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Schlagwörter:
Cost of capital, Default risk, Carbon pricing, Forecasting, Machine learning
Zusammenfassung:
As support mechanisms aimed at promoting investment in renewable energy are phased out, producers must consider electricity market risk. Market price exposure affects economic feasibility of investment by making producers’ revenue stream vulnerable to the merit-order effect and by increasing revenue risk, which leads to higher costs of capital. The cost of capital is detrimental to the profitability of capital-intensive renewable energy sources, such as wind and solar power. To analyse the connection between electricity market exposure, the merit-order effect and the financing costs of wind power, this paper models the cost of capital of wind power investments in West-Denmark based on simulated return distributions. The return distributions are generated using a novel price forecasting model, an Adaptive Network-based Fuzzy Inference System, that predicts hourly prices from the residual load, natural gas price, and carbon price. Although it is a purely data-driven model, it reproduces the merit-order effect. The results emphasise the importance of recognising the endogenous changes in financing costs for accurate assessments of the profitability of wind power projects and the design of effective policies for incentivising renewable energy investments. The findings suggest that a higher carbon price can improve revenue distributions and lower financing costs, but its effectiveness diminishes at high levels of installed wind capacity.
