Construction of Mixed Derivatives Strategy for Wind Power Producers

Author:

Yamada Yuji1ORCID,Matsumoto Takuji2ORCID

Affiliation:

1. Faculty of Business Sciences, University of Tsukuba, Tokyo 112-0012, Japan

2. Faculty of Transdisciplinary Sciences for Innovation, Kanazawa University, Ishikawa 920-1192, Japan

Abstract

Due to the inherent uncertainty of wind conditions as well as the price unpredictability in the competitive electricity market, wind power producers are exposed to the risk of concurrent fluctuations in both price and volume. Therefore, it is imperative to develop strategies to effectively stabilize their revenues, or cash flows, when trading wind power output in the electricity market. In light of this context, we present a novel endeavor to construct multivariate derivatives for mitigating the risk of fluctuating cash flows that are associated with trading wind power generation in electricity markets. Our approach involves leveraging nonparametric techniques to identify optimal payoff structures or compute the positions of derivatives with fine granularity, utilizing multiple underlying indexes including spot electricity price, area-wide wind power production index, and local wind conditions. These derivatives, referred to as mixed derivatives, offer advantages in terms of hedge effectiveness and contracting efficiency. Notably, we develop a methodology to enhance the hedge effects by modeling multivariate functions of wind speed and wind direction, incorporating periodicity constraints on wind direction via tensor product spline functions. By conducting an empirical analysis using data from Japan, we elucidate the extent to which the hedge effectiveness is improved by constructing mixed derivatives from various perspectives. Furthermore, we compare the hedge performance between high-granular (hourly) and low-granular (daily) formulations, revealing the advantages of utilizing a high-granular hedging approach.

Funder

Grant-in-Aid for Scientific Research

Grant-in-Aid for Challenging Research

the Japan Society for the Promotion of Science

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference54 articles.

1. Electricity derivatives and risk management;Deng;Energy,2006

2. Weather derivatives and weather risk management;Brockett;Risk Manag. Insur. Rev.,2005

3. Halkos, G.E., and Tsirivis, A.S. (2019). Energy commodities: A review of optimal hedging strategies. Energies, 12.

4. Eydeland, A., and Wolyniec, K. (2002). Energy and Power risk Management: New Developments in Modeling, Pricing, and Hedging, John Wiley & Sons, Ltd.

5. Clewlow, L., and Strickland, C. (2000). Energy Derivatives: Pricing and Risk Management, Lacima.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3