| Work Detail |
A research group has proposed hedging default risk in the large-scale PV business using credit default swaps. The new methodology was tested using a series of Monte Carlo simulations and reportedly demonstrated how PV asset owners can transfer default risk to a protection seller at an affordable cost. An international research team led by Concordia University in Canada has created a new financial instrument that can help reduce the risk of default on solar photovoltaic energy projects. The novel approach uses credit default swaps (CDS) to provide an additional layer of financial security to PV project developers. A CDS is a two-party contract in which one party buys protection from another against losses arising from a borrowers default. “While PPAs ( power purchase agreements ) have traditionally been the cornerstone of revenue security for renewable energy projects, they do not fully protect against risks such as defaults, inaccuracies in resource data, or changes in fiscal and market conditions,” the researchers explain. “A CDS provides a mechanism to transfer default risk from lenders to third parties, functioning in a similar way to an insurance contract.” In the study “ Risk mitigation in project finance for utility-scale solar PV projects”, published in Energy Economics , the research team explains that the proposed framework involves the presence of a PPA sealed in a project finance agreement. Furthermore, it assumes that a special purpose vehicle (SPV) acts as a protection buyer by paying a premium to the protection seller, which compensates the SPV in the event of default. Under the terms of this agreement, the SPV is obligated to make periodic premium payments to the protection seller until the CDS agreement expires or default materializes. The new risk mitigation strategy also includes the use of a closed-form formula for assessing the probability of default (PD) over a given period, which the scientist says is key to setting the price of the CDS. The framework was tested using Monte Carlo simulations – a mathematical technique that predicts the possible outcomes of an uncertain event – ??on a 10 MW solar PV power plant located in Iran. For the analysis, the group relied on either satellite-derived solar irradiance data or ground-based solar data measured through site adaptation. “This analysis demonstrates the impact of solar irradiance data quality on default probability and CDS pricing, highlighting the financial sensitivity of large-scale solar PV projects to variations in resource availability and accuracy,” the academics said. The plant was assumed to have been built at €600 ($624)/kW installed and to have secured a PPA price of €45/MWh. The project lifespan was estimated at 30 years, while the loan was to last for 20 years. The scientists say their simulations show that the proposed approach significantly reduces the probability of default, while improving leverage ratios and project viability. “We also highlight the critical role of power purchase agreements (PPAs) in stabilising revenue streams and mitigating post-construction risks,” they added. “Our sensitivity analysis reveals that maintaining a minimum PPA price threshold is essential to ensure project viability at higher leverage ratios.” Looking ahead, they plan to expand the new methodology to other low-carbon projects and to regions with different incentive structures and mechanisms. The team also included researchers from the Australian Institute of Engineering Technology and Irans Tarbiat Modares University. |
