [8,9].…”

Section: Introduction 1general Context and Motivationmentioning

confidence: 99%

Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks

2022

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The black hole optimization (BHO) method is applied in this research to solve the problem of the optimal reactive power compensation with fixed-step capacitor banks in three-phase networks considering the phase-balancing problem simultaneously. A master–slave optimization approach based on the BHO in the master stage considers a discrete codification and the successive approximation power flow method in the slave stage. Two different evaluations are proposed to measure the impact of the shunt reactive power compensation and the phase-balancing strategies. These evaluations include a cascade solution methodology (CSM) approach and a simultaneous solution methodology (SSM). The CSM approach solves the phase-balancing problem in the first stage. This solution is implemented in the distribution network to determine the fixed-step capacitor banks installed in the second stage. In the SSM, both problems are solved using a unique codification vector. Numerical results in the IEEE 8- and IEEE 27-bus systems demonstrate the effectiveness of the proposed solution methodology, where the SSM presents the better numerical results in both test feeders with reductions of about 32.27% and 33.52%, respectively, when compared with the CSM. To validate all the numerical achievements in the MATLAB programming environment, the DIgSILENT software was used for making cross-validations. Note that the selection of the DIgISLENT software is based on its wide recognition in the scientific literature and industry for making quasi-experimental validations as a previous stage to the physical implementation of any grid intervention in power and distribution networks.

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Development of methods for minimizing energy losses in electrical networks

Cited by 2 publications

References 16 publications

Applications of artificial intelligence methods in the energy sector

Applications of artificial intelligence methods in the energy sector

Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks

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