What are you waiting to invest in grid-connected residential photovoltaics in California? A real options analysis

ABSTRACT

The purpose of this paper is to assess the optimal choice of an investor, a typical household in California, United States, in terms of whether to invest or not, in a residential scale, grid-connected, solar photovoltaic system, aiming to obtain savings in their monthly electric expenses. If they invest, they shoulder a fixed upfront cost but also accept uncertain potential savings. If they do not invest, they forego any potential savings. To assess this irreversible decision, Real Options Analysis is deployed to assess the actual benefit for the household. This approach allows us to determine whether to trigger the investments and the optimal timing to do so. Our findings show it is optimal for our investor to invest in photovoltaics; however, some delay might be advised depending on the energy production factor of specific geographical areas and the expected useful life of the equipment. The results of this study also show that it might be optimal to delay the investment between 5.5 and 12 years in some areas, which is a drawback. Our findings also show that subsidies and other incentives do not seem to be a key driver in the above-mentioned investment decision. This study contributes to the existing literature by examining the present dynamic of residential grid-connected photovoltaic systems in the most relevant market for the United States and by including an assessment of uncertainty in both electric rates and photovoltaics prices, that accounts for seasonality, price escalation and price manipulation.

KEYWORDS:

• Renewable energy
• real options
• photovoltaics
• solar PV
• renewables
• investments under uncertainty

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 According to a CNBC in 2018 ‘California remains the undisputed leader when it comes to solar power in the Unites States, with almost 23 GW of installed solar’.

2 Real Option Assessments allow for dynamic analysis, as it accounts for uncertainty and continuous evaluation as further information is learned and then included into the assessment.

3 According to Jordan et al. ‘The average degradation rate still allows reasonable performance after 25 years’ (Jordan and Kurtz 2013).

4 Also known as electricity prices.

5 Not all states report enough projects to the OpenPV project database to allow for a fair assessment.

6 Montecarlo Simulations allow to simulate a number of sources of uncertainties that affect the valuation of our real option. According to Heijungs there is no clear argument for the number of runs recommended on Montecarlo simulations, but 10,000 are commonly use and can ‘accurately [used for] estimating an output distribution on the basis of perfect knowledge of the input distributions’ (Heijungs 2020).

7 Representative Agent Model.

8 Let $(\mathrm{\Omega },F,{\{F_t\}}_{t\in I},P)$ be a filtered probability space, that is, a probability space equipped with a filtration of $\sigma$-algebras. Then the random variable ${\tau }_A$ is a stopping time if $\{\omega \in \mathrm{\Omega }:\tau (\omega )\le t\}\in F_t$, that is, the decision to stop waiting and to invest is only based on historical data.

9 Also EPF represents the amount of energy to be produced by each kW of PV installed capacity, this amount is determined on average by geographic location and determined in kWh/year. Further detail on different geographic areas of the United States For further information see (U.S. Department of Energy 2016)

10 For this setting, >20.00 suggests that the there is no optimal stopping time within 20 years.

11 At the time that this article was written, only the latter had passed.

12 If implemented, these charges could set a floor price for energy limiting the potential of savings described in this work. No fixed monthly charges are expected to be introduced before 2020.