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Research and application of an intelligent control system in central air-conditioning based on energy consumption simulation

机译：基于能耗仿真的中央空调智能控制系统的研究与应用

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For the central air-conditioning energy-saving,it is common practice to use a wide range of PID controllers in engineering to optimize energy savings. However, the shortcomings of the PID controller have also been magnified on this issue, such as: calculation accuracy is not enough, the calculation time is too long. Particle swarm optimization has the advantage of fast convergence. This paper is based on Particle Swarm Optimization apply in PID controller tuning parameters in order to achieve the purpose of saving energy while ensuring comfort. The algorithm proposed in this paper can adjust the weight according to the change of population fitness, reduce the weights of particles with lower fitness and enhance the weights of particles with higher fitness in the population, and fully release the population vitality. The method in this paper is validated by the TRNSYS model based on the central air-conditioning system. The experimental results show that the room temperature fluctuation is small, the overshoot is small, the adjustment speed is fast, and the energy-saving fluctuates at 10%.
机译：对于中央空调节能，常规做法在工程中使用各种PID控制器来优化节能。但是，PID控制器的缺点也在这个问题上放大了，例如：计算精度是不够的，计算时间太长。粒子群优化具有快速收敛的优点。本文基于PID控制器调谐参数应用粒子群优化，以达到节省能源的目的，同时确保舒适。本文提出的算法可以根据种群适应度的变化调节重量，减少适合度较低的颗粒的重量，并增强具有较高人群的粒子的重量，并充分释放种群活力。本文的方法由基于中央空调系统的TRNSYS模型验证。实验结果表明，室温波动小，过冲小，调节速度快，节能波动为10％。

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