A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
Z Qian, Y Pei, H Zareipour, N Chen - Applied energy, 2019 - Elsevier
With the continuous growth of wind power integration into the electrical grid, accurate wind
power forecasting is an important component in management and operation of power …
power forecasting is an important component in management and operation of power …
A review on hybrid empirical mode decomposition models for wind speed and wind power prediction
Reliable and accurate planning and scheduling of wind farms and power grids to ensure
sustainable use of wind energy can be better achieved with the use of precise and accurate …
sustainable use of wind energy can be better achieved with the use of precise and accurate …
[HTML][HTML] Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine
As the share of global offshore wind energy in the electricity generation portfolio is rapidly
increasing, the grid integration of large-scale offshore wind farms is becoming of interest …
increasing, the grid integration of large-scale offshore wind farms is becoming of interest …
Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference …
Long-term windspeed prediction is crucial for establishing the viability of wind as a clean
energy option, including the selection of wind farm locations, feasibility studies on energy …
energy option, including the selection of wind farm locations, feasibility studies on energy …
An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia
This research paper aims to develop a hybrid neuro-evolutionary wrapper-based model for
daily global solar radiation estimation in the solar-rich Sunshine State of Queensland …
daily global solar radiation estimation in the solar-rich Sunshine State of Queensland …
A multi-strategy random weighted gray wolf optimizer-based multi-layer perceptron model for short-term wind speed forecasting
Gray wolf optimizer (GWO) that is one of the meta-heuristic optimization algorithms is
principally based on the hunting method and social hierarchy of the gray wolves in the …
principally based on the hunting method and social hierarchy of the gray wolves in the …
A multivariable hybrid prediction model of offshore wind power based on multi-stage optimization and reconstruction prediction
Offshore wind power prediction is the basis for safe operation and grid dispatch. However, it
is difficult due to the high volatility. Aiming at the three shortcomings of current methods: lack …
is difficult due to the high volatility. Aiming at the three shortcomings of current methods: lack …
Smart coordination of predictive load balancing for residential electric vehicles based on EMD‐Bayesian optimised LSTM
The charging load forecasting of residential Electric Vehicles help grid operators make
informed decisions in terms of scheduling and managing demand response. The residence …
informed decisions in terms of scheduling and managing demand response. The residence …
A temporal convolutional network based hybrid model of short-term electricity price forecasting
Electricity prices have complex features, such as high frequency, multiple seasonality, and
nonlinearity. These factors will make the prediction of electricity prices difficult. However …
nonlinearity. These factors will make the prediction of electricity prices difficult. However …
[PDF][PDF] Performance comparison of hybrid neuro-fuzzy models using meta-heuristic algorithms for short-term wind speed forecasting
In this paper, short-term wind speed forecasting models have been developed using neuro-
fuzzy systems. The optimal neuro-fuzzy model has been investigated in detail. In addition …
fuzzy systems. The optimal neuro-fuzzy model has been investigated in detail. In addition …