REN Yifang ZHAO Yanxia CHEN Sining SUN Qin LI Muyuan LIU Li ZHANG Yi

To address the strong weather dependence of the new energy industry and the limitations of traditional insurance, it is imperative to accelerate the application of weather index insurance in new energy risk management. Taking the Beijiang River Basin as a case study, this paper utilizes meteorological data from 1984 to 2023 and runoff data from 2003 to 2017, combined with hydrological and power generation potential models, to analyze the spatiotemporal distribution characteristics of solar and hydrological climate resources on a monthly scale. Through core processes such as setting insurance trigger thresholds, determining net premium rates, formulating compensation schemes, and simulating historical claim payments, a basin-level photovoltaic and hydropower index insurance product is designed and applied. Furthermore, Kendall rank correlation analysis and the percentage decrease method of insurance loss ratio standard deviation are employed to systematically conduct quantitative analysis on the hedging performance of the photovoltaic and hydropower index insurance product across different spatiotemporal scales and evaluate its effectiveness under varying proportional configurations. The results show that the photovoltaic and hydropower index insurance, which uses monthly solar radiation and runoff as indices, can provide insurance schemes with different risk coverage levels by setting monthly compensation trigger thresholds based on exceedance probabilities. The annual average monthly net premium rates of the photovoltaic and hydropower index insurance under the claim standards of P95, P90, and P85, as well as P76, P74, and P72 are 7.1%, 9.7%, and 11.8%, as well as 7.1%, 19.7%, and 39.9% respectively, with the annual average monthly cumulative compensation ratios being 5.5%, 9.1%, 12.9%, 6.3%, 15.1%, and 28.8% correspondingly. The spatial hedging performance of the photovoltaic and hydropower index insurance is superior to that of single-factor power generation index insurance. In the same spatial range, the complementarity of photovoltaic and hydropower generation potential is generally strong from June to October, showing a distribution pattern of "stronger in the southeast and weaker in the northwest". In different spatial ranges, the risk diversification effect of the photovoltaic and hydropower index insurance is stronger than that in the same spatial range, and the performance of "hydropower hedging against photovoltaics" is better than "photovoltaics hedging against hydropower". In the scenario with the strongest hedging performance, when the proportion of photovoltaic and hydropower index insurance products is 7:3, the volatility of the loss ratio of the "hedging-type" insurance product is minimized, with the maximum percentage decreases in standard deviation of loss ratios relative to standalone photovoltaic and hydropower insurance reaching 19.2% and 51.9% respectively. Therefore, by optimizing the proportion of photovoltaic and hydropower index insurance products, the volatility of the loss ratio of "hedging-type" insurance products can be effectively reduced, and their overall operational stability could be improved.