Optimal allocation strategy for temperature and humidity based on improved glowworm swarm optimization algorithm

Aiming at the problems that the factors such as strong temperature and humidity coupling, nonlinear time delay and other factors of flower vending machine which affects the optimal matching of the power of the machine. This paper proposed a temperature and humidity optimization allocation strategy based on a variable-step adaptive glowworm swarm optimization algorithm. By studying flower storage constraints, temperature and humidity coupling characteristics and analyzing the influence of temperature and humidity coupling coefficient on the operation cost of flower vending machine. This paper established a temperature and humidity power optimization matching model of the machine with the goal of the optimal economy, and used fuzzy control and improved glowworm swarm optimization algorithm to adjust compensation parameters and optimize the objective function respectively. Simulation results showed that the optimized allocation strategy proposed in this paper effectively reduced the energy consumption of the equipment and improved the economic efficiency of the whole machine