Wyniki 1-2 spośród 2 dla zapytania: authorDesc:"Petro LEZHNIUK"

Selfoptimization local electric systems modes with renewable energy sources DOI:10.15199/48.2019.06.06

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Electric grids were functionally designed to transport and distribute electricity produced centrally at large power plants. With the development of non-traditional and renewable energy sources (RES), they acquire the features of a local electric system (LES). In this connection, new tasks arise: harmonization of load schedules of consumers and generation of RES with consideration of their dependence on meteorological parameters of the environment, optimal control of power flows in order to reduce the losses of electricity and improve its quality, ensuring the balance power reliability of the formed LES centralized and local generation, etc. Naturally, it is advisable to solve these problems with the use of modern Smart Grid technologies [1-3]. Among the tasks to be solved for switching to the electrical grids (EG) based on the concept of the Smart Grid, there are, among other things, tasks whose solution is intended to improve the power flow control system [4, 5]. To do this, it is necessary to ensure the technical condition and regulatory capabilities of the relevant equipment. This, first and foremost, concerns the actual renewable energy sources (RES) - wind and solar power stations (WEP and PV), small hydroelectric power plants (SHPP), cogeneration and biogas plants (CGU and BGU) [4, 5]. This also applies to transformers and autotransformers with tap regulators, for which modern operational diagnostic systems should be created, as well as improved conditions for their operation in order to optimally utilize their load capacity to control power surges between higher and lower voltage grids [6] . At the same time it is necessary to improve the activeadaptive automatic control system (ACS) with power and voltage flows in electric grids of power systems, which allow to minimize power losses in them taking into account the technical state of electrical equipment of RES and the control effect of transformers with voltage and[...]

Reducing the dissymmetry of load currents in electrical networks 0,4/0,23 kV using artificial neural networks DOI:10.15199/48.2019.11.56

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The problem of the quality of electric energy plays a prominent role in development strategies of virtually every state. In European countries, it is believed that if the electricity losses exceed 7 - 9%, then such a transfer of electric energy is inefficient. Therefore, a need has emerged to develop new methods and measures of reducing the losses and improving the indicators of electric energy quality. Numerous studies on the analysis of voltage up to 0,4/0,23 kV in rural networks operating modes [1 - 3] showed that current dissymmetry is due to of municipal and household workload, most of which consists of casual switching, single-phase power-consuming equipment that is non-uniformly distributed over the phases. Knowledge of current values of asymmetry in a network allows specifying its additional power losses comparing to the symmetrical mode and the possibility of applying measures to reduce the losses [2]. The changing load of single-phase residential consumers of electricity is erratic and it is very difficult to predetermine its value at any given time. Boundaries of load change can only be established with a certain probability [4, 5, 6]. Technical and economic characteristics of the network performance deteriorate sharply in single-ended mode: energy losses increase and the voltage deviation from the nominal [7, 8]. Lifetime of asynchronous motors attached to a network also declines sharply. Furthermore, there are a number of adverse electromagnetic effects, both in the network and in the load. Therefore, losses of active energy, resulting in non-uniformity of phase load lines 0,4/0,23 kV and consumer transformers 6-10/0.4 kV, may increase by more than a third compared with the losses that would have occurred with a uniform load [3]. Analyzing two types of asymmetry, systematic, which is caused by a constant uneven phase load over time, and probable, which is determined by randomly varying loads in time, one fir[...]

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