Pricing the risk due to weather conditions in small variable renewable energy projects

Mosquera-López, Stephanía; Uribe, Jorge M.

doi:10.1016/j.apenergy.2022.119476

Cited by 4 publications

(3 citation statements)

References 40 publications

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“…In this study, we assume that the hedged risk is only the volume of wind power generated, and we do not consider price risk. Hedging volume risk in electric business is a challenging issue because it is generally difficult to completely hedge [7], and this is why several recent studies, especially in the renewable energy business, have often addressed the hedging problem for volume risk only [5,14,17,35]. These studies suggest that even if price risk is excluded (i.e., even if price risk can be completely hedged), weather derivatives are still effective because the volume risk of renewable energy is heavily linked to weatherrelated indices.…”

Section: Minimum Variance Hedging Problemmentioning

confidence: 99%

Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Matsumoto

Yamada

2023

Energies

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Since the future output of wind power generation is uncertain due to weather conditions, there is an increasing need to manage the risks associated with wind power businesses, which have been increasingly implemented in recent years. This study introduces multiple weather derivatives of wind speed and temperature and examines their effectiveness in reducing (hedging) the fluctuation risk of future cash flows attributed to wind power generation. Given the diversification of hedgers and hedging needs, we propose new standardized derivatives with higher-order monomial payoff functions, such as “wind speed cubic derivatives” and “wind speed and temperature cross-derivatives,” to minimize the cash flow variance and develop a market-trading scheme to practically use these derivatives in wind power businesses. In particular, while demonstrating the importance of standardizing weather derivatives regarding market liquidity and efficiency, we propose a strategy to narrow down the required number (or volume) of traded instruments and improve trading efficiency by utilizing the least absolute shrinkage and selection operator (LASSO) regression. Empirical analysis reveals that higher-order, multivariate standardized derivatives can not only enhance the out-of-sample hedge effect but also help reduce trading volume. The results suggest that diversification of hedging instruments increases transaction flexibility and helps wind power generators find more efficient portfolios, which can be generalized to risk management practices in other businesses.

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Section: Minimum Variance Hedging Problemmentioning

confidence: 99%

Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Matsumoto

Yamada

2023

Energies

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“…This is due to issues such as emergency curtailment, which has seen a rapid increase both in the Kyushu region of Japan [11] and globally [12] in recent years, as well as changes in installed capacity, delayed information disclosure, and opaque measurement errors. In response to these challenges, we opt for a more commonplace and homogeneous observed data, i.e., solar radiation, as in recent related studies [13][14][15][16], as an alternative underlying asset.…”

Section: Introductionmentioning

confidence: 99%

Efficient Risk Management for Distributed Clean Energy: Principal Component based Weather Derivatives

Matsumoto,

Yamada

2024

E3S Web Conf.

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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.

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“…In particular, weather derivatives are extremely useful for hedging energy market-related risks, and in recent years, there have been a large number of applications in both practical and research contexts [6]. Moreover, pricing methods and specific applications of weather derivatives are presented in several pieces of literature [7][8][9][10], where previous studies have been mainly related to weather derivatives on a single underlying index such as temperature [11][12][13][14][15][16], but also solar radiation/irradiation [17,18] and rainfall [19]. In the context of wind power businesses, the recent increase in hedging needs, coupled with the increased demand for wind power to achieve decarbonization goals, has led to recent studies on wind derivatives.…”

Section: Introductionmentioning

confidence: 99%

Construction of Mixed Derivatives Strategy for Wind Power Producers

Yamada

Matsumoto

2023

Energies

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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.

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Pricing the risk due to weather conditions in small variable renewable energy projects

Cited by 4 publications

References 40 publications

Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Improving the Efficiency of Hedge Trading Using Higher-Order Standardized Weather Derivatives for Wind Power

Efficient Risk Management for Distributed Clean Energy: Principal Component based Weather Derivatives

Construction of Mixed Derivatives Strategy for Wind Power Producers

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