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State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
McVCsB: A new hybrid deep learning network for stock index prediction
Forecasting the stock composite index is a challenge on account of the abundant noise-
induced high degree of non-linearity and non-stationarity. Numerous predictive models …
induced high degree of non-linearity and non-stationarity. Numerous predictive models …
A short-term wind power forecasting method based on multivariate signal decomposition and variable selection
T Yang, Z Yang, F Li, H Wang - Applied Energy, 2024 - Elsevier
Accurate and effective short-term wind power forecasting is vital for the large-scale
integration of wind power generation into the power grid. However, due to the intermittence …
integration of wind power generation into the power grid. However, due to the intermittence …
Solar irradiance prediction with variable time lengths and multi-parameters in full climate conditions based on photovoltaic greenhouse
Y Zhu, M Li, X Ma, Y Wang, G Li, Y Zhang, Y Liu… - Energy Conversion and …, 2024 - Elsevier
Photovoltaic power generation can provide energy for greenhouses and achieve high
quality and high yield of crops. In reality, solar irradiance is fluctuating and intermittent. Thus …
quality and high yield of crops. In reality, solar irradiance is fluctuating and intermittent. Thus …
Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting
Y Chen, M Bai, Y Zhang, J Liu, D Yu - Energy, 2023 - Elsevier
As the proportion of solar power generation increases, accurate solar irradiance forecast
used to connect solar power to the grid has become crucial. Multi-parameter prediction is …
used to connect solar power to the grid has become crucial. Multi-parameter prediction is …
Integrated approaches in resilient hierarchical load forecasting via TCN and optimal valley filling based demand response application
Considering the electricity market, data analytics paves the way for completely new
strategies regarding demand and supply-side policies. In this manner, predictive analysis of …
strategies regarding demand and supply-side policies. In this manner, predictive analysis of …
Enhancing solar irradiance forecasting for hydrogen production: The MEMD-ALO-BiLSTM hybrid machine learning model
This study focuses on an innovative hybrid machine-learning model for solar irradiance
forecasting, targeting the integration of solar power into hydrogen production systems …
forecasting, targeting the integration of solar power into hydrogen production systems …
A hybrid model based on multivariate fast iterative filtering and long short-term memory for ultra-short-term cooling load prediction
The current ultra-short-term cooling load forecasting models have not given due attention to
the data pre-processing stage. In this paper, multivariate signal decomposition methods …
the data pre-processing stage. In this paper, multivariate signal decomposition methods …
Forecasting hourly day-ahead solar photovoltaic power generation by assembling a new adaptive multivariate data analysis with a long short-term memory network
Accurate multi-step PV power forecasting is a challenging task because of complex time
series and error buildup in muti-step forecasts. This work is based on develo** a …
series and error buildup in muti-step forecasts. This work is based on develo** a …
Energy fluctuation pattern recognition coupled with decomposition-integration: A novel ocean tidal energy forecasting system
Q Wu, H Yang, G Li - Measurement, 2024 - Elsevier
Ocean tidal energy is a new energy source which is recognized and utilized earlier by
human beings. For the complexity of tidal generation and the singleness of tidal prediction …
human beings. For the complexity of tidal generation and the singleness of tidal prediction …