Buchumschlag

Short-term electrical load forecasting for the electrical supply company with deep neural network

Gespeichert in:

Bibliographische Detailangaben
Datum:	2018
Hauptverfasser:	P. O. Chernenko, V. O. Miroshnyk
Format:	Artikel
Sprache:	Englisch
Veröffentlicht:	2018
Schriftenreihe:	Proceedings of the Institute of Electrodynamics of the National Academy of Sciences of Ukraine
Online Zugang:	http://jnas.nbuv.gov.ua/article/UJRN-0000906817
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:	Library portal of National Academy of Sciences of Ukraine \| LibNAS

Institution

Library portal of National Academy of Sciences of Ukraine | LibNAS

Ähnliche Einträge

Univariable short-term forecast of nodal electrical loads of energy systems
von: P. O. Chernenko, et al.
Veröffentlicht: (2020)

Accounting for Electricity Consumption of Energy Enterprises for Short–Term Forecasting of Electrical Load of Power System
von: P. O. Chernenko, et al.
Veröffentlicht: (2014)

Modeling and Short-Term Forecasting of Technology Component of Electrical Load of the Regional Electric Power System
von: P. O. Chernenko, et al.
Veröffentlicht: (2016)

Specificity of short-term electrical load forecasting of power system with significant share the industrial electricity consumption
von: P. O. Chernenko, et al.
Veröffentlicht: (2016)

Increasing the accuracy of short-term electrical load forecasting with considering to changes in the structure of consumption during the year
von: P. O. Chernenko, et al.
Veröffentlicht: (2017)

Statistical homogeneity assurance of the electrical load daily schedules of the energy-consuming enterprises for short-term load forecasting of electric power system
von: P. O. Chernenko, et al.
Veröffentlicht: (2015)

Functionally oriented model of adaptive short-term forecasting of electrical load
von: Voloshko, A. V., et al.
Veröffentlicht: (2016)

Increasing the accuracy of short-term forecasts of PVSPP generation based on artificial neural networks and taking additional factors into account
von: V. O. Miroshnyk, et al.
Veröffentlicht: (2024)

Electrical load forecasting on hierarchical levels of IPS of Ukraine using LSTM neural network
von: S. S. Loskutov, et al.
Veröffentlicht: (2021)

Short-term interval forecast of total electricity generation by renewable energy sources producers
von: I. V. Blinov, et al.
Veröffentlicht: (2019)

Improving the algorithm for determining the effect of air temperature on the overall electrical load of the power system to improve the accuracy of short-term forecasting
von: P. O. Chernenko, et al.
Veröffentlicht: (2021)

Application of decomposition methods in short-term forecasting of overall electric load of energy system
von: I. V. Blinov, et al.
Veröffentlicht: (2021)

Analysis of methods of increasing data reliability for problems of short term forecasting of nodal load
von: V. O. Miroshnyk, et al.
Veröffentlicht: (2021)

The Short-Term Forecasting of the Labor Market Supply in Ukraine
von: O. S. Korepanov, et al.
Veröffentlicht: (2017)

Automatic development of deep neural networks for improving numerical meteorological forecast
von: Doroshenko, А.Yu., et al.
Veröffentlicht: (2024)

Multifactor Modeling and Analysis of Electrical Load of the Power System Using the Data of Long-Term Prehistory
von: P. O. Chernenko, et al.
Veröffentlicht: (2018)

Formal verification of deep neural networks
von: Panchuk, B.O.
Veröffentlicht: (2024)

DESIGN OF A MATLAB GUI FOR SHORT-TERM SOLAR FORECASTING BASED ON DEEP LEARNING
von: Matushkin, D., et al.
Veröffentlicht: (2023)

Statistical analysis of random coefficient periodic autoregression and its application for short-term electricity consumption forecasting
von: Ye. Fryz, et al.
Veröffentlicht: (2019)

Synthesis of optimal structure of deep neural network
von: Yu. Koval, et al.
Veröffentlicht: (2016)

Capabilities of short-term forecasting of solar energy
von: M. P. Kuznietsov, et al.
Veröffentlicht: (2017)

On some problems of neural network technologies in electric components diagnosing
von: S. F. Telenyk, et al.
Veröffentlicht: (2017)

Dynamic routing of wireless electrical sensors based on neural networks
von: Yamnenko, Ju., et al.
Veröffentlicht: (2016)

Dynamic Routing of Wireless Electrical Sensors Based on Neural Networks
von: Yu. Yamnenko, et al.
Veröffentlicht: (2016)

Mathematical models of the short-term forecast of development of Aphis gossypii in the forest-steppe of Ukraine
von: V. L. Chernenko
Veröffentlicht: (1999)

Capabilities of short-term forecasting of solar energy
von: Kuznietsov, M., et al.
Veröffentlicht: (2017)

Short-term forecasting of gross domestic product
von: A. Huseynova, et al.
Veröffentlicht: (2023)

Structural and Parametric Synthesis of Deep Learning Neural Networks
von: V. M. Syniehlazov, et al.
Veröffentlicht: (2020)

Estimation of the cost of the electricity supply forecast error for the &quot;green&quot; tariff producers balance group
von: I. V. Blinov, et al.
Veröffentlicht: (2020)

NEURAL NETWORK MODELING IN PROBLEMS OF PREDICTION MODES OF ELECTRICAL GRIDS
von: Moroz, A. N., et al.
Veröffentlicht: (2016)

Satellite monitoring of clouds over deep fault zones, short-term earthquake forecast and seismic activity in Ukraine
von: Vorobiov, Anatolii, et al.
Veröffentlicht: (2019)

Satellite monitoring of clouds over deep fault zones, short-term earthquake forecast and seismic activity in Ukraine
von: A. I. Vorobiov, et al.
Veröffentlicht: (2019)

Deep neural network elements and their implementation in FPGA Xilinx
von: T. A. Samoliuk
Veröffentlicht: (2015)

The models, tools, and measures to ensure reliable and efficient operation of energy supply companies, balancing and distribution of electricity in the IPS of Ukraine
von: O. V. Kyrylenko, et al.
Veröffentlicht: (2019)

Application of neural networks to prediction of company future development
von: L. Dvořáková, et al.
Veröffentlicht: (2015)

EQUATIONS OF ELECTRIC MOTOR POWER SUPPLY UNIT DISSYMMETRY UNDER PHASE SHORT-CIRCUIT FAULT
von: Chaban, V. Y., et al.
Veröffentlicht: (2013)

Increasing the reliability of mobile intelligent machines based on deep neural networks
von: S. V. Kovalevskyi, et al.
Veröffentlicht: (2018)

Using the Artificial Neural Networks for Forecasting the Risk of Bankruptcy of Banks
von: Ye. Markov
Veröffentlicht: (2018)

Recurrent neural networks for the problem of improving numerical meteorological forecasts
von: Doroshenko, А.Yu., et al.
Veröffentlicht: (2023)

Enhancing image inpainting through image decomposition and deep neural networks
von: K. Bellaj, et al.
Veröffentlicht: (2023)