Electricity demand and price forecasting model for sustainable smart grid using comprehensive long short term memory
This paper proposes an electricity demand and price forecast model of the smart city large datasets using a single comprehensive Long Short-Term Memory (LSTM) based on a sequence-to-sequence network. Real electricity market data from the Australian Energy Market Operator (AEMO) is used to validate t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-11-01
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| Series: | International Journal of Sustainable Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/19397038.2021.1951882 |