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oaioai:bura.brunel.ac.uk:2438/22762

Load Forecasting based on Deep Long Short-term Memory with Consideration of Costing Correlated Factor

Authors
Publication date
27 September 2018
Publisher
IEEE
Doi

    Abstract

    Guangdong University of Technology, Guangzhou, China, Grant from the Financial and Education Department of Guangdong Province 2016[202]: Key Discipline Construction Programme; Education Department of Guangdong Province: New and integrated energy system theory and technology research group, project number 2016KCXTD022; National Science Foundation of China: A Time-Based-Demand- Response Program of Compensated Multiple-Shape Pricing Scheme, Grant No. 51707041; State Grid Technology Project: the Smart Monitoring Techniques Research in Self- Correlated Framework for Power Utility (Grant No. 5211011600RJ); Education Department of Guangdong Province: The Power Market Advanced Service for Load Monitoring Technologies, 2016KQNCX047

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    This paper was published in Brunel University Research Archive.

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