Abstract:
The usage of electricity of several businesses around the world has been rising, which is a large proportion of their overhead for some business like horticulture. The proper energy usage management is not only helping to reduce the overall business overhead, but also can be able to balance energy usage and relieve the generating cost for electricity provider. In this research, we provide a simulation-based framework to estimate the electricity cost of cooling and lighting systems along with the plant revenue in horticulture for a given plants temperature and photoperiod profile. Since the electricity price follows a Time-of-Use (TOU) pricing program which asks for a higher price during the peak period, the electricity cost could be reduced by having an adaptive Energy Management System (EMS) performing a demand response function, shifting some electricity demand from the high to low pricing periods. To allow demand shifting, we assume that the temperature settings of the cooling system at different times can be varied within a range but their average must meet the optimal setting for the plant. On SketchUp, we build a model of a simple greenhouse and use EnergyPlus, developed by Lawrence Berkeley National Laboratory, to estimate the electricity consumption for the temperature settings determined using the continuous genetic algorithm (CGA) in MATLAB. Our framework is an attempt to provide a simulation-based decision support tool for horticulturists and investors, to determine the best temperature setting that maximizes the estimated profit, which is the estimated revenue minuses the estimated minimum electricity cost, of producing a given plant with TOU pricing. To illustrate the tool, the Pharachatan-80 strawberry is considered with the optimum average temperature setting to grow it indoor by using an estimated ambient temperature profile and the TOU pricing in Thailand
Thammasat University. Thammasat University Library