Volume 07: Proceedings of Applied Energy Symposium: CUE2019, China, 2019

Greenhouse Climate Model Predictive Control for Energy Cost Saving Dong Lin*, Lijun Zhang, Xiaohua Xia


In this paper, an optimal strategy for greenhouse climate control is proposed. The objective is to minimize the total energy cost for greenhouse heating and cooling while keeping the greenhouse climatic conditions (temperature, relative humidity, carbon dioxide concentration) within required ranges. A dynamic model with three inputs and three outputs is adopted. The time-of-use electricity tariff is considered to calculate the energy cost. The proposed strategy is compared with an optimal control strategy which aims at minimizing the total energy consumption. In order to reduce the impact of system disturbance, a model predictive control (MPC) method is presented. The performance index (relative deviation mean) of the proposed MPC and an open loop control are calculated under 2 % system disturbances. The results show that compared with the strategy of minimizing energy consumption, the proposed strategy has higher energy consumption but lower cost. Moreover, MPC has better tracking performance than open loop control.

Keywords Greenhouse climate, Energy cost, Time-of-use, Model predictive control

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