4th Year Project model code.
This code runs best when using Jupyter Notebook. Please ensure that you have the following Python libraries installed prior to running:
- Numpy
- Scipy
- Pandas
- Matplotlib
This project presents a novel approach to valuing renewable energy projects by incorporating multiple American-style real options within the binomial lattice framework. The goal is to develop a robust model that considers both cost stochasticity and managerial flexibility on the valuation of UK-based offshore wind farms. Our results demonstrate that when all three real options (abandonment, gearbox replacement, and generator replacement) are considered, the value of the wind project increases by £273.27 million, highlighting the significance of incorporating investment and operation flexibility into the valuation of wind farms. The model was examined at varying electricity prices, and it was found that the option value increases linearly with an increase in electricity price. At low prices, the abandonment option becomes dominant, and so after a certain value, the option price will increase with a decrease in electricity price. Moreover, the option value decreases exponentially with an increase in gearbox or generator replacement cost, while the option value increases exponentially with an increase in abandonment value.
This project emphasizes the potential for further research into modelling multiple Americanstyle real options. The framework introduced can be extended to incorporate more complex factors, such as more accurate cash flow forecasting of the wind farm, and to include other types of options, such as the option to delay operations or the option to expand. The model can be applied to a range of scenarios applicable to renewable energy projects, and its use can aid in the development of more and better renewable energy sources worldwide.