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An overview of energy demand forecasting methods published in 2005–2015
The importance of energy demand management has been more vital in recent decades as
the resources are getting less, emission is getting more and developments in applying …
the resources are getting less, emission is getting more and developments in applying …
[HTML][HTML] Forecasting India's electricity demand using a range of probabilistic methods
Y An, Y Zhou, R Li - Energies, 2019 - mdpi.com
With serious energy poverty, especially concerning power shortages, the economic
development of India has been severely restricted. To some extent, power exploitation can …
development of India has been severely restricted. To some extent, power exploitation can …
Electricity load and price forecasting with influential factors in a deregulated power industry
With the emergence of smart power grid and distributed generation technologies in recent
years, there is need to introduce new advanced models for forecasting. Electricity load and …
years, there is need to introduce new advanced models for forecasting. Electricity load and …
Generalized additive model (GAM) based corrosion growth prediction model using mass in-line inspection (ILI) data
H Zhang, L Yang - Proceedings of the 2023 8th International …, 2023 - dl.acm.org
In the pipeline integrity management, corrosion growth plays an important role since it is
critical to the determination of the re-inspection interval and development of appropriate …
critical to the determination of the re-inspection interval and development of appropriate …
Short-term forecasting in electric power systems using artificial neural networks
EE Roussineau, P Otto… - 2018 IEEE PES Innovative …, 2018 - ieeexplore.ieee.org
In order to optimize the power flows within microgrids for high economic profitability, as
general rule the energy management systems (EMSs) need as input real-time forecasts of …
general rule the energy management systems (EMSs) need as input real-time forecasts of …
A fusion prognostic approach based on multi-kernel relevance vector machine and Bayesian model averaging
Y Liu, G Zhao, X Peng - 2016 Prognostics and System Health …, 2016 - ieeexplore.ieee.org
The fusion approaches with multi-model ensemble can present a better performance than
the simple approaches with single model in Prognostics and Health Management (PHM) …
the simple approaches with single model in Prognostics and Health Management (PHM) …
[HTML][HTML] Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case
M Sabat, D Baczyński - Energies, 2021 - mdpi.com
Transmission, distribution, and micro-grid system operators are struggling with the
increasing number of renewables and the changing nature of energy demand. This …
increasing number of renewables and the changing nature of energy demand. This …
[PDF][PDF] Baczy nski, D. Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case …
M Sabat - 2021 - repo.pw.edu.pl
Transmission, distribution, and micro-grid system operators are struggling with the
increasing number of renewables and the changing nature of energy demand. This …
increasing number of renewables and the changing nature of energy demand. This …
Prediction Models for Dynamic Decision Making in Smart Grid
S Aman - 2015 - search.proquest.com
The widespread use of smart meters and other sensors in smart grid has resulted in
unprecedented amounts of data being generated at high spatial and temporal resolutions …
unprecedented amounts of data being generated at high spatial and temporal resolutions …
[CITARE][C] Electricity Load Forecasting
J Meyer - 2018 - Heriot-Watt University