Solar PV electricity and market characteristics: two Canadian case-studies

Renewable Energy 30 (2005) 815–834 www.elsevier.com/locate/renene

Solar PV electricity and market characteristics: two Canadian case-studies Ian H. Rowlands* Department of Environment and Resource Studies, Faculty of Environmental Studies, University of Waterloo, Waterloo, Ont., Canada N2L 3G1 Received 16 July 2004; accepted 3 August 2004 Available online 30 November 2004

Abstract To determine whether solar electricity (that is, electricity generated by photovoltaics) is, on an average, more valuable—in market terms—than the electricity generated in power systems as a whole, this article investigates the extent to which solar resource availability in two Canadian locations is associated with peak electricity market demand and peak electricity market price. More specifically, solar radiation and electricity market data for the period 1 May 2002 to 30 April 2004 are examined for Calgary, Alta. and Guelph, Ont. A variety of visual and statistical investigations reveal that solar radiation values coincide closely with peak electricity market demand and, though to a somewhat lesser extent, peak electricity market prices during the summertime in each location. While more detailed investigation is needed in order to determine the specific impact of different levels of PV penetration upon provincial electricity markets, the article provides ample encouragement for further research. The article also shows how different techniques can be used—in any location—to investigate the relationship among solar electricity potential, system-wide demand and market prices. With electricity industries being restructured around the world, it continues to be important for solar energy proponents to participate in discussions regarding economic costs and benefits. Techniques used in this article can help them advance the solar electricity case more effectively and thus catalyse the deployment of photovoltaics in markets around the world. q 2004 Elsevier Ltd. All rights reserved. Keywords: Canada; Electricity; Markets; Photovoltaics; Prices

* Corresponding author. Tel.: C1 519 888 4567x2574; fax: C1 519 746 0292. E-mail address: [email protected]. 0960-1481/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.renene.2004.08.001

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1. Introduction Conventional wisdom suggests that photovoltaics (that is, panels to generate solar electricity) should be deployed where the sun shines the brightest and the longest. It is only logical, the argument continues, that the performance of solar panels will be maximised when they are exposed to the most sunlight. While it is certainly the case that this would maximise the amount of electrical energy produced, it would not necessarily maximise the ‘value’ of the solar electricity that could be generated by the panels. Given the unique nature of electricity as a commodity (in particular, the fact that it cannot be easily stored), all energy generated by photovoltaics (or, indeed, by any power source) is not valued equally. Instead, electricity produced during times of peak market demand and/or peak market price will be valued—either informally or formally—more highly. If, therefore, solar electricity can show itself to be especially available during these peak periods, it will come to be more valued by society than would otherwise be the case. While there has recently been much work investigating the extent to which solar electricity is available during peak periods, most of this work has been undertaken in the United States [1–4]. Other countries that have both high electricity demand and significant solar resources have received relatively less attention (Ref. [5] is an exception). One such country is Canada. Although relatively small compared to the United States, Canada is nevertheless still a significant electricity market, ranking fifth in the world in terms of generation and sixth in terms of consumption (2001 figures [6]). Moreover, although its deployment of solar electricity to date is modest, its large land mass—parts of which receive significant quantities of solar radiation—means that Canada has huge potential in this area. More specifically, at the end of 2002, installed PV capacity in Canada stood at 9997 kW, which meant the country ranked 10th of 20 reporting countries of the International Energy Agency. This figure, in per capita terms, was 0.32 W/person, which ranked 12th of 20 [7]. Moreover, some Canadian locations receive on a horizontal surface, on an average, more than 15 MJ/m2 of solar radiation per day. Large stretches— including most of Canada’s urban areas—receive more than 12 MJ/m2 a day [8]. Given this, the purpose of this article is to determine the extent to which solar resource availability in two Canadian locations is associated with peak market demand and peak market price. This will allow us to conclude whether solar electricity should be more or less valued than a conventional ‘energy mapping’—that is, a calculation that solely considers energy production—would suggest (this ‘conventional energy mapping’ has also been called the ‘traditional view’ with respect to solar energy [9]). The article is divided into five main sections. After this brief introduction, the context is set in Section 2. In this, the two Canadian locations for investigation are introduced, and their historical electricity demand and solar resource profiles are presented. The data that are used in the subsequent analysis are also described. In Section 3, the relationship between solar resource availability and electricity market demand is investigated. Similarly, the relationship between solar resource availability and electricity market price is studied in Section 4. Finally, the results are scrutinised, and the policy and research implications highlighted in Section 5.

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2. Context We focus this article upon two provinces in Canada—namely, Alberta and Ontario— for three reasons. First, they are large: Ontario is Canada’s second-largest generator of electricity (of 10 Canadian provinces) and Alberta, Canada’s fourth largest (2002 figures [10]). Second, these two electricity supply systems are responsible for 71% of Canada’s electricity-related greenhouse gas emissions—and 13% of Canada’s total greenhouse gas emissions [11]. More specifically, in 2000, Alberta’s electricity industry-generated 51 Mt of greenhouse gases (carbon dioxide equivalent) and Ontario’s 40 Mt. Canada’s total greenhouse gas emissions in 2000 were 726 Mt carbon dioxide equivalent [11]. With Canada having ratified the Kyoto Protocol, these provinces are strong candidates for greater use of renewable resources in their power supply systems. And third, Alberta and Ontario are Canada’s ‘pioneers’ in terms of electricity industry restructuring: each has opened its electricity supply system to competition and market forces. Therefore, renewable energy entrepreneurs have greater opportunity to participate in these provinces’ electricity supply systems. In Alberta, electricity supply is dominated by coal-fired power stations (which supplied 66% of the province’s electricity needs in 2002 [12]). The system has its overall peak demand in winter (driven by heating demands), with a smaller peak in summer (driven by cooling requirements). Overall energy use is approximately 65 TW h a year. Table 1 provides more details. In Ontario, nuclear, coal and large hydro stations all make significant contributions to the province’s electricity supply. The system has experienced a fundamental change during the past 5 years, moving from a winter peaking situation to a summer peaking one. Driving this is increasing demand for air conditioning in the summer (accompanied by reduced use of electrical heat in the winter). Total energy use is approximately 152 TW h a year. Table 2 provides additional information. Within these two provinces, we select individual communities for further investigation—namely, Calgary, Alta. and Guelph, Ont. (see Fig. 1 for location). Data regarding solar radiation on a horizontal surface—averaged over a 10 year period—for each of these communities are presented in Table 3. The majority of annual solar resource availability occurs in the summer months: between April and September (inclusive), for example, 75.8% of Calgary’s solar radiation is received and 73.2% of Guelph’s. The period investigated in this article is 1 May 2002 to 30 April 2004. This provides a continuous 2-year period in which both electricity market and solar radiation data are available. Electricity information—more specifically, system demand and system Table 1 Alberta’s electricity profile

Peak winter demand in MW (month) Peak summer demand in MW (month) Total energy demand in TW h

2002

2003

8570 (December) 8217 (July) 64.9

8786 (December) 8295 (July) 62.7

Sources: [12]; Alberta Electric System Operator.

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Table 2 Ontario’s electricity profile

Peak winter demand in MW (month) Peak summer demand in MW (month) Total energy demand in TW h

1996

1997

1998

1999

2000

2001

2002

2003

22,321 (January) 21,428 (August)

22,197 (January) 21,667 (July)

22,067 (December) 22,443 (July)

23,308 (January) 23,435 (July)

23,428 (January) 23,222 (August)

22,672 (January) 25,269 (August)

23,334 (December) 25,414 (August)

24,158 (January) 24,753 (June)

137.4

138.4

139.9

144.1

146.9

146.9

153.3

151.7

Source: Independent Electricity Market Operator of Ontario.

price—were provided by the Electric System Operator (Alberta) and the Independent Electricity Market Operator (Ontario). In both cases, hourly prices, representing the payment for the energy component of electricity that would be made to electricity suppliers, and system-wide electricity demand were obtained. Solar radiation data, meanwhile, were taken from the University of Calgary’s Weather Station (51.048N, 114.088W) and the Guelph Turfgrass Institute (43.558N, 80.218W). In both locations, a flat plate collector was used to record hourly values of solar radiation (an Epply PSP Pyranometer in Calgary and a LiCor Pyranometer in Guelph). Although

Fig. 1. Two study locations [8].

Calgary, Alta. Guelph, Ont.

January

February

March

April

May

June

July

August

September

October

November

December

Total

3.1

6.3

11.4

17.1

19.8

21.2

22.9

17.0

13.4

8.4

4.0

2.6

12.3

4.9

7.6

11.4

15.5

19.7

22.5

21.9

18.3

14.1

8.8

4.8

3.9

12.8

Source: NASA.

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Table 3 Solar radiation received on a horizontal surface, daily average (MJ/m2) [22]

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investigations into the optimal tilt for solar PV structures suggest that an angle of either the location’s latitude (to maximise annual energy generation) or latitude minus 158 (to maximise summer energy generation) is preferred [13: 17 and 18,14: 38], our use of the data from the flat plate collector (that is, at an angle of 08) effectively models how PV panels are often mounted on commercial roofs [15, p. 4].

3. Solar availability and electricity market demand We begin the analysis by investigating the relationship between solar resource availability and electricity system load, considering Alberta and Ontario in turn. 3.1. Alberta In the case of Alberta, Fig. 2 compares these two variables on two axes, using hourly averages over the entire 2-year period under investigation. While solar radiation values peak at 13:00, demand displays two peaks: the lower one at 12:00, and the higher one at 18:00 (note that all times in this article are reported in local standard time. Calgary, Alta. is located in the ‘Mountain Time Zone’, while Guelph, Ont. is located in the ‘Eastern Time Zone’. Additionally, when values are reported at a particular time, they represent the value for the hour up to, and including, that time). Nevertheless, simple observation suggests that there appears to be—at least at times—a direct, and positive, relationship between solar resource availability and electricity system load. What may be hidden within this picture of the entire 2-year period (Fig. 2), however, is any variation within an individual year. The discussion in Section 2 above has already revealed that solar resource availability in Calgary has traditionally peaked in June and July, while electricity system demand in Alberta has usually reached its maximum values

Fig. 2. Average hourly solar radiation and system demand, Alberta, annual.

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Fig. 3. Average hourly solar radiation and system demand, Alberta, December.

in December and July. This inspires us, therefore to look at the case of individual months during the Albertan winter and summer. Figs. 3 and 4 compare hourly averages for solar resource availability and electricity system for, respectively, the months of December and July. Fig. 3 shows that there remain two electricity demand peaks during December, but that the 12:00 peak is markedly lower than the 18:00 one. While the peak value for solar radiation remains at 13:00, its amplitude is much lower than the annual average already reported—it is less than half as intense as the overall average. Fig. 4, meanwhile, reveals that there is a single peak demand period for electricity in the month of July—namely, 15:00. Solar radiation, meanwhile, reaches its peak at 13:00 at a level 65% higher than the average annual value (at 13:00). Thus, for reasons related to both ‘quantity available’ and ‘when it is available’, it appears that PV has greater potential to meet summer peaks than winter peaks. For this reason, the focus for Alberta in the rest of this section is upon the summer months.

Fig. 4. Average hourly solar radiation and system demand, Alberta, July.

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Table 4 Potential PV contribution in Alberta (April to September) Percentage of peak demand

98 (O8129 MW) 95 (O7880 MW) 90 (O7466 MW) All hours

All peak demand periods

Daytime peak demand periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

33 265 1431 8784

72.9 64.4 46.8 21.4

33 265 1329 5395

72.9 64.4 50.3 34.9

More specifically, we study April to September generally and July specifically. The former represents the 6-month period with the greatest solar resource availability in Calgary; the latter is the month not only with the most solar resources available, but also the summer month with the highest peak demand and overall energy load in Alberta. For these two periods, we investigate the extent to which solar PV is well-placed to meet peak demand by means of three distinct statistical investigations. First, following Taylor [16], we calculate the Pearson’s two-tailed correlation coefficient, relating solar radiation and electricity demand. For daylight hours between April and September (inclusive), the coefficient has a value of 0.397, which is significant at the 0.01 level (nZ5395). This suggests that demand correlates strongly with solar radiation during this period. Moreover, when we examine July, the correlation is even stronger: the coefficient value is 0.558, which is significant at the 0.01 level (nZ983). Second, following Taylor [17], we focus upon those summer periods during which the load was at least 90, 95 or 98% of the summer peak load (in Alberta during 2002 and 2003, the peak summer load was 8295 MW at 15:00 on 31 July 2003). For each of these periods, we then calculate the potential PV contribution. We define ‘potential PV contribution’ as the level of solar radiation available as a percentage fraction of the maximum solar radiation received at the site during the 2-year period under investigation. That latter value, for this case, is 3.630 MJ/m2, which occurred during the hour ending 13:00 on 7 June 2002. Hence, the value for potential PV contribution—which will be somewhere between 0 and 100%—reveals how well PV could contribute to meeting the system-wide load during peak demand periods (see [4,18] for similarly inspired investigations). Table 4 provides full results for the April to September period, and Table 5 for the month of July. Table 5 Potential PV contribution in Alberta (July) Percentage of peak demand

98 (O8129 MW) 95 (O7880 MW) 90 (O7466 MW) All hours

All peak demand periods

Daytime peak demand periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

22 140 465 1488

73.9 69.7 55.7 28.1

22 140 448 983

73.9 69.7 57.8 42.5

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Two points are worth making here. First, the vast majority of peak demand periods during the Albertan summer occur during the day. Indeed, all 265 periods in which demand was greater than 7880 MW (the 95% threshold) were during daylight hours. And second, as demand peaks, there is more and more solar radiation available for electricity generation. The belief that the sun warms the air, thus catalyzing greater air conditioning use, therefore driving up electricity demand appears to be confirmed here. Thus, solar power is well-placed to help meet periods of peak summer demand in Calgary, with potential PV contribution standing at approximately 70% of the maximum possible during the hours with the greatest demand. Third, following Letendre et al. [4] and Perez et al. [9], we examine a key summer peak event and calculate the ‘PV availability’ during that period. PV availability refers to the solar radiation received as a percentage of the maximum solar radiation that would have been received with completely clear skies throughout the day. It provides an indication of how well a PV panel would have performed (in terms of power produced) as compared to its performance on an ‘ideal day’. In Alberta, the electricity system experienced its greatest periods of summertime demand on 31 July 2003. Not only did the highest single summer demand value occur at this time (as already noted above), but this day also experienced the second, third and fourth highest summer demand levels witnessed during the 2 years under investigation in this article. Using methods for the ‘estimation of clear sky radiation’ outlined in [19, p. 73–76], we find that the standard clear day radiation for Calgary, Alta. on 31 July is 26.4 MJ/m2. Actual radiation for this day in 2003 was 22.9 MJ/m2, which yields a value for PV availability of 87%. 3.2. Ontario We now turn to Ontario, and we repeat the steps undertaken for Alberta to investigate the relationship between solar resource availability and electricity system load. First, consideration of hourly averages (Fig. 5)—for the entire 2-year period—reveals that there

Fig. 5. Average hourly solar radiation and system demand, Ontario, annual.

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Fig. 6. Average hourly solar radiation and system demand, Ontario, January.

appears to be a close correlation between average solar availability and average system demand, at least for part of the day. While solar availability peaks during the hour ending 13:00, demand experiences two peaks: one at 12:00 and the other at 18:00. We also, however, explore seasonal differences. The discussion in Section 2 above has already revealed that solar resource availability has traditionally peaked in June and July, while electricity system demand has usually reached its maximum values in January and either July or August. This, therefore, inspires us to look at January and July as individual winter and summer cases. Figs. 6 and 7 present these cases. Reflecting differences in weather conditions across the year, the January evening peak (19:00), is much more pronounced than its mid-day (11:00) counterpart—on an average it is almost 8% higher (for the year as a whole, the evening

Fig. 7. Average hourly solar radiation and system demand, Ontario, July.

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Table 6 Potential PV contribution in Ontario (April to September) Percentage of peak demand

98 (O24,906 MW) 95 (O24,143 MW) 90 (O22,873 MW) All hours

All peak demand periods

Daytime peak demand periods

Number of hours (%)

Potential PV contribution

Number of hours

Potential PV contribution (%)

24 81 241 8784

64.3 58.6 51.9 21.9

24 79 229 5277

64.3 60.1 54.6 36.5

peak is only 2% higher than the mid-day peak). In July, meanwhile, although there are two peaks, the earlier one (17:00) is more than 6% higher than the later one (at 21:00). Given this, and the difference in solar availability—almost four times as much solar energy is available in July as in January, and the peak value in July is more than twice as high as the peak value in January—it appears that solar PV is much better placed to meet summer peak demand than winter peak demand. The apparently close correlation—at least as it appears visually—between solar radiation and electricity demand encourages us to undertake the same three statistical investigations that we did for the Alberta case. First, a two-tailed Pearson’s correlation for the daylight hours during summer months (April to September, inclusive) yielded a coefficient value of 0.272, which is significant at the 0.01 level (nZ5277). This suggests that solar radiation and electricity load values track each other closely. Restricting this analysis to the months of July and August (when demand and solar resources have traditionally been high), we find an ever closer association—0.347 is the Pearson’s correlation coefficient, which is significant at the 0.01 level (nZ1830). Second, we took the summer peak value (25,414 MW, which was reached on 13 August 2002 at 14:00), and explored the potential PV contribution during demand times which approached this peak load. Potential PV contribution was calculated against a ‘benchbenchmark’ value of 3.533 MJ/m2, which was recorded during the hour ending 12:00 on 24 May 2003. Tables 6 and 7, which provide full results, show that the same two key points we made in the Alberta investigation can be revisited here. First, the vast majority of peak demand periods occur during the daytime. And second, as demand moved closer Table 7 Potential PV contribution in Ontario (July and August) Percentage of peak demand

98 (O24,906 MW) 95 (O24,143 MW) 90 (O22,873 MW) All hours

All peak demand periods

Daytime peak demand periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

23 62 186 2976

66.2 61.0 52.1 24.4

23 61 178 1830

66.2 62.0 54.4 39.7

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and closer to the system peak, the potential PV contribution also increased. During those hours of greatest demand, the potential contribution of PV systems stood at more than 64%. Third, we investigate a specific period in which demand peaked and calculate the PV availability. In Ontario, demand peaked on 12 and 13 August 2002 (when five of the six highest peak demands occurred). Following the method laid out in the investigation into the Alberta case, above, we first calculate the standard clear day radiation values for Guelph, Ont. on 12 and 13 August. They are, respectively, 24.2 and 24.1 MJ/m2. Actual radiation values received at this location on these two days in 2003 were 22.2 and 21.8 MJ/m2, respectively. This yields PV availability values of 92% for 12 August 2002 and 90% for 13 August 2002.

4. Solar availability and electricity market price We also investigate the relationship between solar resource availability and electricity market prices. While basic economic laws of demand and supply suggest that as demand rises, prices will rise as well, the vagaries of markets mean that that is not always the case. 4.1. Alberta We follow the framework laid out in the previous section and begin with the province of Alberta. In Fig. 8, we explore the relationship, in terms of hourly averages across the entire 2-year period, visually. While both electricity price and solar radiation rise during the morning hours of the day, their peaks are markedly different: the electricity price peaks sharply at 18:00, a time at which solar radiation is only one-quarter of its peak value.

Fig. 8. Average hourly solar radiation and system price, Alberta, annual.

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Fig. 9. Average hourly solar radiation and system price, Alberta, December.

Again, we look for seasonal differences, examining December and July as significant individual months. Fig. 9 shows that the pattern in December mirrors—and, in fact, magnifies—the annual pattern. Prices are at their highest at 18:00, with the entire 17:00– 22:00 period experiencing average prices more than 50% higher than any other time in the day. In July, meanwhile (Fig. 10), there seems to be a closer relationship between price and solar radiation levels. Prices reach their highest average value at 16:00—a time at which the solar radiation level is still more than 80% of its peak value. An additional peak price period occurs at 23:00, but the level then only reaches 64% of the late afternoon peak. As with peak demand, therefore, it appears that solar radiation is more closely correlated to summer peak prices than winter peak prices in the Albertan case. Complementing this visual representation, we move on to our statistical analyses. First, we calculate the two-tailed Pearson’s correlation coefficient for the two periods previously identified. For the daylight hours during the April to September (inclusive) period, the coefficient has a value of 0.231, which is significant at 0.01 (nZ5395). Focusing upon

Fig. 10. Average hourly solar radiation and system price, Alberta, July.

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Table 8 Potential PV contribution in Alberta (April to September) Price per MW h

RC$300 RC$200 RC$100 All hours

All peak price periods

Daytime peak price periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

111 201 694 8784

50.0 45.9 39.5 21.4

96 172 545 5395

57.8 53.7 50.3 34.9

July, the association is approximately the same: the coefficient is 0.227, which is significant at 0.01 (nZ983). Second, we look at periods of peak pricing. The average price of electricity in Alberta, during the 2 years under investigation, was C$57/MW h. Following Letendre et al. [4], we consider those hours in which prices were above certain threshold values—in this case, namely, C$300/MW h, C$200/MW h and C$100/MW h. Full results are presented in Tables 8 and 9. From this, we see that not all summer peak price periods occur during daylight hours. Additionally, it is also clear that the potential PV contribution is a bit lower than during periods of peak demand—even when non-daylight hours are filtered out. Nevertheless, with all values above 50%, PV would still appear to have a considerable contribution to make during summer peak price periods in Alberta. Third, we consider a single episode of peak power prices—namely, 25 June 2002. On this day, the top three highest summer hourly prices in Alberta occurred (worth noting, as well, is that these were the second, third and fourth highest hourly prices for the entire 2-year period (in each case, C$999/MW h). A single hour on 10 January 2003 surpassed it (C$999.99/MW h). Thus, in spite of the fact that most of the highest electricity demand values occur in the winter in Alberta—the highest summer hourly demand level ranks 297th overall—peak electricity prices occur almost equally in the winter and summer. Of the top 100 peak price periods, 60 occur in the winter and 40 in the summer). On 25 June, the standard clear day radiation is 29.6 MJ/m2. The amount received in Calgary on 25 June in 2002 was 28.3 MJ/m2, which means that the PV availability value is 96%. Departing from the steps taken in Section 3 of this article, we now calculate, following Perez et al. [20], the ‘solar-weighted price’. This is the average price paid Table 9 Potential PV contribution in Alberta (July) Price per MW h

RC$300 RC$200 RC$100 All hours

All peak price periods

Daytime peak price periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

33 57 181 1488

58.1 53.1 47.3 28.1

30 50 149 983

63.9 60.5 57.5 42.5

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Fig. 11. Average monthly electricity prices, Alberta.

for solar-generated electricity, as if it had been sold in the market at the time it was generated. As Fig. 11 shows, the solar-weighted price is, between April and September, 22–63% higher than the average price of electricity in the province. 4.2. Ontario We now turn to Ontario, and we repeat the steps undertaken for Alberta to investigate the relationship between solar resource availability and electricity market prices. First, in Fig. 12, we explore the relationship in terms of hourly averages across the entire 2-year period. Prices rise during the morning and reach a peak at 13:00, then falling to a low at 16:00. They, however, again rise and reach the peak for the entire day at 20:00, with a value of C$70/MW h, more than twice as high as the lowest average hourly price (C$33/ MW h at 5:00).

Fig. 12. Average hourly solar radiation and system price, Ontario, annual.

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Fig. 13. Average hourly solar radiation and system price, Ontario, January.

Again, however, we look for seasonal differences by exploring individual months. Fig. 13 reveals the pattern in January. Prices rise quickly after 7:00, reaching a sustained high level between 12:00 and 14:00. This mid-day peak, however, is modest compared to the peak reached at 18:00—a value of C$95/MW h. Fig. 14, finally, shows that July peaks occur at three times during the day: 14:00 (with an average price of C$69/MW h), 16:00 (C$71/MW h) and 21:00 (C$61/MW h). Like in the case of Alberta, it is during July that the relationship between price and solar radiation appears to be closest. During the peak price period (16:00), the average solar radiation value is still 74% of its peak value. As with peak demand, therefore, it appears that solar radiation is more closely correlated to summer peak prices than winter peak prices in the Ontario case.

Fig. 14. Average hourly solar radiation and system price, Ontario, July.

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Table 10 Potential PV contribution in Ontario (April to September) Price per MW h

RC$300 RC$200 RC$100 All hours

All peak price periods

Daytime peak price periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

32 65 324 8784

44.4 44.4 37.3 21.9

27 59 273 5277

52.7 49.0 44.3 36.5

Complementing this visual representation, we move on to our statistical analyses. First, we calculate the two-tailed Pearson’s correlation coefficient for the two periods previously identified. For the April to September (inclusive) period, the coefficient has a value of 0.137, which is significant at 0.01 (nZ5277). Focusing upon July and August, the association is even stronger: the coefficient is 0.214, which is significant at 0.01 (nZ1830). Second, we look at periods of peak pricing. The average hourly price of electricity in Ontario, during the 2 years under investigation, was C$56/MW h. Tables 10 and 11 narrow the focus to peak price periods—that is, when market prices were above particular threshold levels. What we found for the Alberta case seems to be repeated here—that is, that not all summer peak price periods occur during daylight hours and that the potential PV contribution is a bit lower (as compared to periods of peak demand). Nevertheless, it is still the case that, in Ontario, PV appears to have a considerable contribution to make during summer peak price periods. Third, we consider 3 September 2002—the day in Ontario during which the first and third highest prices for electricity were reached (C$1028.42/MW h and C$889.13/MW h, respectively). The standard clear radiation for Guelph, Ont. on this day was 20.5 MJ/m2. On this day in 2002, 17.4 MJ/m2 was actually received, which means that the solar reliability value was 85%. Finally, the ‘solar-weighted price’ for the months under consideration are presented in Fig. 15. The premiums for electricity generated by PV panels are not as high as was the case for Alberta—they range from 7 to 27%. September is the month with both the highest premium and the highest price (C$86/MW h, compared to an overall average of C$67/MW h). Table 11 Potential PV contribution in Ontario (July and August) Price per MW h

RC$300 RC$200 RC$100 All hours

All peak price periods

Daytime peak price periods

Number of hours

Potential PV contribution (%)

Number of hours

Potential PV contribution (%)

6 20 136 2976

44.8 45.7 48.6 24.4

5 19 120 1830

53.7 48.1 55.0 39.7

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Fig. 15. Average monthly electricity prices, Ontario.

5. Summary and conclusions Table 12 provides a summary of the findings from the article, explicitly contrasting values for the Alberta and Ontario examples. What is clear is that, for both provinces, solar PV appears to have greater potential during times of high system-wide demand and also (though to a somewhat lesser extent) during times of high electricity prices. As such, it is the case that solar PV should be more valued by utilities and others than system-wide ‘average prices’ (this is even, of course, in the absence of other benefits of solar PV, particularly given that the marginal fuel in both provinces is coal). Table 12 Summary Peak demand

Alberta (April to September) Ontario (April to September) Alberta (July) Ontario (July and August)

Peak price

Pearson’s correlation coefficient

Potential PV contribution (95% of peak demand, daylight hours)

PV availability during single events

Pearson’s correlation coefficient

Potential PV contribution (price RC$200/ MW h, daylight hours)

PV availability during single events

0.397 (nZ5395)

64.4% (nZ265)

Alberta, 87%; Ontario, 91%

0.231 (nZ5395)

53.7% (nZ172)

Alberta, 96%; Ontario, 85%

0.272 (nZ5277)

60.1% (nZ79)

0.137 (nZ5277)

49.0% (nZ59)

0.558 (nZ983) 0.347 (nZ1830)

69.7% (nZ140) 62.0% (nZ61)

0.227 (nZ983) 0.214 (nZ1830)

60.5% (nZ50) 48.1% (nZ19)

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Conclusions that are voiced by Perez et al. in the context of their investigation in the United States would seem to apply equally well to this Canadian case: ‘We have provided evidence that photovoltaics are part of the solution to provide dependable peak power to utilities stressed by growing summertime demand and faced with the risks of rolling blackouts and extreme events’ [9, p. 5]. Moreover, when Letendre and colleagues [3,4] similarly find that PV output is more readily available during peak power price events, they go on to argue that ‘the widespread use of distributed PV could effectively serve as a hedge against price spikes in wholesale markets for power’ [4, p. 5]. They also maintain that net metering rules should compensate solar PV electricity providers more favourably than simply ‘avoided costs’ [3: 4,4: 5]. With net metering legislation in Canada currently in a state of transition [21], similar suggestions could be made here. The purpose of this article has been to determine whether solar electricity is more or less readily available during times of peak market demand and peak market price in two Canadian jurisdictions. In both Alberta and Ontario, it was shown—through a variety of visual and statistical methods—that solar radiation values coincide closely with peak market demand and, though to a somewhat lesser extent, peak market prices during the summertime. While more detailed investigation is needed in order to determine the specific impact of different levels of solar penetration upon provincial electricity markets, this first look at the issue has certainly provided sufficient encouragement for further research. The article has also shown how different techniques can be used—in any location—to investigate the relationship among solar electricity potential, system-wide demand and market prices. With electricity industries being restructured around the world, it will continue to be important for solar energy proponents to participate in discussions regarding ever-changing economic costs and benefits. Techniques used in this article can help them advance the solar case more effectively and thus catalyse the deployment of photovoltaics in markets around the world.

Acknowledgements The author would like to thank Terry Gillespie (University of Guelph) and Rick Smith (University of Calgary) for assistance obtaining solar radiation data.

References [1] Perez R, Seals R, Stewart R. Assessing the load matching capability of photovoltaics for US utilities based upon satellite-derived insolation data. Proceedings of the 23rd IEEE PV specialists conference; 1993. [2] Perez R, Seals R, Herig C. Photovoltaics can add capacity to the utility grid. National Renewable Energy Laboratory; 1996. [3] Letendre S, Perez R, Herig C. An assessment of photovoltaic energy availability during periods of peak power prices. Proceedings of the American solar energy society annual conference; 2001. [4] Letendre S, Perez R, Herig C. Solar and power markets: peak power prices and PV availability for the summer of 2002. Proceedings of the American solar energy society annual conference; 2003. [5] Groppi F. Grid-connected photovoltaic power systems: power value and capacity value of PV systems. International Energy Agency; 2002.

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[6] International Energy Agency Key world energy statistics. Paris: International Energy Agency; 2003. [7] Photovoltaic Power Systems Programme Trends in photovoltaic applications: survey report of selected IEA countries between 1992 and 2002. Paris: International Energy Agency; 2003. [8] Natural Resources Canada The atlas of Canada. Ottawa: Natural Resources Canada; 2004. [9] Perez R, Letendre S, Herig C. PV and grid reliability: availability of PV power during capacity shortfalls. Proceedings of the American solar energy society annual conference; 2001. [10] Statistics Canada Energy statistics handbook, Quarter III, 2003. Ottawa: Statistics Canada; 2004. [11] Environment Canada Electricity and petroleum industries: 1990–2000. Hull: Environment Canada; 2002. [12] Alberta Energy and Utilities Board Alberta electric industry: annual statistics for 2002. Edmonton: Alberta Energy and Utilities Board; 2003. [13] Markvart T, Bogus K. Solar electricity. New York: Wiley; 1994. [14] Messenger R, Ventre J. Photovoltaic systems engineering. Boca Raton: CRC Press; 2004. [15] Perez R. Determination of photovoltaic effective capacity for New Jersey. Clean Power Research; 2003. [16] Taylor MP. A performance, cost/benefit, and policy analysis of photovoltaic technologies in Minnesota.: University of Minnesota; 2002. [17] Taylor M. Statistical relationship between photovoltaic generation and electric utility demand in Minnesota (1996–2002). Minnesota Department of Commerce State Energy Office; 1996. [18] Bailey BH, Doty JR, Perez R, Stewart R, Donegan JE. Evaluation of a demand-side management photovoltaic system bailey. IEEE Trans Energy Convers 1993;8:621–7. [19] Duffie J, Beckman W. Solar engineering of thermal processes. New York: Wiley; 1991. [20] Perez R, Burtis L, Hoff T, Swanson S, Herig C. Quantifying residential PV economics: payback vs. cash flow determination of fair energy value. Proceedings of the American solar energy society annual conference; 2003. [21] Bell J. A survey of Canadian policies to compensate small power producers for electricity fed to the grid: net metering and net billing. Dalhousie University; 2003. [22] NASA. NASA surface meteorology and solar energy: RETScreen data. Langley: National Aeronautics and Space Administration; 2004.