The renewable energy market has seen rapid growth during the past few years. According to the Renewables 2010 Global Status Report (REN21 2010), investment in clean energy assets (not including large hydro) was $29.5 billion in the first quarter of 2010, 63% above that in the same period of 2009. The global capacity of many renewable technologies increased at rates of 10 - 60% annually during the period from the end of 2004 through 2009. In the power sector, though conventional fuels (fossil fuels and nuclear) remain the primary suppliers of global energy, power production from renewable energy (excluding large hydro) increased by 22% in 2009. Worldwide among all types of renewable power generating technologies, solar photovoltaic (PV) power continues to be the fastest growing power generation technology. Cumulative global PV installed capacity was almost six times larger in 2012 than in 2004 (REN21 2010). In 2009, about 16% of all new electric power capacity additions in Europe were credited to Solar PV (REN21 2010). In North America, an estimated 470 MW of solar PV was installed in 2009 in the United States (REN21 2010) where 1800 MW of PV is expected to be installed on the power grid by 2013. Over 1600 MW of PV was under development in Ontario, Canada at the end of 2011 (Ontario Power Authority 2011).
Some facts of solar PV power are particularly favorable for investors: 1) The source of solar photo-voltaic (PV) is free and clean; 2) Solar PV power is easier to predict and more reliable/stable than wind power. Sunlight levels, while still at the mercy of weather patterns, are not as unpredictable as wind speeds; the fact that solar cells don’t work at night is at least a predictable feature of their design; 3) Research (Rowlands 2005; Perez et al. 2012) conducted in the United States and Canadian electricity markets finds that solar PV power is highly associated with peak market demand and to somewhat lesser extent associated with high power prices. It also points out that the PV power is a potential solution to provide dependable peak power to meet growing summertime demand. However, investors must balance these desirable features against the high capital cost of solar PV power. Although a great deal of analysis has been done on the scientific and engineering development of solar cells, much less literature exists on the economic analysis of these cells. The paper by (
Powell et al. 2009) calculates various financial indicators for an “organic” solar cell. Their work uses an approach (complementary to the one taken here) for simulating ground level insolation measurements for which historical data does not exist. The repayment time metric is calculated in the (Powell et al. 2009) paper, but assuming market electricity prices, and finds that payback periods are too large to be economically viable. In a later work, (Azzopardi et al. 2011) compute the average cost of generated power metric for such organic solar cells.
The dramatic growth in the solar PV industry has come in large part because of substantial government support. In the first decade of the 21st century, the world’s major governments launched, updated or modified several programs to ensure that financial and administrative instruments are available to aid the development of renewable energy. Common policy measures for promoting solar PV power generation are feed-in tariffs, capital subsidies or grants, tax credits, net metering and direct public investment or financing. The most common policy used to encourage solar PV power is the feed-in tariff (FIT). A FIT offers stable prices under long-term contracts for energy generated from renewable sources. Germany is a pioneer and advocate for feed-in tariff policy among European countries. In 2000, Germany adopted the Renewable Energy Sources Act (Germany 2000), which is a replacement of the previous Electricity Feed Act launched in the 1990’s. The German Renewable Energy Sources Act turned out to be a great success and has since been amended several times. Following Germany’s success, between 2005 and 2010 at least 50 countries and 25 states or provinces adopted feed-in tariffs (REN21 2010). For instance, France adopted a feed-in tariff of EUR 42-58 cents/kWh for ground-mounted PV systems in 2009 (REN21 2010). Japan also implemented its first feed-in tariff of JPY 48/kWh for residential PV systems in 2009 (REN21 2010). In the Province of Ontario Canada, the current (2012) FIT program provides much higher rates than the market price for the electricity generated from solar PV. In addition, the rates are fixed even though the market price is variable. The Ontario FIT offers CAD 44 cents/kWh for large scale solar PV plants (Ontario Power Authority 2012). On the other hand, the monthly volume weighted average Hourly Ontario Energy Price (HOEP) between 2003 and 2011 has always been below CAD 10 cents/kWh (IESO 2012).
An investor in solar PV projects faces high risks, of which the three largest are: high capital costs, price risk, and volume risk. As mentioned above, high capital cost is indeed a concern but the trend of such costs is falling and capital subsidies may be available in local jurisdictions. Price risk arising from highly volatile electricity prices is another big issue in power plant financing. Even though solar PV power, which is not generated during the low demand night time hours, is associated with peak electricity prices (Rowlands 2005), this does not suffice to remove all price risk. The goal of a FIT program is to provide constant power rates, thereby removing price risk, and to make these rates sufficiently large that sufficient funds may be generated by the developer even in years which are not very sunny, thereby vastly reducing the impact of volume risk. This paper presents a statistical framework for answering the question of whether a given feed-in tariff is high enough to effectively eliminate both price and volume risk. The statistical framework is applied to show that the FIT tariff level in 2012 Ontario sufficed to eliminate solar farm volume risk, as measured by two financial metrics.
Risks other than volume risk include weather damage to panels from hail or snow, faster than expected degradation in panel performance due to extreme cold or heat and transmission line failure. This paper does not consider these risks, which may be hedged using insurance or product warranties.
This paper presents a representative case study from the city of London in the Canadian province of Ontario. The case study demonstrates how FIT performs as a financial inducement to promote solar PV power generation. We seek to answer the question: is the Ontario FIT price at the correct level? This question is answered using two types of financial metric. The first is based on the repayment time. This is the length of time a developer would take to repay the loan taken out to construct the solar farm. This repayment time will fluctuate according to future sunshine level patterns, and so will be a random variable; histograms of the outcomes of this random variable will be generated and reported. The repayment time conclusions are then reinforced using calculations of the Cash Flow at Risk (CFaR) metric (RiskMetrics Group 1999). The relatively new CFaR metric captures some of the risks due to uncertain cash flows in a way that is impossible for a more traditional engineering economic analysis performed using a Discounted Cash Flow approach (White et al. 2010). The CFaR metric reports the worst cash flow that can happen at a given materiality threshold; for instance, that 19 times out 20 the worst lowest cash flow that would be realized in a given year is X. Minimal work has focused on the application of the CFaR metric in the solar PV industry; this new metric will introduce an important new perspective for solar investors. The results of the repayment time and CFaR studies both show that the Ontario FIT levels were, in 2012, more than sufficient to cover the variable insolation risk considered here.
The rest of this paper is organized as follows. Section ‘Solar PV financial basics’ describes the financial basics of a solar PV plant. Section ‘Impact of volume risk on repayment time’ describes the methodology used to analyze repayment time of a solar PV plant and discusses the results. Section ‘Sensitivity analysis’ presents a sensitivity analysis. Section ‘Cash flow at risk’ presents a Cash Flow at Risk analysis. Section ‘Conclusions’ concludes the paper.