Statistical Decision-Theoretic Risk Management for Planning Renewable Energy Pathways

The world has witnessed an increase in the level of investments for renewable energy technologies in the past decade mainly owing to the pressure for mitigating greenhouse gas (GHG) emissions, whilst addressing the issue of climate change. According to recent statistics, global investments edged up by 2 % in 2019 to $301.7 billion, taking the value of cumulative investments since 2004 to $3.5 trillion, which has been attributed to the falling costs of solar and wind technologies. With the commissioning of additional capacities from renewable energy sources each year, there is a growing need for managing the associated risks and uncertainties from the perspective of different stakeholders throughout the planning, development and operational phases. Renewable energy sources entail considerable technological and financial risks exposure, depending on the location where the technologies are implemented, and thus needs to be managed using techniques that would provide both the quantification of risks and optimal decisions that lead to risk mitigation. The objective of the proposed research is to develop a probabilistic framework which broadly includes: (a) statistical modelling of financial risks - such as variability of revenue due to electricity price, demand fluctuations, generation costs, or other market conditions; and (b) evaluating options that maximise the stakeholders’ utility/reward functions, or minimise risks, for a given technology mix. This research demonstrates the implementation of binomial lattice model in real options analysis (ROA) for the valuation of investments on diversified energy portfolios. The framework is applied to analyse the impact of risks and uncertainties on capital budgeting decisions relating to project size (expand or contract); project life and timing (initiation, deferment or abandon); and project operation (flexibility in the technology mix) for scenarios involving large-scale deployment of renewable energy sources.