Protected cultivation has developed primarily as a season-extension technology for food crops by applying simple protection from cold temperatures. Structures classified as ‘high tunnels’ are typically equipped with single- or double-layer polyethylene film glazing and often do not have a heating system. When outside temperatures drop below freezing and the days are cloudy and overcast, it is difficult to maintain temperatures for crop growth inside these unheated structures which limits the crops’ production season. Because of relatively high market prices for locally grown, fresh vegetables and fruits in winter, there is increasing interest among high tunnel growers to produce crops throughout the winter season (if possible and economically feasible) by introducing heating to their structures. Estimating heating costs based on energy balance helps growers consider such a critical investment. This article presents estimated heating costs for a small structure in several Ohio locations.
Greenhouse Cost-Estimating Software for Heating and Lighting
Virtual Grower (ver. 3.1) is a software developed by the United States Department of Agriculture, Application Technology Research Unit (USDA ARS) in Wooster, Ohio. This software was developed) primarily to meet the needs of greenhouse growers who are interested in conducting a quick estimate of greenhouse heating and lighting costs. This software allows testing of various designs of a structure and therefore is applicable to high tunnels. The first release of Virtual Grower was in 2006 and the current 3.1 version was developed in 2015. For heating cost estimates, users can select locations, structure design/dimensions, “leakiness” (infiltration) of the structure, heating system type and efficiency, heating setpoint temperatures, and, if needed, supplemental lighting system. The software’s settings for ten Ohio locations with representative weather data provides site-specific simulations. Heat load calculation considers the heat gain and loss affected by the structure design, heating system efficiency, and outdoor climate conditions (temperatures and solar radiation), but soil heat flux is not considered. Greenhouse heat-loss properties are determined based on geometry of the structure (surface area), glazing materials, and leakage/infiltration. Solar radiation is assumed to partially offset the heating load at a fixed percentage, with 33% of solar radiation contributing to a temperature increase inside the structure. A validation conducted by Frantz et al. in 2010 confirmed a reasonable accuracy in estimating heating load using this software. More detailed analyses need to be conducted if better accuracy is desired. However, this software gives an approximate level of heating costs while also allowing users to examine the factors affecting those costs.
Example Analyses: A small standalone single-span structure is selected and considered for Virtual Grower simulations at ten Ohio locations. The reported temperatures and daily light integral of these locations are summarized in Tables 1 and 2.
Month | Akr | Cin | Cle | Col | Day | Fin | Man | Tol | You | Zan |
Jan | 35.5/20.3 | 39.6/23/1 | 38.5/22.3 | 37.1/22.0 | 37.1/21.8 | 35.1/20.4 | 34.1/19.1 | 34.7/20.3 | 34.3/19.3 | 38.4/21/7 |
Feb | 38.6/21/9 | 43.7/25.8 | 38.5/23.7 | 40.8/24.2 | 41.2/24.5 | 38.4/22.7 | 37.0/21.2 | 37.8/22.1 | 37.3/20.7 | 42.0/23.8 |
Mar | 48.4/29.4 | 53.5/33.8 | 47.1/30.7 | 51.1/32.0 | 51.5/32.7 | 48.9/30.6 | 46.9/28.7 | 48.4/29.9 | 46.6/27.8 | 52.0/31.3 |
Apr | 61.8/39.8 | 65.5/43.7 | 60.1/40.8 | 64.1/42.2 | 64.5/42.9 | 62.2/40.6 | 60.4/38.9 | 61.5/40.3 | 60.3/37.9 | 64.6/41.0 |
May | 72.3/50.4 | 74.5/53.7 | 71.1/51.4 | 74.1/52.4 | 74.2/53.8 | 73.3/51.8 | 71.1/49.6 | 73.3/50.9 | 70.9/47.6 | 73.8/50.9 |
Jun | 80.4/59.4 | 82.6/62.1 | 79.8/61.1 | 82.2/61.6 | 82.6/62.7 | 82.1/61.3 | 79.4/58.6 | 82.7/60.5 | 78.8/56.2 | 81.4/59.6 |
Jul | 84.3/63.4 | 86.0/65.9 | 83.7/65.3 | 85.4/65.4 | 85.9/66.1 | 85.4/64.4 | 82.8/62.3 | 86.5/64.2 | 82.7/60.3 | 84.8/63.6 |
Aug | 82.7/61.9 | 85.2/64.6 | 82.0/63.9 | 84.1/63.9 | 84.6/64.3 | 83.5/62.3 | 81.2/60.8 | 84.1/62.8 | 81.1/58.8 | 83.7/61.7 |
Sep | 75.9/54.9 | 78.9/57.3 | 75.6/57.1 | 77.8/56.5 | 78.6/56.8 | 77.7/55.2 | 75.0/53.7 | 77.7/55.1 | 74.3/52.1 | 77.5/54.4 |
Oct | 63.4/44.0 | 66.7/45.7 | 63.7/46/5 | 65.5/44.8 | 66.2/45.9 | 65.2/44.5 | 62.8/43.1 | 65.0/44.3 | 62.1/42.2 | 65.6/43.1 |
Nov | 50.7/34.2 | 53.8/35.1 | 51.3/36.7 | 52.3/35.0 | 52.7/35.4 | 51.4/34.4 | 49.6/33.4 | 51.1/34.5 | 49.6/33/4 | 53.2/33.7 |
Dec | 39.9/26.1 | 43.3/27.9 | 40.4/28.2 | 41.5/27.4 | 41.5/27.1 | 39.8/26.2 | 38.6/25.0 | 39.4/26.1 | 38.7/25.5 | 42.5/26.8 |
Avg | 51.7 | 54.7 | 52.4 | 53.5 | 53.9 | 52.4 | 50.6 | 52.5 | 49.9 | 53.0 |
Key: Akr (Akron), Cin (Cincinnati), Cle (Cleveland), Col (Columbus), Day (Dayton), Fin (Findlay), Man (Mansfield), Tol (Toledo), You (Youngstown), Zan (Zanesville). https://www.weather.gov/cle/local_climate. |
Month | Akr | Cin | Cle | Col | Day | Fin | Man | Tol | You | Zan |
Jan | 12.5 | 14.2 | 10.1 | 13.2 | 13.4 | 11.8 | 12.3 | 12.0 | 12.1 | 13.2 |
Feb | 17.4 | 20.2 | 16.6 | 18.2 | 19.3 | 17.7 | 17.4 | 18.2 | 17.8 | 18.3 |
Mar | 26.5 | 27.4 | 24.7 | 26.2 | 26.5 | 26.2 | 26.0 | 25.9 | 25.5 | 26.3 |
Apr | 34.9 | 35.4 | 35.0 | 34.9 | 35.1 | 34.9 | 35.3 | 34.7 | 34.7 | 35.0 |
May | 40.1 | 41.7 | 40.9 | 40.6 | 41.1 | 40.3 | 40.3 | 40.4 | 39.8 | 40.6 |
Jun | 43.1 | 44.8 | 44.6 | 44.2 | 44.5 | 44.2 | 43.7 | 44.9 | 43.1 | 44.4 |
Jul | 43.2 | 43.4 | 44.4 | 42.9 | 43.4 | 44.9 | 43.4 | 44.7 | 42.7 | 43.2 |
Aug | 38.0 | 40.1 | 38.5 | 39.0 | 40.0 | 38.6 | 38.1 | 38.1 | 37.8 | 39.3 |
Sep | 31.2 | 33.3 | 31.1 | 32.7 | 33.1 | 31.9 | 31.3 | 32.3 | 30.6 | 32.7 |
Oct | 19.8 | 23.3 | 18.7 | 22.5 | 22.9 | 21.5 | 21.0 | 20.8 | 20.0 | 22.2 |
Nov | 13.0 | 15.8 | 11.7 | 14.6 | 15.2 | 13.3 | 13.5 | 12.9 | 13.2 | 14.6 |
Dec | 11.1 | 12.1 | 8.1 | 11.4 | 11.5 | 10.2 | 10.9 | 10.5 | 11.0 | 11.6 |
Avg | 27.6 | 29.4 | 27.1 | 28.4 | 28.9 | 28.0 | 27.8 | 28.0 | 27.4 | 28.5 |
Key: Akr (Akron), Cin (Cincinnati), Cle (Cleveland), Col (Columbus), Day (Dayton), Fin (Findlay), Man (Mansfield), Tol (Toledo), You (Youngstown), Zan (Zanesville). |
The structure’s size is a typical small high tunnel with gable ends, as shown in Fig. 1. This structure was assumed to be covered with double layer polyethylene films. No other heat conservation technologies were considered in this analysis.
The heating system used was a high-efficiency unit heater using separated combustion with overhead air distribution tubes. This selection of heating system resulted in a moderate heating efficiency of 61%. The heating setpoint was selected as 54°F (12°C, a minimum temperature for tomato) or 45°F (7°C for a minimum temperature for leafy greens and berries). The fuel type was natural gas at $0.61 per therm, which is the average price for Ohio industrial natural gas over the past five years (US EIA 2020).
Tables 3, 4, and Fig. 2 show the monthly heating costs and the annual total of a sample structure (Fig. 1) located in the ten Ohio locations.
Month | Akr | Cin | Cle | Col | Day | Fin | Man | Tol | You | Zan |
Jan | $0.22 | $0.15 | $0.20 | $0.18 | $0.20 | $0.19 | $0.24 | $0.20 | $0.20 | $0.11 |
Feb | $0.17 | $0.13 | $0.17 | $0.15 | $0.16 | $0.13 | $0.18 | $0.17 | $0.17 | $0.11 |
Mar | $0.11 | $0.08 | $0.11 | $0.08 | $0.08 | $0.07 | $0.11 | $0.09 | $0.09 | $0.08 |
Apr | $0.04 | $0.02 | $0.04 | $0.03 | $0.03 | $0.03 | $0.05 | $0.04 | $0.05 | $0.03 |
May | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.02 | $0.01 |
Jun | - | - | - | - | - | - | - | - | $0.01 | - |
Jul | - | - | - | - | - | - | - | - | - | - |
Aug | - | - | - | - | - | - | - | - | - | - |
Sep | $0.01 | $0.01 | - | - | $0.01 | - | $0.01 | $0.01 | $0.01 | - |
Oct | $0.04 | $0.03 | $0.03 | $0.03 | $0.04 | $0.04 | $0.04 | $0.05 | $0.05 | $0.04 |
Nov | $0.08 | $0.06 | $0.08 | $0.07 | $0.09 | $0.07 | $0.09 | $0.10 | $0.08 | $0.06 |
Dec | $0.15 | $0.13 | $0.16 | $0.15 | $0.17 | $0.15 | $0.16 | $0.21 | $0.19 | $0.14 |
Total | $0.82 | $0.62 | $0.81 | $0.71 | $0.78 | $0.70 | $0.87 | $0.89 | $0.88 | $0.59 |
Key: Akr (Akron), Cin (Cincinnati), Cle (Cleveland), Col (Columbus), Day (Dayton), Fin (Findlay), Man (Mansfield), Tol (Toledo), You (Youngstown), Zan (Zanesville). |
Month | Akr | Cin | Cle | Col | Day | Fin | Man | Tol | You | Zan |
Jan | $0.15 | $0.09 | $0.13 | $0.12 | $0.13 | $0.12 | $0.16 | $0.14 | $0.13 | $0.06 |
Feb | $0.11 | $0.08 | $0.11 | $0.10 | $0.10 | $0.07 | $0.12 | $0.11 | $0.12 | $0.06 |
Mar | $0.06 | $0.04 | $0.06 | $0.05 | $0.04 | $0.03 | $0.06 | $0.05 | $0.05 | $0.05 |
Apr | $0.02 | - | $0.02 | $0.01 | $0.01 | $0.01 | $0.01 | $0.02 | $0.02 | $0.01 |
May | - | - | - | - | - | - | - | - | - | - |
Jun | - | - | - | - | - | - | - | - | - | - |
Jul | - | - | - | - | - | - | - | - | - | - |
Aug | - | - | - | - | - | - | - | - | - | - |
Sep | - | - | - | - | - | - | - | - | - | - |
Oct | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.01 | $0.02 | $0.02 | $0.01 |
Nov | $0.03 | $0.03 | $0.04 | $0.03 | $0.04 | $0.03 | $0.04 | $0.05 | $0.03 | $0.02 |
Dec | $0.09 | $0.07 | $0.09 | $0.09 | $0.10 | $0.09 | $0.10 | $0.14 | $0.12 | $0.08 |
Total | $0.47 | $0.32 | $0.46 | $0.40 | $0.45 | $0.38 | $0.52 | $0.53 | $0.50 | $0.30 |
Key: Akr (Akron), Cin (Cincinnati), Cle (Cleveland), Col (Columbus), Day (Dayton), Fin (Findlay), Man (Mansfield), Tol (Toledo), You (Youngstown), Zan (Zanesville). |
In all locations, when the target minimum temperature (heating setpoint) was 54°F, the annual total heating cost ranged from $0.59 to $0.89 per ft2 ($1,277–$1,919 for the 2,160 ft2 structure) with a trend showing relatively lower costs in southern locations. Table data includes monthly costs and so can be used to compute the heating costs of specific months of crop production. As expected, the highest heating cost appeared in January when the lowest average temperatures appear in most locations. In some locations (such as Zanesville), the lowest temperature month reported by NOAA (Table 1) does not match with the highest heating cost month estimated by Virtual Grower. This is likely because the Virtual Grower software takes a stochastic approach rather than simple average of multiple years. Simple averaging over years tends to mask the extreme weather conditions, leading to underestimating actual costs. When the heating setpoint is reduced to 45°F, the annual cost can be reduced to $0.30–$0.53 per ft2 (Table 3, Fig. 2) ($642–$1,145 for the 2,160 ft2 structure).
A brief description of the factors affecting heating costs in the structure is presented below to provide a better understanding of why these variables are important in the Virtual Grower simulation. Virtual Grower can test the impact of these factors on the heating costs.
Covering Materials
A structure (greenhouse or high tunnel) sitting outdoors loses heat in different ways (convection, conduction, and radiation) when the structure’s internal temperature is higher than the temperature outside. Overall heat transfer coefficients (AKA U-values) are reported for various structures, and generic values are used specific to the glazing type selected in the simulation. U-values express the heat loss per unit surface area, per time, per one-degree temperature gradient (BTU ft-2 h-1 F-1). Using glazing materials with a smaller U-value is one way to reduce heating costs; however, in addition to U-value, light transmission, material costs, and the life of the glazing material (replacement cycle) need to be considered when selecting glazing. In our example simulation we used a double-layer polyethylene film glazing. Replacing this glazing with a single-layer film increased the pre-determined U-value from 0.7 to 1.15 BTU ft-2 h-1 F-1. This resulted in a more than 60% greater heat loss through the glazing) which increased the heating cost significantly.
Geometry (Surface to Floor Ratio)
A structure having a relatively large surface area to floor area tends to lose more heat. An unheated structure should be as short in height as possible to retain heat. Having a secondary layer or low tunnel inside a structure is a common practice in high tunnels. This minimizes heat loss from the crop microclimate. In contrast, taller structures are preferred for the uniformity of temperature and high ventilation capacity (chimney effect) in summer. While height is difficult to change for existing structures, Virtual Grower theoretical simulations can show growers the influence of height on heating costs.
Containment (Infiltration)
Heat loss via infiltration can be significant and needs to be accounted for when estimating heating costs. The loss is proportional to the infiltration rate and the difference in temperature between the inside and outside of the structure. Structures should have as few holes and gaps as possible to minimize infiltration.
Thermal Screen
Not many high tunnels have additional thermal screening. The installation and deployment of a thermal screen at night is worth considering to minimize heat loss.
Fuel Price
The optimum type of fuel and its price are specific to locations and growers’ situations. While natural gas is typically preferred, propane or heating oil may make better sense in some situations.
Supplemental Lighting
Some growers may want to add supplemental lighting because the Ohio winter does not provide an optimum level of light for their crop. The total electrical use (watt hours) of lights in the structure can be considered as an offset for the heating requirement.
For locations that the Virtual Grower software does not currently include, heating cost estimates can be done if the location’s local weather data is available. The Ohio State University College of Food, Agricultural, and Environmental Sciences has a total of ten weather stations (https://weather.cfaes.osu.edu/) for areas not included on Virtual Grower. These weather stations monitor temperature and radiation data for Ashtabula, Caldwell, Custar, Fremont, Jackson, Piketon, South Charleston, Wooster, and Willard. Contact the author, Chieri Kubota, at kubota.10@osu.edu if you have questions or site-specific analysis needs.
References
Faust, James E., and Joanne Logan. 2018. “Daily Light Integral: A Research Review and High-Resolution Maps of the United States.” HortScience Volume 53, Issue 9.
doi.org/10.21273/HORTSCI13144-18
Frantz, Jonathan M., Bryon Hand, Lee Buckingham, and Somik Ghose. 2010. “Virtual Grower: Software to Calculate Heating Costs of Greenhouse Production in the United States.” HortTechnology Volume 20, Issue 4: 778–785.
doi.org/10.21273/HORTTECH.20.4.778
U.S. Energy Information Administration (US EIA). 2020. Natural Gas Prices. Independent Statistics & Analysis.
eia.gov/dnav/ng/ng_pri_sum_dcu_SOH_a.htm