基于随机模型预测控制的智能楼宇能量管理方法

doi:10.3969/j.issn.2097-0706.2022.10.011

摘要/Abstract

摘要：

建筑楼宇不仅是我国的能耗大户，更是碳排放的重要来源。智慧建筑能耗管理对于提高建筑楼宇系统能量利用效率、实现节能降碳至关重要，然而由于环境温度、辐照度等环境因素预测的不确定性，对系统经济运行造成不可忽略的影响。提出了一种考虑建筑蓄热特性，基于机会约束随机模型预测控制的智能楼宇能量管理方法。该方法通过将建筑热动态特性引入楼宇能量系统模型，考虑了由于室外温度和光照强度预测偏差导致状态约束违背的概率描述，通过机会约束与仿射扰动反馈结合，将概率约束转化为确定性约束，提出基于机会约束随机模型预测控制的楼宇能量管理优化问题，实现各用能设备的优化调度。仿真结果表明，该方法能够有效减少环境因素预测不确定性引起运行成本的增加，提升用户舒适度及系统整体运行的鲁棒性。

关键词: 智能楼宇, 暖通空调系统, 随机模型预测控制, 优化调度, 热舒适度, 碳排放, 地源热泵

Abstract:

Buildings are major energy consumers and carbon emission sources in China.Building energy management systems are vital to improve the energy utilization efficiency，save energy consumption and reduce carbon emissions.However，the prediction uncertainties of ambient temperature，solar irradiation and other environmental factors are detrimental to the economy of the whole system.Accordingly，a smart building energy management method based on chance-constrained stochastic model predictive control considering the characteristics of buildings'heat storage is proposed.By introducing the building thermal dynamic characteristics into the building energy system model，the proposed method descripts the probability of the state constraint violation caused by the prediction deviation of outdoor temperature and solar irradiation.Combining the chance constraint and affine disturbance feedback，the probability constraint can be transformed into deterministic constraint.Then，a smart building energy management model based on chance-constrained stochastic model predictive control is constructed，to realize the optimal operation of each energy-consuming equipment.The simulation results have shown that the proposed method can effectively reduce the operating costs caused by the uncertainty prediction on environmental factors and improve the comfortableness and robustness of the overall system.

Key words: smart building, HVAC system, stochastic model predictive control, optimal scheduling, thermal comfort, carbon emissions, geothermal heat pump

中图分类号:

TK02

张怡, 房方. 基于随机模型预测控制的智能楼宇能量管理方法[J]. 综合智慧能源, 2022, 44(10): 83-90.

ZHANG Yi, FANG Fang. Smart building energy management strategy based on stochastic model predictive control[J]. Integrated Intelligent Energy, 2022, 44(10): 83-90.

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控制器	J_eco
控制器	β=10	β=100	β=200	β=500
DeMPC	99.4	394.8	723.0	1707.7
SMPC	77.8	94.0	121.9	145.2
PBMPC	65.4	65.4	65.4	65.4

控制器	DV
控制器	β=10	β=100	β=200	β=500
DeMPC	6.2	6.2	6.2	6.2
SMPC	0.55	0.57	0.67	0.04
PBMPC	0	0	0	0