Can cross-sector information improve multi-energy demand forecasting accuracy?
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Published:2023-12
Issue:
Volume:9
Page:886-893
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ISSN:2352-4847
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Container-title:Energy Reports
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language:en
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Short-container-title:Energy Reports
Author:
Zhou Yangze,
Cui XueyuanORCID
Reference33 articles.
1. Multiple regression model for fast prediction of the heating energy demand;Catalina;Energy Build.,2013
2. Neural network model for short-term and very-short-term load forecasting in district buildings;Dagdougui;Energy Build.,2019
3. Davodi, M., Modares, H., Reihani, E., Davodi, M., Sarikhani, A., 2008. Coherency approach by hybrid PSO, K-Means clustering method in power system. In: 2008 IEEE 2nd International Power and Energy Conference. pp. 1203–1207. http://dx.doi.org/10.1109/PECON.2008.4762659.
4. Optimization strategy based on robust model predictive control for RES-CCHP system under multiple uncertainties;Dong;Appl. Energy,2022
5. Improving cooling load prediction reliability for HVAC system using Monte-Carlo simulation to deal with uncertainties in input variables;Fan;Energy Build.,2020
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