Louis D. Albright

Controlling greenhouse light to a consistent daily integral

Lettuce growth data are presented that show the importance of the daily light integral for predictable vegetative growth. Dry mass accumulation is shown to be proportional to the light integral, and a consistent daily light integral is proposed to be central to consistent production. Supplemental lighting control rules are defined and described and a computer implementation is used in conjunction with ten years of hourly weather data to test (by simulation) adequacy of the rules to control supplemental lights and movable shades in greenhouses to achieve a consistent daily integral of Photosynthetically Active Radiation (PAR), mol-m –2 -day –1 , on days of either insufficient or excess solar irradiation, which are most days. The rules require neither historical data bases of weather characteristics nor daily weather forecasts. Control decisions are suggested to be made hourly, based on the current day’s accumulating solar PAR integral inside the greenhouse. The model is sensitive to time-of-day electricity rates, changing seasons, weather, greenhouse and component characteristics, and greenhouse location (latitude and longitude). The rules contain parameters with values suggested for northeastern United States solar conditions but which may be adjusted for local solar climates that are significantly different.

Optimal temperature setpoints for greenhouse lettuce

A two state-variable greenhouse lettuce model is formulated and used to optimize dynamically the daytime temperature setpoint of the greenhouse. Pontryagins Maximum Principle is used to solve the problem numerically. The resulting control strategy recommends that initially leaf area expansion should be promoted, while later on, when the canopy fully covers the soil, the emphasis should be shifted to dry matter accumulation. This is reflected in a decreasing temperature setpoint during the growing period. Day-to-day fluctuations in response to the changing weather are superimposed on the general trend. While this result is consistent with the physiology of the modelled crop, the projected economic gain, compared with the results for the best constant temperature setpoint, was found to be small.

A Time Dependent Analysis of Greenhouse Thermal Environment

ABSTRACT RISING fuel prices are having a significant effect on further development of the greenhouse industry. This has directed research efforts along two paths: (a) improving the greenhouse structure to reduce energy losses, while maintaining a desirable growth environ-ment; and (b) developing alternate energy sources such as solar, wind, waste heat from power plants, and geo-thermal energy to meet greenhouse heating demand. Although a number of greenhouse thermal environ-ment models (analytical and numerical) are available at present, each model is restrictive in its applicability. A more general time-dependent analysis of greenhouse thermal environment is desirable to detect and control thermal stress on plants, to design so as to reduce heat-ing and cooling requirements, and to consider intermit-tent sources of heating and cooling such as solar and wind.

Analytical determination of the effect on greenhouse heating requirements of using night curtains.

ABSTRACT A theoretical procedure, using energy balance princi-ples, is developed to estimate the energy conserving potential of night curtains used in greenhouses. The pro-cedure is tested by comparing the results of the analysis with published experimental data.

In situ thermal calibration of unventilated greenhouses

Abstract A method for in-situ thermal calibration of unventilated greenhouses is proposed. The model whose coefficients are to be evaluated is: H+aS o −C( dT m dt )−U(T i −T o )−R=0 where the five terms represent: (1) the heat from the heater, (2) the heat generated by solar radiation (So), (3) the rate of heat storage in the system, (with dTm/dt representing the rate of change of the thermal mass temperature), (4) the loss by convection and infiltration due to the temperature difference (Ti−To) between the inside and the outside, and (5) radiation through the cover. The parameters to be evaluated are U, the overall heat transfer coefficient; a, the heating efficiency of the solar radiation; C, the heat capacity of the greenhouse; and R, a correction factor for radiative heat transfer. Latent heat transfer is not considered explicitly, but does affect the value of U. Experimental results for greenhouses at Technion and at Cornell University indicate that predicted values of the coefficients, in particular U and a, are consistent enough to be useful. The effect of heat capacity on the predictability of inside temperatures and system time constants should not be ignored. It presents, however, certain difficulties in application. A comparison between a dry and a wet greenhouse (both devoid of plants) showed that the heat transfer coefficient U for the wet greenhouse was higher by 28% than for the dry greenhouse. This is attributed to the latent heat contribution through the evaporation-condensation cycle and through infiltration.

Application of pseudo-derivative-feedback algorithm in greenhouse air temperature control.

Pseudo-Derivative-Feedback (PDF) control is compared to PI control through simulation using an approximated dynamic system thermal model of the greenhouse. The effects of time delays on control system performance for both PDF and PI control are demonstrated. Results showed PDF control to have a better load handling capability than PI control. PDF control was exceptionally better than PI for systems without time delay and significantly better for systems with time delay. The algorithm was then tested to control a greenhouse section and showed satisfactory results.

Steady-Periodic Analysis of Glasshouse Thermal Environment

ABSTRACT A mathematical model is developed to predict steady-periodic thermal behavior of glasshouses. The model is shown to predict temperatures of the internal air, plant canopy, and floor surface with reasonable accur-acy. The utility of the model is demonstrated through simulations predicting the effects of several potential glasshouse design modifications.

Optimal design of plant lighting system by genetic algorithms

A genetic algorithm technique is developed for the optimal design of a supplemental lighting system for greenhouse crop production. The approach uses the evolutionary parallel search capabilities of genetic algorithms to design the pattern layout of the lamps (luminaires), their mounting heights and their wattages. The total number and the exact positions of luminaires are not predefined (even though possible positions lay on a fixed grid layout), thus the genetic algorithm system has a large degree of freedom in the designing process. The possibilities of mounting heights and luminaire wattages are limited to four different values for each luminaire in this study. A fitness function for the genetic algorithm was developed, taking into account light uniformity, light intensity capability, shading effects of the design, as well as operational and investment costs. The systems designed by the genetic algorithm show improved values of light uniformity and substantial savings without any effect on the light capacity capabilities of the system. Innovative automatically designed systems compare favorably with typical and expert-designed lighting systems.

An application of the K-ε turbulence model to predict how a rectangular obstacle in a slot-ventilated enclosure affects air flow.

ABSTRACT A modification of the TEACH-T program (based on the k-£ model of turbulence transport) was applied to the problem of predicting air mixing patterns and velocities in a rectangular, slot-ventilated enclosure having a rectangular obstacle to flow. Comparisons of predictions to data showed air distribution patterns were predicted well, and calculated air velocities were reasonably accurate.

An Application of the K-Epsilon Turbulence Model to Predict Air Distribution in a Slot-Ventilated Enclosure

ABSTRACT THE TEACH computer model was modified to predict two-dimensional, isothermal air flow patterns and velocities in a slot-ventilated enclosure of simple geometry. Air distribution patterns, velocities, jet growth and attachment, and entrainment predictions were found to agree well with published data.