Pricing climate-related risks of energy investments

The latest study on "Pricing climate-related risks of energy investments" by Soh Young In, John Weyant and Yasat Berk Manav is published in Renewable and Sustainable Energy Reviews.

This study presents a new, integrated framework for pricing the #climateresilience of #energy #infrastructure assets comprehensively. It is designed to project the financial impacts of adverse climate scenarios, measured by conventional financial metrics. This asset-level and forward-looking climate risk assessment framework integrates climate data from multiple sources and scenarios into a project-finance-based valuation model and estimates an asset's financial default risks resulting from single or combined climate risk scenarios.

This framework is expected to also be able to demonstrate ways to integrate advanced climate-related risk #data. Its application can expand to broader infrastructure assets, particularly re-evaluating #strandedassets under the changing #climate and #market conditions. 

Abstract

This paper presents a framework for pricing the climate resilience of an energy infrastructure project through assessing the value of its required debt and equity investments. Integrating climate scenarios into an asset valuation model provides useful and specific insights for risk management, but there is a lack of academic and market tools that effectively address this need. The critical barrier is that climate-related risks (physical and transition) are typically indirect variables in the cash flow calculation, and they should be computed based on the direct variables such as revenue, capital expenditures, operating expenses, and financing costs. The implementation of this framework shows how to delineate climate-related risks that are asset-specific and transforms them into financial risks. Using cash flow simulation and scenario analysis, it estimates an energy infrastructure asset's probability of default due to climate-related risks and the size and timing of the losses for any given default. To demonstrate the framework's application, we simulate the price climate-related risks of a utility-scale electricity generation facility powered by natural gas.