Martina Assereto

Martina Assereto

PhD Thesis Title: Evaluating and mitigating the financial risks of renewable energy integration systems: a real options approach

Supervisor: Dr Julie Byrne

External Examiners:
Associate Professor Michael Dowling
Rennes School of Business


This thesis includes four research papers that explore the application of a real options approach to evaluate and mitigate the financial risks associated with renewable energy investments.

The first paper, in Chapter 2, considers volatility as the key parameter for real option valuation and attempts to identify the best models to forecast volatility related to solar energy projects, with a focus on policy uncertainty. The United States is used as the country of reference, and we identify electricity prices and renewable credit prices as the main sources of uncertainty. We utilize a generalized autoregressive conditional heteroskedastic (GARCH) methodology that includes both individual models and combinations of models. The models are evaluated by carrying out in-sample and out- of-sample comparisons. We find that the GJR-GARCH model and the Constrained Least Square (CLS) combination are the best predictors for electricity prices, while the NGARCHK model and the Bayesian Model Averaging (BMA) combination provide superior forecasts for credit prices. We believe this paper is the first attempt to consider different sources of volatility for solar photovoltaic (PV) and the first to apply combinations of GARCH models to credit prices.

The second paper, included in Chapter 3, evaluates the financial feasibility of a solar PV project in New Jersey, United States. New Jersey has a successful Solar Renewable Energy Certificate (SREC) system in place as part of the nationwide renewable Portfolio Standard (RPS) program. We employ a real option approach in order to overcome limitations of the traditionally used discounted cash flow approach.

The real option is valued using the Least Square Monte Carlo method and we consider two main state variables: electricity price and SREC price. Our results prove that the option to defer the investment to a later date has a positive and significant value, and that the SREC program in place is successful in incentivizing investment. While the majority of real option papers assume a Geometric Brownian Motion for electricity prices, we utilize a more realistic GARCH model. In addition, this is the first study, to our knowledge, to evaluate an option to defer a utility-scale solar plant in a developed market like New Jersey.

The third paper (Chapter 4) explores the economic feasibility of utility-scale solar in Ireland by utilizing a real options approach. Currently very little electricity is generated by solar in Ireland, and the Irish Government recently unveiled plans to have 70% of electricity in the state generated from renewable sources by 2030. We identify electricity prices as the main source of uncertainty and use the Least Square Monte Carlo method to price the real option. We conclude that, due to the lack of policy support, investment in utility-scale solar in Ireland is discouraged and that, where the real option has value, the optimal strategy is to defer investment. This is the first research study, to our knowledge, to evaluate a solar PV plant in Ireland by employing a real options approach.

The fourth and last paper, Chapter 5, investigates the case of the Irish government introducing a Solar Renewable Energy Credit (SREC) support system for utility-scale solar photovoltaic, by using a real options approach. Currently, there is the absence of comprehensive policy support for solar in Ireland and large-scale investments are not commercially viable. Our results strongly suggest that introducing a credit system would incentivize investments in the solar industry. This is the first study exploring the possibility of introducing a credit system for renewable energy support in Ireland, as the majority of renewable energy technologies have been supported by Feed-in-tariff mechanisms to date.


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