Abstract
Forecasting the long-term demand (LTDF) is crucial for efficiently planning power systems. Typically, utilities perform separate long-term projections for energy consumption and peak demand, using distinct forecasting frameworks, which can lead to increased complexities. To address this challenge, this paper introduces a comprehensive LTDF model that utilizes the eXtreme Gradient Boosting algorithm with various sequential configurations. Initially, the paper develops a monthly energy consumption forecasting model for one year ahead. This model takes into account external factors such as macro-economic and climatic conditions. To capture the feature of energy consumption profile, a multi-input multi-output sequential approach is employed. Subsequently, the forecasted energy consumption becomes an influencing factor in a multivariate model for predicting the monthly peak demand one year ahead. Motivated by the great fluctuation of the monthly peak demand, the paper adopts a hybrid direct-recursive sequential configuration to address these variations effectively. Through considering the information of forecasted energy, the LTDF model achieved improved forecasting accuracy for peak demand. To validate the effectiveness of this proposed model, data from the New South Wales (NSW) power network was utilized for testing purposes.
Original language | English |
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Title of host publication | 2023 IEEE 5th International Conference on Power, Intelligent Computing and Systems, ICPICS 2023 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 157-162 |
Number of pages | 6 |
ISBN (Electronic) | 9798350333442 |
DOIs | |
Publication status | Published - 2023 |
Event | 5th IEEE International Conference on Power, Intelligent Computing and Systems - Shenyang, China Duration: 14 Jul 2023 → 16 Jul 2023 https://ieeexplore.ieee.org/xpl/conhome/10235327/proceeding |
Publication series
Name | 2023 IEEE 5th International Conference on Power, Intelligent Computing and Systems, ICPICS 2023 |
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Conference
Conference | 5th IEEE International Conference on Power, Intelligent Computing and Systems |
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Abbreviated title | ICPICS 2023 |
Country/Territory | China |
City | Shenyang |
Period | 14/07/23 → 16/07/23 |
Internet address |