Steven J. Brunner Brendle Group 212 W. Mulberry Street Fort Collins, CO

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1 Model to Calculate PV Array Altitude and Azimuth Angles to Maximize Energy and Demand Revenues from Measured Hourly Solar Radiation and Building Use Data Steven J. Brunner Brendle Group 212 W. Mulberry Street Fort Collins, CO ABSTRACT Traditionally, economic analyses of commercial photovoltaic (PV) systems have focused on energy use reduction as opposed to electrical demand reduction. While several studies have calculated the impact of PV systems on reducing monthly peak demand, they have relied on hourly energy simulation and/or TMY data or have a limited study period, which limit their usefulness and do not compare simulation results to actual building use data. In response, an hourly simulation model was developed to utilize hourly measured weather data and hourly electrical demand for several buildings in Fort Collins, Colorado. Data for four years (7 ) was analyzed to estimate expected economic savings resulting from the installation of a PV array. The model provides flexibility to test different utility rates and calculate how varying the PV array slope and azimuth angles impacts PV energy production, demand reduction, and revenue. Outputs include monthly and annual energy, greenhouse gas reductions, and peak demand reductions. When applied to two specific Fort Collins office buildings where the rate includes energy, peak demand, and coincident demand rates, the model indicates that to maximize economic return, one should install the PV array at an altitude angle roughly equivalent to the latitude (º) and an azimuth angle greater than 45 degrees to the west of due south, resulting in a greater than 15% revenue improvement compared to ideal array installations. INTRODUCTION Fixed-mount PV array orientation is described by two angles: 1. Slope angle: the angle between the array surface and horizontal (ground) and 2. Azimuth angle: the angle between the normal to the array surface and due south (due south is zero; east is negative; west id positive). Traditionally, PV arrays have been oriented to maximize annual energy production. To accomplish this, designers specify a slope angle that is equal to the location s latitude and an azimuth angle of zero, or slightly positive. On a typical clear day, the array electrical output gradually increases throughout the morning to a maximum at around solar noon, before gradually decreasing throughout the afternoon. The electrical load of a commercial building may not match this PV production curve. For many months in a year, a typical office building in a moderate climate will peak in the mid-afternoon as a result of its HVAC (heating, ventilation, and air conditioning) system working hard to compensate for higher outside air temperatures, internal thermal loads, and solar radiation (among other factors). By the time the building reaches its peak daily electrical load, a PV array may be producing less than half of its maximum output. This has economic consequences in situations where utility electrical rates have low energy prices, but place a price premium on peak demand. Fort Collins Utilities ( FCU ), a municipal utility located in northern Colorado, purchases and distributes electricity from Platte River Power Authority ( PRPA ), a wholesale electricity provider that operates generation capacity for the cities of Fort Collins, Longmont, Loveland and Estes Park. Larger commercial customers (> kw demand) in

2 Electrical Load (kw) FCU s territory are subject to a rate that has three price components (1): 1. Electric Energy: Total amount of electricity used in a month (measured in kwh), plus a fixed charge for metering and billing; 2. Facility Demand: The facility's highest one-hour demand (kw) during the billing period; and 3. Coincident Peak: Hourly facility demand (kw) during the hour each month during which the PRPA system peaks. This occurs 12 times per year, typically in the late afternoon during the summer months and the early evening in the winter months. Table 1 summarizes the monthly charges for each of the rate components. TABLE 1: COMPONENTS IN ELECTRIC RATE Component Unit Price Energy kwh $.2629 Facility Demand kw-mo $5.11 Coincident Peak kw-mo $13.57 (Note: rates in Table 1 were in place during 11; the rates changed as of January 1, 12) Because of the low energy price and relatively high coincident peak price, a typical office building s annual electricity bill may break down as follows: % for Energy, % for Facility Demand, and % for Coincident Peak (2). For a commercial entity that is contemplating installing a PV array on a building in Fort Collins, it must consider the building load pattern and the electrical rate when deciding the array orientation. By orienting the array to maximize energy production, it will likely reduce its potential to offset the economic impacts of Facility Demand and Coincident Peak, which occur in the afternoon, well after the array has maximized its electrical output. To assist building owners in determining the impact that various array orientations have on the economics of a potential PV installation, a computer model was developed that takes into account the building s electrical load pattern, the utility rate, and the performance of a PV array at different slope and azimuth angles. The model is an hour-by-hour simulation that utilizes historical hourly weather data and building meter data. the electrical use pattern of a specific building. Therefore, the data presented here is the result of running the model on two actual buildings located in Fort Collins, CO. While the loads are actual meter data, the buildings are referred to here simply as Building A and Building B to keep their use confidential. Building A is a two-story commercial building that is relatively square in shape with windows that are evenly distributed among all four orientations. Its heating, ventilation, and air conditioning ( HVAC ) system is made up of numerous small rooftop units that are controlled through a central building automation system ( BAS ) that relaxes temperature setpoints at 5 PM on weekdays and all day on weekends. Fig. 1 represents the hourly metered electrical load for weekdays during July 7. The load pattern is consistent, with the building usually peaking in the late afternoon Hour of Day Fig. 1 - Hourly Building Electrical Load for Building A July 7 Weekdays Building B is a three-story commercial building that is rectangular in shape, with the long axis running northsouth. This large amount of west-facing glazing has a significant impact on the afternoon HVAC load and thus, the building electrical load. It, too, has a BAS that effectively shuts down the HVAC system during unoccupied hours. Fig. 2 represents the hourly metered electrical load for weekdays during July 7. The load pattern is less consistent than that for Building A and it shows a distinct increase in the very late afternoon just prior to the BAS shutting down the HVAC system. Also of note, is a single day on which the building peaked considerably higher than any other day. This was a very hot day and coincided with PRPA a Coincident Peak day for the month. While a model that utilizes hourly outputs from a building simulation program such as DOE-2, equest, EnergyPro, etc. would be educational, it would not accurately depict

3 kwh Electrical Load (kw) Fig. 2 - Hourly Building Electrical Load for Building B July 7 Weekdays METHODOLOGY Hour of Day In order to calculate the electrical output of a solar panel on a tilted surface, a source of local hourly insolation (solar radiation) was needed. This was obtained via the Agricultural Meteorological Network (COAgMet), a network of automatic weather stations distributed across the state of Colorado and design to assist agricultural producers. Data collected by the network is available on the Internet at Among the weatherrelated data is hourly insolation on a horizontal surface. Expressed in kj/m 2 -min, insolation is measured by a LiCor X pyranometer every ten seconds and then averaged over the hour (3). The data for this study came from the FTC1 weather station, which is located at the U.S. Agricultural Engineering facility at Colorado State University. Calculating total radiation on a tilted surface requires separating the radiation on a horizontal surface into its diffuse and beam components. The methodology for doing this is explained well in the literature and is described here only generally. The methodology used herein follows that described by Duffie and Beckman (4). In general, the approach is to calculate an hourly clearness index, k T, by dividing the COAgMet horizontal insolation by the calculated extraterrestrial horizontal radiation for that corresponding hour. With this data, the beam and diffuse components of the horizontal radiation can be separated using the Erbs correlation (5). Assuming an anisotropic sky and a generalized ground reflectance of.2, the total irradiation on a tilted surface can be calculated using the HKDR model (4). Thus, after adjusting for solar panel absorptance, reflectance, and efficiency, the above method can be used to estimate the hourly output of a given PV system at fixed tilt and azimuth angles. To determine the ideal solar system orientation, the model used the above method to calculate the output of a gridintertied, nominal kw (AC) PV array at various slope and azimuth angles. Slope angles were adjusted in five degree increments from to 7 degrees from horizontal. For each slope angle increment, the azimuth angle was adjusted in ten degree increments from degrees east of due south to 7 degrees west of due south. This was done for each hour from 7 through. Because the model used actual hourly horizontal insolation data from COAgMet, its hourly electrical output is a good reflection of how a real PV array would perform. Fig. 3 depicts the annual energy output for various combinations of slope angles and azimuth angles using 7 insolation data. The results are similar to what one would expect at this location: the annual energy is maximized at a slope angle of degrees and an azimuth angle slightly west of due south. 7 Annual Energy Output (kwh) 15,-16, 16,-17, 17,-18, 18,-19, 19,-,, 19, 18, 17, 16, 15, 7 Azimuth Angle Fig. 3 PV Array Annual Energy Production - 7 Traditionally, PV arrays have been oriented to maximize the annual energy production. However, with a commercial electrical rate that puts a price premium on demand compared to energy, this may not be the most economical orientation. To calculate the economic impact of the various array orientations, the model utilizes actual hourly metered electrical data that was provided by the customer and calculates how much a PV array would reduce the Energy, Facility Demand, and Coincident Peak charges at various orientations. At each combination of slope and azimuth angle, the model separately calculated the economic impact that the PV array had on the annual utility bill as a result of energy production, Facility Demand Reduction and

4 Coincident Peak reduction. Then, it calculated the total annual maximum economic impact at each combination of slope and azimuth angles. The economic impact of energy production was simply the product of the array s annual energy production (in kwh) and the Energy component of the electrical rate. The economic impact of the Facility Demand was the product of the total monthly reduction of the building s demand and the Facility Demand component of the electrical rate. This was calculated for each month, and the monthly values were accumulated to arrive at an annual figure. The monthly value was not simply the array s reduction of the building s highest monthly demand, because reducing the peak on one day may result in a new peak on another day. Therefore, the Facility Demand reduction had to take into account the array s contribution to the building s demand for the entire month. The economic impact of Coincident peak demand reduction was the product of the array s power output at the hour of PRPA s system peak and the Coincident Peak component of the electrical rate. The hour of the system peak is provided by the utility at the end of every month. RESULTS Among the outputs of the model are graphs that illustrate the impacts the array orientation has on array performance and the system economics. In the interest of space, this section includes examples of some of the graphs. Years 7 and 9 were chosen for display purposes because they show how different rate components can change between years. Building A and Building B are addressed separately. However, because the arrays are identical between the two buildings, the Energy cost reduction is the same (see Fig. 4 for 7 data). Not surprisingly the slope and azimuth angles that maximize Energy cost reduction are the same as those for energy production. $525 $375-$ $-$425 $425-$4 $4-$475 $475-$ $-$525 $ $475 $4 $425 $ $37 Fig. 4 Energy Cost Reduction for 7 for Buildings A and B Building A 7 Azimuth Angle Annual Facility Demand reduction results indicate the ideal economic PV array orientation for Building A should have a slope angle of about degrees and an azimuth angle of about degrees. Fig. 5 shows the Facility Demand cost reduction for 7 at various combinations of slope angle and azimuth angle. Fig. 6 shows the Facility Demand cost reduction for 9. There Annual is little difference Facility Demand between Cost the two Reduction years. - 7 $225 $5 $185 $165 $145 $12 $125-$145 $145-$165 $165-$185 $185-$5 $5-$225 7 Azimuth Angle Fig. 5 Building A Facility Demand Cost Reduction - 7

5 Cost Reduction Annual Facility Demand Cost Reduction - 9 $125-$145 $145-$165 $165-$185 $185-$5 $5-$225 $125-$225 $225-$325 $325-$425 $225 $5 $185 $165 $145 $ Azimuth Angle $425 $325 $225 $ Azimuth Angle Fig. 6 Building A Facility Demand Cost Reduction 9 Annual Coincident Peak reduction results indicate the ideal economic PV array orientation for Building A should have a slope angle of about degrees and an azimuth angle of about 7 degrees. Fig. 7 shows the Coincident Peak cost reduction for 7 at various combinations of slope angle and azimuth angle. Fig. 8 shows the Coincident Peak cost reduction for 9. Based on the electrical load, there was a greater opportunity Annual to Coincident save in 7. Peak Cost Reduction - 7 $625 $525 $425 $325 $22 $225-$325 $325-$425 $425-$525 $525-$625 7 Azimuth Angle Fig. 7 Building A Coincident Peak Cost Reduction - 7 Fig. 8 Building A Coincident Peak Cost Reduction - 9 The graphs above illustrate how the various rate components make up the potential savings from the PV array. The total annual savings analysis shows the overall impact of the different orientations. Again, this data is not the sum of the maximum savings from each component. Rather, it is the combination of the components for each hour. Fig. 9 shows the overall potential cost reduction for 7. It indicates that the maximum cost savings is achieved by an array with a slope angle of degrees and an azimuth angle of degrees. Fig. presents that same data for 9. It indicates that the maximum cost savings is achieved at slope angle of 35 degrees and an azimuth angle of degrees. 7 Cost Reduction $8 - $9 $9 - $1, $1, - $1, $1, - $1, $1, - $1, $1, $1, $1, $1, $9 $ Azimuth Angle Fig. 9 Building A Overall Cost Reduction - 7

6 Cost Reduction Cost Reduction 9 Cost Reduction $7 - $8 $8 - $9 $9 - $1, $1, - $1, Annual Coincident Peak Cost Reduction - 7 $-$ $-$ $-$ $-$ $-$6 $1, $9 $ $ $8 $ $7 $ $ - - Fig. Building A Overall Cost Reduction Azimuth Angle Azimuth Angle Building B Annual Facility Demand reduction results indicate the ideal economic PV array orientation for Building B should have a slope angle of about degrees and an azimuth angle of about degrees. Fig. 11 shows the Facility Demand cost reduction for 7. Only 7 data is shown for Building B. Annual Facility Demand Cost Reduction - 7 $-$75 $75-$9 $9-$5 $5-$1 $1-$135 Fig. 12 Building B Coincident Peak Cost Reduction - 7 Figure 13 illustrates the overall potential cost reduction for 7. It indicates that the maximum cost savings is achieved at a slope angle of degrees and an azimuth angle of degrees. Annual Cost Reduction - 7 $1, - $1, $1, - $1, $1, - $1,1 $1,1 - $1, $1, - $1,2 $1,2 $1, $135 $1,1 $1 $1, $5 $1, $9 $1, $75 $ 7 7 Azimuth Angle Azimuth Angle Fig. 13 Building B Overall Cost Reduction - 7 Fig. 11 Building B Facility Demand Cost Reduction 7 Annual Coincident Peak reduction results indicate the ideal economic PV array orientation for Building B should have a slope angle of about degrees and an azimuth angle of about 7 degrees. Fig. 12 shows the Coincident Peak cost reduction for 7. ANALYSIS AND CONCLUSIONS A model was developed to gauge the impacts that various orientations have on the economics of PV installations at two office buildings in Fort Collins Utilities territory. Using historical insolation and electrical meter data, it was determined that for the period 7 through, the

7 slope and azimuth angles that maximize economic return for Building A are and degrees, respectively. The same model analysis for Building B reveals that the angles that maximize economic return would be and degrees, respectively. Azimuth angles for both buildings vary considerably from the azimuth angle at which many PV arrays are installed in this part of Colorado (zero degree azimuth angle). Compared to this typical orientation, the idealized orientations for Buildings A and B would increase energy cost savings by an average of 15.5% and 17.4%, respectively. Many fixed-mount PV arrays that are being installed on existing flat roofs are using lower slope angles than the traditional degrees. This is so that arrays have a lower profile and, thus, a lower wind load. This reduces the ballast required to anchor these systems. These angles range from to degrees. The model described herein was run at slope angles of, 15, and degrees at various azimuth angles. The economic savings for these orientations were compared to the traditional orientation described above. Table 2 summarizes the economic savings of these lower slope angles for Building A. Table 3 summarizes the savings for Building B. TABLE 2 ECONOMIC SAVINGS FOR LOW SLOPE ANGLES FOR BUILDING A Azimuth Angle deg. 15 deg. deg. deg. -1.9% -.1% 1.% deg. -.4% 2.% 3.8% deg..9% 3.8% 6.1% deg. 1.9% 5.2% 8.% deg. 2.6% 6.2% 9.3% deg. 2.9% 6.8% 9.9% deg. 3.% 6.8% 9.9% 7 deg. 2.7% 6.3% 9.2% TABLE 3 ECONOMIC SAVINGS FOR LOW SLOPE ANGLES FOR BUILDING B Azimuth Angle The results described herein are limited to a single electrical rate structure in Fort Collins, CO. However, the model is flexible and can simulate energy, demand, and economic results for many different types of commercial electrical rates. ACKNOWLEDGEMENTS deg. 15 deg. deg. deg. -.6%.9% 1.9% deg..8% 3.% 4.6% deg. 2.% 4.8% 6.9% deg. 3.% 6.2% 8.8% deg. 3.7% 7.2%.2% deg. 4.1% 7.8% 11.% deg. 4.1% 7.9% 11.1% 7 deg. 3.9% 7.6%.7% The author would like to thank to the following: City of Fort Collins Utilities, which provided assistance with electrical rates and project management support of Renewable and Distributed Systems Integration project; U.S. Department of Energy, who provided partial funding of the Renewable and Distributed Systems Integration, which supported a portion of this work; Laura Ruff, formerly of Brendle Group, who worked on the model and programmed many of the solar calculations; and Marty Pool, Brendle Group, who worked on the model and programmed many of the economic calculations. REFERENCES (1) 11 Electric Rates, City of Fort Collins Ord. 142 and Ord. 166, (2) Personal communication with Julie Sieving, senior engineer, Brendle Group, Fort Collins, CO, June 11 (3) Personal communication with Wendy Ryan, Research Associate II at the Colorado Climate Center, March 12 (4) Duffie, John A. and William A. Beckman, Solar Engineering of Thermal Processes (Third Edition), John Wiley and Sons, Hoboken, NJ, (6) (5) Erbs, D. G., S. A. Klein, and J. A. Duffie, Solar Energy, 28, 293 (1982). Estimation of the Diffuse Radiation fraction for Hourly, Daily, and Monthly- Average Global Radiation.