Comparing the feed-in tariff incentives for renewable electricity in Ontario and Germany

Energy Policy 40 (2012) 480–489

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Comparing the feed-in tariff incentives for renewable electricity in Ontario and Germany Warren E. Mabee a,n, Justine Mannion b, Tom Carpenter c a

School of Policy Studies/Department of Geography, Queen’s University, 423 Sutherland Hall, 138 Union Street, Kingston, ON, Canada K7L 3N6 Faculty of Environmental Studies, York University, Canada c Queen’s Institute for Energy and Environmental Policy, Queen’s University, Canada b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 July 2011 Accepted 27 October 2011 Available online 10 November 2011

The development of feed-in tariff (FIT) programs to support green electricity in Ontario (the Green Energy and Green Economy Act of 2009) and Germany (the Erneuerbare Energien-Gesetz of 2000) is compared. The two policies are highly comparable, offering similar rates for most renewable electricity technologies. Major differences between the policies include the level of differentiation found in the German policy, as well as the use of a price degression strategy for FIT rates in Germany compared to an escalation strategy in Ontario. The German renewable electricity portfolio is relatively balanced, compared to Ontario where wind power dominates the portfolio. At the federal level, Canada does not yet have a policy similar to the European Directive on Renewable Energy, and this lack may impact decisions taken by manufacturers of renewable technologies who consider establishing operations in the province. Ontario’s Green Energy and Green Economy Act could be benefit from lessons in the German system, especially with regard to degression of feed-in tariff rates over time, which could significantly reduce payments to producers over the course of a contract, and in turn encourage greater competitiveness among renewable power providers in the future. & 2011 Elsevier Ltd. All rights reserved.

Keywords: Feed-in tariffs Renewable electricity Price degression and escalation

1. Introduction The introduction of feed-in tariff (FIT) programs for renewable electricity in Germany, and more recently Ontario, has promoted rapid development of new generation sources. In Germany, the FIT was first brought in as part of the Stromeinspeisungsgesetz (StrEG), and since 2000 has been part of the Erneuerbare EnergienGesetz (EEG). In Ontario, the FIT was introduced as part of the Green Energy and Green Economy Act (GEGEA) of 2009, which replaced an earlier standard offer program for renewable electricity. In both countries, the criteria for renewability adheres to international definitions, with qualifying technologies exploiting existing flows of energy or natural processes that are replenished constantly (see IEA, 2006; Little and van Berkel, 2006). Technologies covered by the FIT programs include those accessing wind, sunlight, geothermal heat, hydropower, tidal power, and biomass, with the latter category including production of biofuels as well as recovery of landfill gas and biogas from wastewater treatment and agricultural operations. The support provided for renewable electricity in both jurisdictions is justified using a familiar set of arguments. The single

n

Corresponding author. Tel.: þ1 613 533 6000x77092. E-mail address: [email protected] (W.E. Mabee).

0301-4215/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2011.10.052

strongest impetus behind this investment is economic growth and job creation, and language in both the GEGEA and the EEG speaks to the desire to create a sustainable energy economy that can lead in the global energy sector (Ontario, 2009; BMU, 2009). New project investment is expected to create local economic development in the renewable energy sector, and to generate subsequent incremental tax revenues and job opportunities for farmers, rural landowners, community groups, First Nations, and local businesses (Ontario, 2009). According to Little and van Berkel (2006), renewable energy generates four times as many jobs per megawatt of installed capacity as natural gas. A recent study conducted by Sovacool (2009) outlined the economic benefits in Germany of the EEG’s promotion of renewable energy, and estimated that by 2008, 157,000 jobs had been created in the German energy and related manufacturing industries (Sovacool, 2009). These jobs include the direct employment at the facility, as well as a wide range of indirect jobs across construction, technology manufacture, and government positions. At that time, this would have been the equivalent of 3.9 jobs per MW installed, based on a total installed capacity of 40.1 GW of renewable power. The Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) has reported higher figures, estimating that the number of direct and indirect jobs varies between 5 and 6.5 per MW (BMU, 2011). It has been estimated that an average investment of 2 billion euros per annum

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is required to employ between 8000 and 12,000 people directly across Germany (Lehr et al., 2008), a figure that can be heavily offset by the net economic benefit associated with exporting technology for renewable energy systems. Lehr et al. emphasize the need for exports to maintain positive net employment. By comparison, the Ontario Power Authority (OPA) estimates that the renewable electricity sector has created 13,000 direct and indirect jobs, including 2000 jobs related to the most recent round of contracts awarded (OPA, 2011a). With just over 3000 MW currently under contract, this represents about 4.3 jobs per MW, although as most of these projects are early phase it may be expected that the total number of jobs related to this capacity will grow. The David Suzuki Foundation had earlier anticipated the development of 77,000 direct and indirect jobs with the installation of 12,000 MW of renewable energy by 2020 (Little and van Berkel, 2006), which would be equivalent to 6.4 jobs per MW installed. Ontario’s strategy would seem to follow Germany, and thus achieving a net economic benefit based on the investment through the FIT will rely to some degree on the province’s success as a technology exporter. It seems clear that variation in employment is strongly related to the type of renewable electricity technology being employed, and that the expectations for employment in Germany and Ontario are very similar. Other arguments justify the investment in renewable electricity, including improving energy security, although the evidence in terms of operations and stability are not well documented. A diversified portfolio strengthens the energy system and reduces the risk of geographically centralized failures on the grid (Ontario, 2009). Such a portfolio is also essential when dealing with intermittent power sources such as wind and solar, where the capacity for effective power production (essentially the overlap between periods of electricity demand and the availability of sunshine or wind for power generation) has been reported at 30% for wind and 20% for solar after a decade of experience in Germany (BMU, 2011). Low capacity factors means that intermittent power sources must be backed up by dispatchable or baseline power, which in practice might mean a combination of different renewables or of renewable, fossil and nuclear options. Some suggest that ‘smart grid’ technology and better forecasting can increase the capacity factor of intermittent sources and therefore improve their competitiveness (e.g. Clastres, 2011). By investing in renewable energy now, countries can ensure they will have mature and competitive renewable energy industries in place before they are forced into transition away from fossil fuels. Renewable electricity also offers environmental benefits due to its low carbon footprint and potential for natural regeneration. Based on a lifecycle analysis, renewable energy tends to emit less carbon than traditional fossil fuels: in the mid-2000s, for example, the IEA estimated that total carbon emissions from a combined cycle turbine using natural gas were approximately 430 g/kWh, compared to only 98 g/kWh for solar photovoltaic technology (IEA, 2006). Germany has an important policy driver for implementing incentives for renewable electricity: as a member of the European Union, the nation is committed to honoring Directive 2009/28/EC, which sets a 20% target for the overall share of energy (including electricity) from renewable sources by 2020 (European Commission, 2009). Germany surpassed their 2010 target of 12.5% renewable electricity, achieving 17.4% by that date (European Commission, 2011), and expects to generate 38% of its electricity from renewable sources by 2030, according to the National Renewable Energy Action Plan (Germany, 2011). The EEG (and its FIT program) can be seen as a tactical policy used to achieve the strategic goal laid out in the Directive; importantly, the EEG is a response by the German government to a broader goal set by multiple nations including Germany.

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Unlike Germany, the Ontario policy is not a necessary step to meet broader goals set by the Canadian government or by some greater North American body. In Ontario, the GEGEA is a tactical policy set by the provincial government primarily to meet two provincial goals, increasing employment (as per Ontario, 2009) and shutting down coal-fired electricity generation in the province, which is currently scheduled to end by 2014 (OPA, 2010). At this time, there is no binding Canadian or North American target or mandate for renewable electricity production. Nor is there an organized or comprehensive market for carbon in North America that otherwise might reward avoided emissions.

2. Feed-in tariffs Feed-in tariffs are one of the most widely used incentive rate structures for stimulating the development of renewable electricity, and for creating conditions that reduce (but not eliminate) risk and improve investment security. In this context, a feed-in tariff is an agreement to pay a guaranteed amount for every kWh over a set period of time, for certain types of renewable electricity (Cory et al., 2009), encouraging investment from both small- and large-scale generators (Sovacool, 2009). This structure offers improved long-term security for investors, combined with the guarantee that all eligible renewable energy projects are granted priority to connect to the grid. The tariff rate is differentiated based on technology type and project size, and is structured so as to provide an equal opportunity for projects of varying sizes, although some technologies may receive favorable rates and thus experience more widespread uptake. Ideally, feed-in tariffs are a source of consistency and predictability for investors. Guaranteed payments from the tariffs provide investors with the confidence to invest the large sums of money required to construct and maintain renewable energy facilities (Rowlands, 2005). Small co-op groups, companies and communities are more inclined to participate given the investment security offered by the feed-in tariffs, and the result is a locally retained profit. Increased community involvement in turn assists with the political and social acceptance of renewable energy and helps to increase awareness of the benefits associated with renewable energy (Peters and Weis, 2008). A feed-in tariff also encourages technological learning. Engineers are persuaded to produce more efficient technologies to increase the amount of electricity generated and the rate of profit return from the initial investment. In a well-structured feed-in tariff system, a variety of technologies of different scales and stages of development are eligible for tailored incentives, which encourages development of renewable energy in many locations and circumstances, not just where the natural resource is more economically efficient (Rowlands, 2005). As with most policies, there are limits and potential pitfalls to the feed-in tariff for renewable energy. Although the tariff premium encourages the development of renewable energy in many locations, regional geographic features often create an agglomeration of development projects in specific areas that are conducive to that technology; a windy pass, for example, ends up filled with dozens of turbines. This physical clustering can increase social friction related to renewable energy, sparking ‘not in my backyard’ debates. In Germany and elsewhere in the EU, relatively high population densities have meant that large-scale renewable electricity projects, particularly wind projects, are faced with localized opposition. Even in Ontario, where the overall population density is relatively low, the siting of new renewable electricity projects is effectively limited by the range of the electrical grid and the position of major population centers, thus creating the opportunity for conflict (Yatchew and Baziliauskas, 2011).

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Another criticism of the feed-in tariff is that it increases the average home’s electricity bill, as the cost of the tariff is generally borne at least in part by the ratepayer. There is as yet no example of a market-based system where consumers have access to multiple suppliers within a system that utilizes feed-in tariffs, and therefore renewable energy is not power being generated at the lowest possible price (Lipp, 2007). It might be argued, however, that the goal of a successful feed-in tariff system is to incent generation using a variety of renewable electricity options, not to drive the generation of electricity at the lowest possible cost. Given this criteria for success, feed-in tariffs are increasingly viewed as successful policy mechanisms.

3. Evolution of the German FIT program Germany’s successful history of policy development for the promotion of renewable energy has also seen significant adjustments along the way. The Stromeinspeisungsgesetz (StrEG), introduced in 1991, was one of the most important instruments for the promotion of renewable energy in Germany during the 1990s (Runci, 2005). The StrEG was formulated based on the principle that feed-in tariffs should cover the investor’s costs of producing renewable energy in Germany, and it obligated public utilities to purchase electricity from renewable sources, such as wind, solar, hydro, biomass, and landfill gas. Under the StrEG, power utilities were required to buy the electricity at calculated rates between 65% and 90% of average electricity prices, which was meant to encourage individual and community production among large-scale electricity producers (Lauber and Mez, 2004). Hydro and particularly wind industries flourished under the StrEG. No provision was made to spread renewable generation evenly in geographical terms, and thus projects were clustered along Germany’s coast, where hydroelectric opportunities were available and where wind availability was high (Lauber and Mez, 2004). In 2000, Germany introduced the EEG, another major piece of renewable electricity legislation to replace and update this policy. The goals of the EEG included decreasing the costs of renewable electricity supply to the national economy, and promoting further development of renewable technologies. The EEG guarantees access to the grid and changed the FIT calculation from a system based on average electricity rates to a set of guaranteed rates. With the implementation of the EEG came the creation of the important tariff degression model. The degression model, which decreases the published tariff rate by a fixed percentage each year, is meant to take technological development into account, as discussed further below. The Act has been amended twice: in 2004, changes were introduced to provide differentiated tariffs for different renewable electricity technologies and at the same time to codify the 20% renewable electricity by 2020 target (Haas et al., 2011). Under the modified act, the grid operators were directed to evenly distribute the purchase of electricity volumes across the nation, which created an incentive for more geographically distributed generation (BMU, 2004). The Act was amended again in 2009, when some of the FIT rates were raised (particularly for wind), and degression rates accelerated for several technologies (notably wind and solar power) (BMU, 2009). Increased degression was brought in due to the rapidly declining price of solar panels and wind turbine components. As generation technologies become less expensive to produce, install, and operate, the premium that the government is willing to pay also shrinks. To account for this, the German government has introduced degression rates, which reduce the tariff paid to producers by a set rate, beginning at 1% per year. The degression percentage is higher in solar PV and wind than the other renewable energies, at 9% for solar PV (BMU, 2004, 2011; RESLegal, 2011). The high initial rate rewards early investments, while anticipation of

declining rates encourages more rapid development of increasingly efficient technology (Lipp, 2007). The degression model answers the problem of investors sitting back and waiting for cheaper technologies and processes and economies of scale (Ragwitz et al., 2010); they know that premium rates are not going to last, and they also know that the quicker they act, the higher the rate they will receive. Thus, the EEG is designed to deliver a majority of new renewable electricity projects in the near term. This impact is most dramatic for solar power, where rates can decline by up to 13% per annum (RESLegal, 2011). The German feed-in tariff program is made more subtle by the presence of a number of different bonuses or ‘adders’, which can be accessed by eligible projects. Some adders are offered for a limited time, such as specific bonuses for projects commissioned prior to a specific date. Others are regularly offered, such as technology bonuses, but the performance requirement to access these adders are adjusted on an annual basis. Some adders, such as the additional funding for the use of energy crops in bioenergy systems, effectively direct development to specific regions where crops are available (RESLegal, 2011). Germany’s feed-in tariff program has been the key incentive structure in the country’s successful renewable energy industry, offering predictable and attractive rates to communities and corporations. The incentives have worked. In progressing from the StrEG to the highly successful EEG, Germany has seen a significant growth in its renewable generation capacity over a relatively short period. With the mounting success of the program, the pressure on prices for power, i.e. the cost to consumers, has eased steadily and predictably. Importantly, manufacturing of renewable technologies has grown, and consequently so has the manufacturing workforce. Because the EEG most heavily incentivizes projects across Germany in the short term, in the longer term manufacturing jobs and products will increasingly rely upon the export trade (Lehr et al., 2008).

4. Introduction and evolution of Ontario’s FIT program The Province of Ontario’s first foray into support for renewable electricity was the Renewable Energy Standard Offer Program (RESOP) of 2006. Designed as a pricing regime for small renewable energy electricity generation projects, the intention of the RESOP was to provide incentives for renewable energy production among communities and large manufacturers, and to facilitate the government’s commitment to double Ontario’s renewable energy supply by 2025 (Gorrie, 2009). The requirements for production under RESOP were an installed capacity of less than 10 MW and connection to a transmission line. The RESOP locked producers into a 20year contract with the Ontario Power Authority, with all forms of renewable energy (wind, water, solar, and biomass) earning a fixed price of 11 cents per kWh, excluding Solar PV, which earned 42 cents per kWh (all figures Canadian (CDN) funds) (OPA, 2007a). By the end of 2008, the RESOP secured 443 contracts with the potential to generate 1419 MW of renewable energy; wind and solar PV accounted for 90% of capacity under development (OPA, 2009). The RESOP supported the province’s first Integrated Power System Plan (IPSP-1), created by the Ontario Power Authority in 2007 as a means of procuring green energy on a long-term scale (OPA, 2007b). There were various problems with the RESOP that led eventually to the formation of the Green Energy and Green Economy Act (GEGEA). Potential renewable energy producers were unable to access the grid in certain areas of Ontario and many communities reported difficulties obtaining financing to investigate the feasibility of renewable resource projects in their area (Ontario, 2009). The provincial government of Ontario recognized the need for a policy framework that would eliminate these barriers. In May of 2009, the

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GEGEA was adopted to create a sustainable energy economy that engages communities through meaningful incentives, while also improving the efficiency of the approvals process. The GEGEA was developed with the aim of making Ontario a competitive leader in the global renewable energy sector, and its implementation promises to diversify the province’s electricity portfolio. The GEGEA provides mechanisms that enable a wide spectrum of Ontarians to potentially participate. In addition to feed-in tariff incentives, the GEGEA offers community and First Nations development bonuses, which provide a slightly higher incentive for each project championed by these groups, as described below. In addition, the GEGEA theoretically makes it easier for investors in renewable electricity to obtain financing by providing a guaranteed revenue stream for accepted projects, which in turn reduces risk for lending institutions (Ontario, 2009). With the GEGEA, Ontario formerly introduced a FIT program, divided into two streams, microFIT and FIT. The microFIT program is applicable to projects generating less than 10 KW of electricity, while the FIT program is applicable to projects generating more than 10 KW of electricity. Both programs provide tariffs for Solar PV, wind, water power (hydropower), biomass, biogas, and landfill gas. The GEGEA is progressive in its encouragement of small-scale electricity development by communities, farmers, rural landowners, and First Nations. Aboriginal and community projects receive an ‘adder’, an additional price incentive meant to overcome barriers and higher project costs not encountered by commercial developers, such as requirements for greater consultation, longer development times, and difficulties with local resource availability among others (Brigham, 2009). Within the FIT program, the aboriginal and

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community price adjustments provide from 0.4 to 1.5 cents (CDN) per kWh on top of the feed-in tariff rates, depending on the energy source. Wind receives the highest price-adder at 1.5 cents per kWh, and biogas, biomass, and landfill gas with the lowest price-adder of 0.4 cents per kWh (OPA, 2011b, 2011c). The desired outcome is that the GEGEA will drive local economic development. The Ontario Power Authority, responsible for implementing the FIT program, has set rates for the feed-in tariffs depending on the project size and amount of electricity generated. With the exception of solar photovoltaic power, the rates are subjected to an escalation percentage, which applies to a portion (20%) of the contracted rate and adjusts that portion based on observed changes to the consumer price index over that period (OPA, 2011d). The purpose of the escalation percentage is to account for future inflationary pressures. The introduction of the FIT has elicited a very strong supply response, with applications totaling over 17.6 GW in hand, including 10.4 GW of wind power and 6.7 GW of solar photovoltaic (OPA, 2011e). It is worth reemphasizing that Canadian Federal policies do not require provinces to increase the amount of renewable sources in their electricity generation portfolios, and that means that federal policies do not provide any reassurance to investors that individual provinces will stick with the programs they undertake.

5. Comparing the FIT programs in Germany and Ontario The rates currently offered under Germany’s and Ontario’s FIT programs are provided in Table 1. It should be noted that

Table 1 Feed-in tariff rates in Ontario and Germany, 2011. Technology

Ontario FIT rates, 2011a Size ranges

CDN b/kWh

Germany FIT rates, 2011b Escalationc (%)

Biomass

Uptaked (%)

Size ranges

h b/kWh

CDN b/kWhe

Degression (%)

Uptakef (%)

7.5

r150 kW r500 kW r5 MW r20 MW

11.55–22.44 9.09–19.98 8.17–17.08 7.71–10.68

15.8–30.7 12.4–27.3 11.2–13.9 10.5–14.6

1 1 1 1

18.7

r10 MW 410 MW

13.8–14.8 13–14

20 20

Biogas

r100 kW r500 kW r10 MW 410 MW

19.5–20.5 16–17 14.7–15.7 10.4–11.4

20 20 20 20

1.4

r150 kW r500 kW r5 MW r20 MW

11.55–20.46 9.09–16.02 8.17–13.12 7.71–12.66

15.8–28 12.4–21.9 11.2–17.9 10.5–17.3

1 1 1 1

12.9

Landfill gas

r10 MW 410 MW

11.1–12.1 10.3–11.3

20 20

1.1

r500 kW r5 MW

8.87–10.84 6.07–8.04

12.1–14.8 8.3–11

1 1

0.7

Solar PV rooftop

r10 kW r250 kW r500 kW 4500 kW

80.2 71.3 63.5 53.9

– – – –

3.0

r30 kW r100 kW r1 MW 41 MW

28.74 27.33 25.86 21.56

39.3 37.3 35.3 29.5

9g 9g 9g 9g

11.7h

Solar PV ground

r10 MW

44.3–46.8

20

15.5

Any size

21.11

28.8

9g

Wind onshore

Any size

13.5–16

20

72.6

Any size

4.97–9.81

6.8–13.4

1

a

36.6

Sources for Ontario: OPA (2011b, 2011c, 2011d). Sources for Germany: Lang and Mutschler (2011), RESLegal (2011). c Escalation of Ontario feed-in tariff rates applies to a percentage of the total price, and is calculated based on the Consumer Price Index change as related to the first year of the contract. The formula for calculation may be found in on the website of the Ontario Power Authority (See OPA, 2011d). d The ‘Uptake’ column indicates the proportion of each renewable electricity type currently under contract and under development or in operation across Ontario, as of October 2011. e Average exchange rate for calendar year 2010 was CDN $1.3661: 1h (Bank of Canada, 2011). f The ‘Uptake’ column indicates the proportional contribution of each renewable electricity type to Germany’s energy supply as of December 2010, with total renewables ¼100% (BMU, 2011). g The degression of German feed-in tariff rates for solar power is fixed by law, and applies to a defined capacity of new installations. When capacity of new installations varies outside of the defined capacity, the percentage can be raised or lowered by a fixed number of percentage points (referred to as the ‘flexible cap’). For example, regular degression for ground mounted systems is 9%, but can increase by up to 4% or decrease by as much as 3% in 2011 (see RESLegal, 2011). h Note that figures are not currently available to differentiate roof-mounted and ground-mounted solar systems in Germany (see BMU, 2011). b

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Germany’s feed-in tariff rates are slightly more complex than Ontario’s, and extend to technologies not included in this table, particularly geothermal power; some of this complexity is omitted here to provide a clearer comparison between the German and Ontario programs. In both jurisdictions, most projects are offered 20-year contracts, with a few exceptions (primarily around hydroelectric power). The German fees are reported in h cents per kWh and converted to Canadian cents for the purpose of comparison; the conversion was carried out using the average exchange rate for 2010 (Bank of Canada, 2011). It can be seen that the lowest German tariffs (in categories comparable to Ontario’s program) are for wind power, followed by landfill gas, biomass-, and biogas-to-electricity, and finally solar power. In Ontario, landfill gas, biogas-, and biomass-toelectricity, and wind power have the lowest rates, while the rates for solar power are significantly elevated (see Table 1). Depending on the current foreign exchange rates, German FIT rates seem for the most part comparable to their Ontario counterparts, with solar photovoltaic power being the striking exception. It is interesting to note that the range of tariffs for different technologies is typically greater. For instance, Ontario-based biomass-to-electricity projects qualify for rates between 13 and 14.8 b CDN/kWh (depending on size and adders), while projects in Germany can qualify for rates between 10.5 and 30.7 b CDN/kWh. Similarly, the rates for biogas, landfill gas, and wind power fall across a greater range in Germany than in Ontario. This reflects the complexity of the German program, which offers a range of incentives pitched at multiple project scales. One striking difference with relation to biomass-to-electricity is the presence of an adder for heat within the German system, which allows combined heat and power facilities that more efficiently use the biomass resource to receive an increased incentive under the single program. This does not exist in the Ontario system, and may be a significant factor behind the lack of biomass-to-electricity projects planned in that jurisdiction. In both jurisdictions, there is an indirect relationship between the project’s size and the tariff rate: as a project’s size increases, the tariff rate decreases. This is to encourage small-scale development in communities by offering a fair rate to cover investment costs. The German system typically identifies a wider range of project sizes, and offers more specific ‘adders’ to the development of these projects (for example, biomass-to-electricity can benefit by employing energy crops, installing advanced technology, or producing combined heat and power) (RESLegal, 2011). The Ontario program was designed to be simpler than the German program, which has the benefit of increasing transparency and ease of administration, but which reduces the ability of the program to influence technology choice, project scale, and facility locations. One major difference between the Ontario and German programs is the rate associated with solar PV installations, where German rates have declined precipitously in the past four years. In part, this may be due to the timing of the Ontario GEGEA: the original FIT rates were calculated to provide acceptable rates of return based on solar PV technology costs available at the timing of writing, which was 2007–2008, but by the time the Act came into effect technology costs had already dropped significantly. The rapidly changing price of solar panels is the reason for the degression rate applied to the German incentive, which is set very aggressively at a 9% base with the potential for accelerated degression depending on the speed at which new projects are built (RESLegal, 2011). While originally the difference between Ontario and German rates for solar PV was smaller, the German system now offers about half that of their Ontario counterparts, with further degression to come. In Ontario, the control mechanism on FIT pricing is primarily in the form of a regular assessment carried out by the OPA, which

examines tariffs and recommends adjustments according to changes in equipment supply costs and exchange rates (Brigham, 2009); the first review is underway in the summer of 2011, and is scheduled to finish in early 2012. Based on the recommendations that come from this review, it is possible that Ontario tariffs for solar PV could be decreased significantly from current rates (as shown in Table 1), and brought closer in line with current technology costs. It is also worth noting that governments in both jurisdictions have shown that they are willing to adjust prices out-of-schedule. In the summer of 2010 Ontario reduced prices for ground-mounted solar PV projects in its microFIT program because of the higher-than-expected number of applications and rapid reductions in production costs. The German government has announced an unscheduled review of tariffs for solar projects, also because of substantial cost reductions for solar technology. Germany’s EEG has been very successful in encouraging renewable energy development. Since the 1991 StrEG, Germany has seen a steady increase in the renewable electricity generated. The renewable energy types that have flourished under the EEG are wind (which now contributes about 55% of Germany’s renewable electricity portfolio, not including hydro power) followed by municipal waste, biomass, biogas, and solar photovoltaics, each of which contributes significantly to the portfolio. Hydropower, which is largely a legacy power source in Germany as it is Ontario, contributes about 27% of total renewable electricity in the country. The rate at which Germany has added renewable energy to the electricity portfolio is instructive for the Ontario case. Over the past decade from 2000–2008, wind energy has grown from approximately 10 TWh to 38 TWh (BMU, 2011), while biomass energy has grown from approximately 5 TWh to 19 TWh. Between 1990 and 2003, the proportion of renewable energy in Germany’s electricity fuel mix expanded from 3% to 9% (Bohm and Vinicius, 2008; Runci, 2005). Between 2003 and 2010, renewable energy production has almost doubled, and now accounts for 17% of Germany’s electricity portfolio (Fig. 1). Germany’s renewable electricity sector can be considered mature after 20 years of experience and growth under different policy incentives, Ontario’s sector is still in its adolescence. Ontario’s first policy, the RESOP, was successful in creating 1419 MW of renewable electricity generating capacity in two years across 443 contracts. Since 2009, the GEGEA has facilitated 100 contracts representing 25 MW of power generation already in commercial operation, with 1859 additional contracts representing 4604 MW under development (OPA, 2011e). The average size of contracts offered has been approximately 13 MW, with priority given to facilities along major transmission lines (OPA, 2011e). To understand what the current contracts might mean to Ontario’s generating capacity, we estimated the outputs of production in the near future when these contracts come online. Our assumptions included capacity factors of 60% for hydro power and biomass power, 30% for wind power, and 20% for solar power, based on IESO data as well as similar factors reported in Germany (IESO, 2011; BMU, 2011). Again, it should be noted that capacity utilization would likely be lower than these figures, as intermittent generation is matched to demand. When all executed contracts achieve commercial generation status, Ontario would have the capacity to produce about 9.8 TWh per year, which would represent about 4.7% of total generation capacity, shown in Fig. 2. When coupled with hydroelectric power generation potential, the total renewable capacity in the province could be as high as 25.4% of total generation capacity. In comparison to Germany, the Ontario contracts are more heavily dominated by wind (72% of the renewable electricity portfolio, less hydro), followed by solar PV (18%) and solid biomass (7.5%). Hydropower, which has been widely exploited for decades in Ontario, continues to dominate the production of

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485

Germany (608.2 TWh*)

Primary Solid Biomass 19.3 TWh Biogas 14TWh Solar Photovoltaics 11.7 TWh Wind 37.8 TWh Hydro 20.6 TWh ALL OTHER SOURCES 504.8 TWh

*Reported contribution of renewable energy to electricity supply (BMU, 2011) Fig. 1. Reported electricity generation by source, Germany, 2008 (IEA, 2011).

Ontario Future (207.0 TWh*)

Primary Solid Biomass 0.7 TWh Biogas 0.2 TWh Solar Photovoltaics 1.8 TWh Wind 7.1 TWh Hydro 42.8 TWh ALL OTHER SOURCES 154.4 TWh

*Estimated generation capacity by source, 2012 (IESO, 2011; OPA, 2011e) Fig. 2. Estimated electricity generation capacity by source, Ontario, 2012þ (IESO, 2011; OPA, 2011e).

green electricity, accounting for 81% of the total renewable portfolio. Ontario has clearly chosen to focus on a few specific technologies, rather than a more ‘balanced’ portfolio of options as has been observed in Germany. According to the latest iteration of the Integrated Power System Plan (IPSP-2), the goal for renewable energy production in Ontario (less hydro) is 10.7 TWh by 2018, and 23.7 TWh per year by 2030. In the later year, the total power generation mix will include 10% wind power, 1.5% solar power, and 1.3% bioenergy (OPA, 2010). Due to the intermittent nature of solar and wind power, the 2030 targets will require significantly more generation capacity than currently available, an increase of more than 120% over the current or contracted renewable energy available on the grid (OPA, 2010). Without hydro, this level of production would be approximately equal to the output of Germany’s existing renewable electricity portfolio. With less diversity of generating options in the renewable electricity portfolio, however, questions may be raised about the ability of this approach to meet future requirements. Winfield et al. (2010) reviewed IPSP-2 and then reimagined its outcomes under a rigorous sustainability assessment framework. The results of this exercise were significantly different from the published plan, and emphasized that plan options need to be identified that can avoid major trade-offs among sustainability criteria in the social,

ecological, economic, and technological realms. One of the outcomes might be a more diversified energy mix, compared to a system more reliant upon one or two favoured technologies. There are many similarities between Ontario and Germany’s renewable energy policies. The structure of Ontario’s GEGEA was patterned to some extent after Germany’s EEG (as well as other similar policies), adopting various key characteristics such as community involvement and differentiated tariffs. The Ontario government has hoped to emulate Germany’s success in developing a renewable electricity sector as well as a strong manufacturing sector supplying technologies to the export market. Our analysis, however, shows that several significant differences exist between the jurisdictions, and that the outcomes to date are significantly different. One important difference, already touched on but deserving extra attention, is the difference between the two jurisdictions in terms of FIT rate escalation or degression.

6. The impacts of escalation and degression on FIT rates As shown in Table 1, Germany has a policy of degression, which applies to all FIT rates, while Ontario has introduced an escalation percentage, which indexes a portion of the contracted rate to inflation. This is a very different approach that suggests

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different philosophies between the two jurisdictions. To explore the ramifications of escalation vs. degression, we estimated Ontario and Germany’s contract prices for comparable 10 MW biomass, wind, and solar power facilities. In the case of Ontario, the assigned contract price for biomass and wind power is escalated according to an equation published by the OPA (2011d, p. 69) and reproduced below for ease of reference. As is made clear from this equation, the actual price depends heavily upon the inflation rate in any given year, as reported through the Consumer Price Index (CPI). In Ontario, solar power is not escalated, and contract prices remain constant     CPIx CPIy CPy ¼ ð1PEÞ  TCPBD  þ TCPBD  CPIBD CPIBD where, CPy is the indexed contract price in calendar year ‘y’ during the term; CPIx is the consumer price index in the month of December immediately preceding the calendar year ‘x’, where x is the contract date, TCPBD is the total contract price, in b/kWh, at the contract date, CPIBD is the consumer price index in the month the contract is signed, CPIy is the consumer price index in the month of December immediately preceding the calendar year ‘y’, and PE is the percentage being escalated. In the Ontario case, the total contract price (TCPBD) for a 10 MW biomass-to-electricity plant would be 14.3 b CDN/kWh in the base year, assuming that the project is eligible for additional funds through community or aboriginal participation. The total contract price for a 10 MW wind-to-electricity plant would be 13.5 b CDN/kWh, assuming that the contract is awarded at the base rate. The total contract price for a ground-mounted 10 MW solar-to-electricity facility would be 44.3 b CDN/kWh, again assuming that the contract is awarded at the base rate. We assumed an inflation rate of 1.6% based on historic changes to the Consumer Price Index (CPI) (Statistics Canada, 2011). The percentage being escalated is 20% for wind and biomass facilities. In the case of Germany, the calculation is much simpler. We estimate that the assigned contract price in 2011 for a 10 MW biomass-to-energy plant would be 14.59 b CDN/kWh, given a base rate of 7.71 h b/kWh and a 2.97 h b/kWh adder (technology bonus for combined heat and power). In Ontario and Germany, adders were selected to create hypothetical facilities that are eligible for comparable initial incentives. The assigned contract price for a 10 MW on-shore wind-to-electricity facility would be about 13.4 b CDN/kWh, assuming that the project was eligible for all available adders. Again, this puts the Ontario and Germany cases at approximately the same initial rate. For both biomass and wind facilities, the initial rate is degressed at a rate of 1% per year. In Germany, the assigned contract price for a ground-mounted solar-to-electricity facility would be about 28.8 b CDN/kWh, a rate that is already significantly lower than the Ontario case. This rate is degressed at an average of 9%, ranging between 6% and 13% (see Table 1). In Fig. 3, we provide the estimates of contract price and net present value over the 20-year term for the three renewable energy generation options. As shown in Fig. 3, the estimated FIT rates start at a very similar point for each project with the exception of solar. In every case the contracted rates diverge over the life of the projects. To understand the impact of this divergence, we calculated the net present value of the total contract in each case, using a discount rate of 8% and theoretical capacity factors of 60% for biomass, 30% for wind, and 20% for solar. It is clear that even with very similar starting contract rates, the Ontario system guarantees a larger payout over the lifetime of the project. In the case of biomass and wind power, the actual difference between the value of contracts depends primarily on interest rates, but the German model consistently costs about 10% less than the Ontario model. This difference would be true for a range of specific technologies,

Fig. 3. Estimated feed-in tariff contract price and net present value of contracts for (A) biomass, (B) wind, and (C) solar-to-electricity facilities sized at 10 MW in Ontario and Germany.

including biomass and wind as well as biogas and landfill gas, that have degression rates at about 1% per year in the German system. The difference between project costs for solar photovoltaic are much more pronounced, but harder to compare due to the already wide difference between Ontario and German FIT contract rates. Our analysis suggests that the Ontario model would pay out between 2.4 and 3.7 times more than the equivalent German contract for solar power. In all, these findings suggests that over the entire Ontario renewable electricity program, the full price of which is not yet known but which will be in the tens of billions of dollars, the increased cost created by the indexed price model is highly significant. The authors estimate that the nearly 2000 contracts already announced and expected to operate between 2012 and

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2032 have a net present value in excess of CDN$ 26 billion, depending upon the final application of rates and adders. If the escalation factor applied to wind, biomass, and hydroelectric projects were replaced with simple rate degression at 1%, and if the rates for solar power were degressed at 9%, the NPV of these contracts could be reduced by about 30% to approximately CDN$ 18 billion. Since these 2000 contracts represent only a part of the fully envisioned FIT program, the final savings could be even more significant. It has been noted by others that unless the cost of renewables, particularly solar PV, drop dramatically, the GEGEA program might not be sustainable (Yatchew and Baziliauskas, 2011). The data shown in Fig. 3 suggest that the Ontario model bears a particularly high price compared to the German model.

7. Lessons for Ontario The comparison of German and Ontario FIT programs suggests that three major differences exist between the two jurisdictions. Firstly, Germany’s EEG is strongly buttressed by a related policy, the European Directive on energy from renewable sources (European Commission, 2009). Germany has been very aggressive in responding to this Directive and is indeed on track to producing much more renewable electricity than stipulated in the Directive, with estimates of 38% renewable capacity by 2020 (Germany, 2011). Germany was the only large industrial member of the European Union that exceeded its targets for renewable electricity as of 2010, producing 17.4% compared to its target of 12.5%; by comparison, the United Kingdom, France, Italy, and Spain all missed their 2010 targets (European Commission, 2011). Moreover, the fact that the EEG and the Directive have been implemented by separate governments decreases the likelihood of a sudden shift away from this policy direction, as adjusted legislation would have to be proposed and passed in separate processes, and as changes within the EC would require support from a majority of member countries. While Ontario’s GEGEA is responding to broader policy goals set out by the Provincial government, most notably the proposed phase-out of coal by 2014, the fact that both policies originated with a single government means that it is relatively easy for future governments to abandon these priorities. Arguably, at this time in Ontario there is declining public support for phasing out coal and less political will to use renewable energy as the alternative. Germany’s commitment to a broader European goal provides more certainty to investors. For example, manufacturers of solar photovoltaic panels who are considering locating a production facility in Germany know in some detail what the FIT program will look like over the coming years, and they know that the FIT policy itself falls within a wider commitment and therefore is unlikely to change with shifts in the political wind. At the very minimum, there will be political costs to Germany within the EU if it fails to meets its EU renewable mandates. No such reassurance exists in the Ontario context, and indeed the current Leader of the Opposition has gone on record stating that he would cancel the FIT program should he be elected (Blackwell, 2011). Increased uncertainty around the long-term viability of the Ontario FIT program may have reduced investment in renewable energy projects, and this in turn would reduce the ability of the sector to optimize processes and reduce overall costs. A mandate from the Canadian federal government, or an inter-provincial agreement on increasing renewable sources of energy might increase the confidence of investors and move the province’s renewable sector forward more effectively. In Ontario, the first round of the FIT program is generous and has successfully spiked a great deal of interest among those who were ready to move quickly on installing generation capacity.

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The program, however, does not necessarily connect well to a long term energy plan. The very high proportion of wind energy represented by current contracts suggests that the incentives offered under the FIT are not promoting a balanced, sustainable portfolio. Arguably, the FIT does not take advantage of the local geography within Ontario; for instance, biomass has significant potential across the province, but represents only a small portion of the contracts currently being executed. The development of the renewable electricity portfolio in Ontario is meant to stimulate broader investment in the manufacturing sector of the province (Ontario, 2009). This investment could be significant; for example, Branker and Pearce (2010) estimate that investment in large-scale manufacture of solar photovoltaic panels in Ontario would provide return on investments in excess of 8% on investments exceeding $100 million. With a skewed portfolio of projects coming online, however, the attraction to potential investors in manufacturing is diminished. Thus, achieving the same rates of employment and associated benefits from renewable electricity development observed in Germany is less likely under the Ontario program. In future iterations of Ontario’s GEGEA, it is worthwhile considering the role of diverse price adders within the German system, which provide focused benefits attached to technological development, project scale and location, and renewable energy type. Finally, a major difference between the Ontario and German FIT programs is the application of escalation and degression (respectively) to the rates provided. There is a significant cost associated with the escalation policy over the degression policy, which may end up costing the Ontario government hundreds of millions of dollars over the next two decades. This cost is not easily borne, particularly in a province that is currently struggling with deficit, and we suggest that the degression model is a more suitable approach. We also note that the detail and nature of the FIT in Germany provides more reason for investor confidence than does the first iteration of the Ontario model. The promise that prices paid for renewable electricity will go down in a smooth fashion is in fact quite reasonable, and therefore reassuring to investors. Those who wish to install renewable generation capacity are given a financial reason to act quickly in order to get the best rates, and can see in advance what it will cost them if they do have to wait. The predictability of this system should reassure potential manufacturers, as it balances the provision of an ongoing incentive with fiscal responsibility and a clearly telegraphed system for rate adjustments. We suggest that amending the GEGEA to adopt the German model of degression to Ontario’s FIT rates would result in a more sustainable program for developing renewable electricity in the province. Most importantly, such a program would combine competitive rates in the short term with reduced government payouts over the longer term, reducing the burden on the public and encouraging the development of lower-cost technological options.

8. Conclusions Renewable electricity is the obvious option to fill the gap left in the electricity portfolio as fossil resources are withdrawn from use. In addition to providing low-emission, renewable and sustainable power from a variety of non-fossil sources, the development of new technologies is expected to provide significant employment benefits and corresponding revenue to local and federal governments. In anticipation of these benefits, both Germany and Ontario have chosen to use feed-in tariffs as their primary policy instrument for developing renewable electricity portfolios. For the most part, the rates offered by these two policies are similar; the major exception is solar photovoltaic

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power, which is supported at a much lower rate in Germany compared to Ontario. In Germany, the EEG is strongly supported by a European Directive on Renewable Energy; no such policy support exists for the Ontario GEGEA. The lack of supporting, complementary policy is one of the reasons that Ontario’s program might be viewed as being less substantial or permanent in comparison to Germany. After 20 years of experience with feed-in tariffs, the total amount of renewable electricity generated in Germany (not including hydroelectric generation, where most capacity predates the policy) accounts for almost 12% of total electricity generation. By comparison, Ontario’s GEGEA and its precursor, the standard offer program, have delivered about 3.4% of total generation capacity in 5 years. A major difference between the two jurisdictions is the variety of technologies that make up the portfolio. Three technologies (wind, solar PV, and biomass) make up the majority of Ontario’s generating capacity, while German renewable electricity generation is spread more evenly across five technologies and feedstocks (wind, biomass, municipal waste, biogas, and solar PV). The German system has developed more dispatchable power sources in concert with intermittent options, while the Ontario system has heavily favoured intermittent wind and solar power, perhaps due to the presence of existing hydroelectric capacity, which serves as baseline and dispatchable power for the Ontario grid. An important difference between the two systems is that the German FIT program is characterized by a greater number of options than Ontario’s program, including more differentiation in project scale, more adders for technology, feedstock, location, and outputs. In future iterations, we conclude that diversification of Ontario’s renewable electricity portfolio might be achieved through the inclusion of more options, which allow the instrument to become more focused. These options might allow Ontario to make better use of some localized opportunities, such as biomass, that are currently not being taken up at the same rate as solar photovoltaics and, particularly, wind. In particular, adders that provide support for heat as well as electricity, similar to those that exist in the German system, might promote more effective use of the biomass resource. There is concern over the cost of renewable electricity development. The German FIT program provides some measures to address these costs, notably the presence of a degression factor. We estimate that the use of a degression factor, rather than an escalation factor as employed in Ontario, could reduce total payout over the life of a program significantly (in terms of net present value), with savings in the billions over the course of the program. We suggest that the introduction of a degression factor be considered as a means of improving the cost of supporting renewable electricity in Ontario.

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