Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
[HTML][HTML] Forecast reconciliation: A review
Collections of time series formed via aggregation are prevalent in many fields. These are
commonly referred to as hierarchical time series and may be constructed cross-sectionally …
commonly referred to as hierarchical time series and may be constructed cross-sectionally …
Improving the Bi-LSTM model with XGBoost and attention mechanism: A combined approach for short-term power load prediction
Y Dai, Q Zhou, M Leng, X Yang, Y Wang - Applied Soft Computing, 2022 - Elsevier
Short term power load forecasting plays an important role in the management and
development of power systems with a focus on the reduction in power wastes and economic …
development of power systems with a focus on the reduction in power wastes and economic …
Time-series power forecasting for wind and solar energy based on the SL-transformer
J Zhu, Z Zhao, X Zheng, Z An, Q Guo, Z Li, J Sun… - Energies, 2023 - mdpi.com
As the urgency to adopt renewable energy sources escalates, so does the need for accurate
forecasting of power output, particularly for wind and solar power. Existing models often …
forecasting of power output, particularly for wind and solar power. Existing models often …
A hybrid approach for hierarchical forecasting of industrial electricity consumption in Brazil
M Mesquita Lopes Cabreira, F Leite Coelho da Silva… - Energies, 2024 - mdpi.com
The Brazilian industrial sector is the largest electricity consumer in the power system. Energy
planning in this sector is important mainly due to its economic, social, and environmental …
planning in this sector is important mainly due to its economic, social, and environmental …
CRPS learning
J Berrisch, F Ziel - Journal of Econometrics, 2023 - Elsevier
Combination and aggregation techniques can significantly improve forecast accuracy. This
also holds for probabilistic forecasting methods where predictive distributions are combined …
also holds for probabilistic forecasting methods where predictive distributions are combined …
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 …
Short-and medium-term electricity consumption forecasting using Prophet and GRU
N Son, Y Shin - Sustainability, 2023 - mdpi.com
Electricity consumption forecasting plays a crucial role in improving energy efficiency,
ensuring stable power supply, reducing energy costs, optimizing facility management, and …
ensuring stable power supply, reducing energy costs, optimizing facility management, and …
A novel decompose-cluster-feedback algorithm for load forecasting with hierarchical structure
In load forecasting fields, electricity demand with hierarchical structure is very popular where
there are some differences among investigated load series because of geography or …
there are some differences among investigated load series because of geography or …
Hierarchical multiobjective distributed deep learning for residential short-term electric load forecasting
Short-term load forecasting plays an essential role in appliance control in households and
demand response at the neighborhood or community level. When load forecasting is …
demand response at the neighborhood or community level. When load forecasting is …