基于模糊区间优化的建筑空调系统预测控制方法
Method of Model Predictive Control for Building Air-conditioning System Based on Fuzzy Interval Optimization
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摘要: 为进一步保障办公建筑室内人员的热舒适需求, 提出一种基于模糊区间优化的建筑空调系统预测控制方法. 首先, 基于建筑运行数据, 充分考虑地理位置、气候环境及人群差异性对舒适感受的影响, 采用模糊规则隶属度函数对传统舒适指标进行优化, 明确室内人员舒适感受的温度区间; 然后, 采用模型预测控制(model predictive control, MPC)方法对空调设定值进行调控, 同时, 结合区间控制策略使办公建筑的室内温度维持在所提出的舒适温度区间; 最后, 通过建筑环境智能监控系统对提出的方法进行实验验证, 室内人员的舒适满意度提高了34%. 结果表明, 提出的模糊热舒适区间可以更好地满足室内人员的舒适感受, 而且结合区间MPC方法, 可以在保证室内温度舒适的同时减少MPC控制器的输出动作次数.Abstract: To further guarantee the thermal comfort requirements of indoor staff in office buildings, a predictive control method of building air conditioning system based on fuzzy interval optimization was proposed. First, based on the building operation data, fully considering the impact of differences in geographical location, climate environment and people on the feeling of comfort, the membership function of fuzzy rules was used to optimize the traditional comfort index, so as to clarify the temperature range of indoor people's comfortable feeling. Then, the model predictive control method was used to adjust the air-conditioning setting value, and the indoor comfortable temperature range was maintained by combining the interval control strategy. Finally, the proposed method was embedded in the smart building monitoring system to verify its advantaged and effectiveness, and the comfort satisfaction of indoor staff was improved by 34%. Results show that the fuzzy comfort zone proposed in this paper can better satisfy the comfortable feeling of indoor people, and integrated with the interval model predictive control method the control actions of the MPC controller can be reduced simultaneously.