[PDF][PDF] A Review of Deep Transfer Learning Strategy for Energy Forecasting

SS Sankari, PS Kumar - Nature Environment and Pollution …, 2023 - neptjournal.com
Over the past decades, energy forecasting has attracted many researchers. The
electrification of the modern world influences the necessity of electricity load, wind energy …

Application of statistical and artificial intelligence techniques for medium-term electrical energy forecasting: A case study for a regional hospital

O Timur, K Zor, Ö Çelik, A Teke, T İbrikçi - Journal of Sustainable …, 2020 - hrcak.srce.hr
Sažetak Electrical energy forecasting is crucial for efficient, reliable, and economic
operations of hospitals due to serving 365 days a year, 24/7, and they require round-the …

[PDF][PDF] Simple approaches to missing data for energy forecasting applications

K Zor, O Celik, O Timur, HB Yildirim… - Proceedings of the 16th …, 2018 - icce2018.emu.edu.tr
FORC-03 Energy forecasting is not only a prominent sub-discipline in energetics, but also
an arduous challenge to acquire electrical and climatological data that might have some …

Forecasting in blockchain-based smart grids: Testing a prerequisite for the implementation of local energy markets

M Kostmann - 2018 - edoc.hu-berlin.de
Local energy markets (LEMs) have been proposed as a solution to the challenges
introduced by the current transformation of the energy landscape towards more distributed …

[PDF][PDF] Very Short-Term Electrical Energy Consumption Forecasting of a Household for the Integration of Smart Grids

K Zor, O Timur, Ö Çelik, HB Yıldırım… - European Conference on …, 2018 - researchgate.net
The recent integration of smart grid systems to present electric power systems and the
increasing penetration of renewable energy sources make electrical energy consumption …

Application of Load Forecasting i Thermal Unit Commitment Problems: A Pattern Similarity Approach

GC Silva, AC Lisboa, DAG Vieira… - Theory and Applications of …, 2019 - Springer
This study investigates the application of short-term load forecasting (STLF), which consists
of estimating a future demand within a period of time up to one week, to thermal unit …

Energy Management System for Smart Buildings and Microgrids Using Sampling-Based Model Predictive Control (SBMPC) and Machine Learning

J Ospina - 2019 - search.proquest.com
As the cost of renewable energy resources decreases and environmental concerns, such as
global warming, arise, new ways of generating, storing, and using clean energy are being …