scholarly journals FEATURES OF ELECTRICITY SUPPLY OF SIDE-BASED EQUIPMENT IN IMPLEMENTATION OF RESTRICTED GENERATION

2019 ◽  
pp. 118-128
Author(s):  
Serhii Boiko ◽  
◽  
Andrey Nekrasov ◽  
Oleksiy Gorodny ◽  
Oksana Borysenko ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Distributed Generation ◽  
Power Supply ◽  
Iron Ore ◽  
Supply System ◽  
Electricity Supply ◽  
Dispersed Generation ◽  
Artificial Neural ◽  
Supply Systems

Urgency of the research. Ukraine has powerful dispersed generation resources. At the same time, one of the four measures proposed by the International Energy Agency for improving energy efficiency in the countries of the world is increasing the use of renewable energy sources in the total electricity production, including not the last role given to dispersed generation. Meanwhile, the consequence of the natural decrease in the levels of iron ore extraction in our country, at depths exceeding 1000-1500 m, that is, towards the projected ones, which already increases the energy intensity of its extraction and the decline of the con-capita ability on the world market. Target setting. The main purpose of this work is to synthesize the features of the electric power supply of iron ore enterprises, provided that they are introduced into the system of their electricity supply of distributed generation sources and analysis of the specifics of their operation. Actual scientific researches and issues analysis. Thus, the actual scientific-practical task is to study the peculiarities of the operation of systems of electricity supply of iron ore enterprises with the use of sources of dispersed generation in their distribution networks. Uninvestigated parts of general matters defining. Previously, it was proposed to install power plants at the crosscutting overheads, on dumps of quarries and other possible places of installation in the conditions of iron ore enterprises. However, the principles of the implementation of intelligent power supply management systems for the enterprises under consideration, especially when reconfiguring these systems, are not yet definitively defined. The research objective. The purpose of this work is to synthesize the features of the electricity supply of iron ore enterprises, provided that the sources of distributed generation are introduced into their electricity supply system. The statement of basic materials. In a number of previous studies, the authors justify the positive effect of the introduction of dispersed generation into the structure of the power supply systems of enterprises. The application of artificial neural networks in control systems and determination of electrical energy parameters of power supply systems of iron ore enterprises is proposed, which will allow multifactorial management and analysis of energy parameters in the implementation of distributed generation sources. The proposed approach for the implementation of artificial neural networks for modeling the reliability of the power supply system of iron ore enterprises with the introduction of dispersed generation can be presented with the help of artificial neural networks, which will improve predictability of generated electricity by dispersed generation in time. Conclusions. The model of reliability of the power supply system of the field-view enterprises in the implementation of dispersed generation can be represented using artificial neural networks, which will improve predictability of generated electricity by dispersed generation in time.

scholarly journals Methods for calculating the reliability of power supply systems

2021 ◽  
Vol 25 (1) ◽  
pp. 57-65
Author(s):  
A. S. Lukovenko ◽  
I. V. Zenkov
Keyword(s):  
Neural Network ◽  
Failure Rate ◽  
Power Supply ◽  
Software Package ◽  
Power Supply System ◽  
Supply System ◽  
Reliability Indicators ◽  
Artificial Neural ◽  
Supply Systems ◽  
Technical Reliability

The aim was to determine the reliability indicators of a power supply system using an artificial neural network model. A model for calculating technical reliability was developed using the following methods: an algorithm for calculating reliability indicators of power supply systems, the method of failure rate of a power supply system and a forecasting model using artificial neural networks. It was established that a power supply system is formed by an open radial power supply circuit. The failure rate of the power supply subsystem was determined by calculating the failure rate of i-th element of the subsystem. As a result of calculating the probability of failure-free operation of the subsystem for various conditions (5 time intervals), it was found that with an increase in the operating time from 100 to 500 h, a linear increase in the rate of system failures occurs from 0.0051 to 0.0073 1/h. A comparison of the obtained mean-to-failure values of the main and the same backup subsystem in the unloaded mode with an absolutely reliable switch (269.62 h) with the main and the same backup subsystem in the loaded mode (202.21 h) was carried out. The results differ by 67.41 h, which indicates a higher degree of reliability of the first method. The software package Prognoz_INS_2020 was developed. An acceptable accuracy of no more than 2.17% was obtained by comparing the results of the conventional calculation of the failure rate of power supply systems and using the Prognoz_INS_2020 software package. This indicates the efficiency of the proposed software package in reliability calculations at operating energy enterprises. The proposed methods for assessing technical reliability both using the conventional model and a model based on an artificial neural network made it possible to assess the state of power supply systems, which helps to prevent dangerous emergencies. 

scholarly journals Joint voltage and frequency predictive controllers for distributed generation plants

2021 ◽  
Vol 25 (5) ◽  
pp. 568-585
Author(s):  
Yu. N. Bulatov
Keyword(s):  
Quality Indicators ◽  
Distributed Generation ◽  
Power Supply ◽  
Power Supply System ◽  
Supply System ◽  
Voltage Sag ◽  
Transient Time ◽  
Operating Modes ◽  
Supply Systems ◽  
Predictive Controllers

The paper determines the effect of proposed joint voltage and frequency predictive controllers for distributed generation (DG) plants on quality indicators characterizing the control process in different operating modes of power supply systems. The studies are conducted in the MatLab environment (Simulink and SimPowerSystems simulation packages) employing control engineering methods. It is proposed to design and adjust joint predictive controllers by determining the resonant frequency of oscillations for the master generator rotor. This approach provides better quality indicators of voltage and frequency control in power supply systems while maintaining the same settings for the controllers of DG plants. With an additional load in an isolated power supply system, the maximum voltage sag is found to be 1.75 times lower than for local predictive control and 3.5 times lower as compared to the use of conventional controllers. For the specified mode, predictive controllers enable a threefold reduction in the transient time between rotor rotational speeds in a synchronous generator. In the start mode of a powerful electric motor, the predictive controllers of synchronous generators in the power supply system enable a 1.5 times reduction in voltage sag, with a 1.4 times reduction in overvoltage following its start. In the case of a short-term three phase short-circuit, joint predictive controllers allow a 1.5 times decrease in transient time and a 2.3 times decrease in the overshoot of power line frequency as compared to local control. In addition, frequency oscillation in the power system is also reduced. Similar effects are observed in other operating modes of the considered power supply systems equipped with DG plants. The performed dynamic simulation confirms the effectiveness of using joint voltage and frequency predictive controllers for DG plants, which consists in a positive impact on the quality of processes involved in controlling the parameters of power supply systems in various operating modes.

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