Leung, EKH 
ORCID: 0000-0003-2058-0287 and Poo, MCP
(2022)
Modeling Short-term Solar Energy Generation: An Integrated Approach
In: 2022 IEEE/ACIS 7th International Conference on Big Data, Cloud Computing, and Data Science (BCD), 2022-8-4 - 2022-8-6, Da Nang, Vietnam.
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Camera ready accepted paper (Paper ID 42).pdf - Author Accepted Manuscript Download (792kB) | Preview |
Abstract
The non-renewable energy generation process emits undesirable CO2 emissions which has long been regarded as a threat to our environment, and ultimately, human beings. Renewable energy is perceived as a viable solution in response to transitioning to a greener future and tackling climate change. However, the major challenge associated with most renewable energy sources is the intermittency caused by fluctuating weather conditions. This paper proposes an integrated approach in predicting the short-term solar energy generation based on changing weather conditions. The proposed approach is generic and thus can be treated as a systematic framework of predicting the generation of different renewable energy. An illustrative example is provided, demonstrating the practicability of the approach.
| Item Type: | Conference Item (Unspecified) |
|---|---|
| Uncontrolled Keywords: | 40 Engineering, 4008 Electrical Engineering, 13 Climate Action, 7 Affordable and Clean Energy |
| Divisions: | Faculty of Humanities & Social Sciences > School of Management |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 22 Aug 2022 14:38 |
| Last Modified: | 22 May 2026 16:37 |
| DOI: | 10.1109/BCD54882.2022.9900595 |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3161983 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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