IOT enabled greenhouse automatic control system for energy efficiency optimization.

Luk, Patrick Chi-Kwong - Associate SupervisorAgricultural greenhouses provide optimal conditions for plant growth, but they consume an excessive amount of energy, making energy the second-largest expense after labour costs. Most of the energy is used for heating, which is a major contributor to the high energy demand of the system. Precise and timely control technology can help reduce energy costs and increase profitability. The integration of IoT into greenhouses is a new development in smart agriculture that has the potential to optimise energy use. Various methods exist for optimising energy use in greenhouses, including the use of phase change materials, efficient greenhouse construction designs, and control systems. However, smart automatic control systems are an efficient method that has not been explored enough. Understanding the control algorithm and its proper implementation for use in the greenhouse control system is critical for energy optimisation. This thesis makes three main contributions to greenhouse temperature control. First, a dynamic, physics-based model of greenhouse temperature was optimised to be adaptable for greenhouses equipped with IoT hardware. Second, two control algorithms were implemented in simulation to regulate the system to the grower's desired temperature, while four other control algorithms were implemented to evaluate their energy minimization capability. Results showed that the MPC controller was the best controller in terms of energy savings. Nevertheless, for small to medium greenhouse operators who may have limited resources, relatively simple on-off control algorithm is cost-effective. Finally, the study demonstrates that an IoT-based control system can optimise the energy use in the greenhouse. The use of IoT technology has the capacity to overcome the greenhouse energy management problem with a distribution control system aided by cloud computing. This study demonstrates the potential of IoT-based control systems to save energy and improve greenhouse efficiency by reducing delays and increasing control effectiveness.PhD in Energy and Powe

A physics-based modelling and control of greenhouse system air temperature aided by IoT technology

The need to reduce energy consumption in greenhouse production has grown. Thermal heating demand alone accounts for 80% of conventional greenhouse energy consumption; this significantly reduces production profit. Since microclimate affects crop metabolic processes and output, it is essential to monitor and control it to achieve both quantity and quality production with minimum energy consumption for maximum profit. The Internet of Things (IoT) is an evolving technology for monitoring and controlling environments that have recently been adopted to boost greenhouse efficiency in many applications by integrating hardware and software solutions; therefore, its adoption is thus critical in enabling greenhouse energy consumption minimisation. The first objective of this study is to improve and validate a greenhouse dynamic air temperature model required to simulate or predict indoor temperature. To achieve the first objective, therefore, an existing model was enhanced and a closed loop test experimental data from the IoT cloud-based control system platform deployed in the prototype greenhouse built in Cranfield University was used to validate the model using an optimisation-based model fitting approach. The second goal is to control the greenhouse air temperature in simulation using relatively simple PI and on-off control strategies to maintain the grower’s desired setpoint irrespective of the inevitable disturbances and to verify the potential of the controllers in minimising the total energy input to the greenhouse. For the second objective, the simulation results showed that the two controllers maintained the desired setpoint; however, the on-off strategy retained a sustainable oscillation, and the tuned PI effectively maintained the desired temperature, although the average energy used by the controllers is the same

A Physics-Based Modelling and Control of Greenhouse System Air Temperature Aided by IoT Technology

25th May, 2022 data set. The data contain the Solar irradiance, windspeed and outdoor temperatureThis research received no external fundin