摘要
Abstract
By existing measures, it is difficult to reduce effectively the peak of grid due to the uncertainty of occurred and lasting time. In this paper, therefore, a dynamic optimized model in response to the peak time rebates (PTR) and an on-line control strategy for the smart air conditioning were proposed. The model integrated the relevant cyber information such as the uncertain PTR in accordance with the peak of grid, weather forecast, load forecast, and setting of users’ preference on indoor temperature for minimizing users’ electric bill (or power consumption) under comfortable conditions. A model predictive control (MPC) improved by a dynamic interval optimization measure is used to deal with the uncertain PTR information to realize online optimal control of the air conditioning. Finally, the case with 120 zones of a 6-floor public building, 432 time frames, 72 hours, and 5 random PTR is employed to analyze the validity and flexibility. The result shows that, under comfortable conditions, the response to PTR under the time-of-use (TOU) and the flat price is done fully. The maximum range of the peak power is decreased up to 32.7% and the average is 25.3% under flat price, the maximum range of energy is decreased up to 34.4% and the average is 26.6% under TOU, the electricity bill is saved by 19.9%, 27.6% under flat price and TOU, respectively.关键词
智能空调/信息融合模型/尖峰折扣电价/动态优化区间/模型预测控制Key words
smart air conditioning/information fusion model/the peak time rebates/dynamic optimized interval/model predictive control分类
信息技术与安全科学
