Multi-Stage Compound Real Options Valuation in Residential PV-Battery Investment

TL;DR

This paper presents a multi-stage real options valuation framework for residential PV-battery investments, accounting for uncertainties and multiple interacting options to optimize investment timing and value.

Contribution

It introduces a novel multi-stage compound options approach using least squares Monte Carlo to evaluate residential PV-battery investments under uncertainty.

Findings

Optimal timing of options increases investment value.

Framework effectively incorporates demand, fuel prices, and technology cost uncertainties.

Sensitivity analysis demonstrates robustness of the valuation model.

Abstract

Strategic valuation of efficient and well-timed network investments under uncertain electricity market environment has become increasingly challenging, because there generally exist multiple interacting options in these investments, and failing to systematically consider these options can lead to decisions that undervalue the investment. In our work, a real options valuation (ROV) framework is proposed to determine the optimal strategy for executing multiple interacting options within a distribution network investment, to mitigate the risk of financial losses in the presence of future uncertainties. To demonstrate the characteristics of the proposed framework, we determine the optimal strategy to economically justify the investment in residential PV-battery systems for additional grid supply during peak demand periods. The options to defer, and then expand, are considered as multi-stage compound options, since the option to expand is a subsequent option of the former. These options are valued via the least squares Monte Carlo method, incorporating uncertainty over growing power demand, varying diesel fuel price, and the declining cost of PV-battery technology as random variables. Finally, a sensitivity analysis is performed to demonstrate how the proposed framework responds to uncertain events. The proposed framework shows that executing the interacting options at the optimal timing increases the investment value.