Issue |
E3S Web Conf.
Volume 530, 2024
2024 14th International Conference on Future Environment and Energy (ICFEE 2024)
|
|
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Article Number | 05005 | |
Number of page(s) | 10 | |
Section | Clean Energy Technology and Building Energy Management | |
DOI | https://doi.org/10.1051/e3sconf/202453005005 | |
Published online | 29 May 2024 |
Efficient Risk Management for Distributed Clean Energy: Principal Component based Weather Derivatives
1 Faculty of Transdisciplinary Sciences for Innovation, Kanazawa University, Ishikawa 920-1192, Japan
2 Faculty of Business Sciences, University of Tsukuba, Tokyo 112-0012, Japan
* Corresponding author: mtakuji@staff.kanazawa-u.ac.jp
As global efforts to achieve net-zero emissions intensify, the integration of renewable energy has brought to the critical need for effective volumetric risk hedging strategies, particularly at the local level. However, existing financial instruments based on total power output, such as wind power futures, fall short in local hedging. This study introduces Principal Component (PC) derivatives designed for the solar power sector, using multi-regional solar radiation as the underlying to overcome data handling complexities. In particular, by incorporating our previous concept of prediction error derivatives, we provide a unique solution to complex pricing to help manage cash flow volatility risks. In addition, we propose PC derivatives based on solar radiation residuals to hedge volumetric risks. Empirical analysis shows that our PC derivatives outperform existing widearea derivatives in terms of hedge effectiveness, with a 20% increase over area-specific derivatives. Using as few as three or four PC derivatives can provide comprehensive coverage across different areas, enhancing market liquidity and creating an efficient transaction framework. Our results highlight the practical benefits of this approach, including the potential to reduce transaction costs by countertrading in different regions.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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