I-Corps: A Cost Limited Home Thermostat (CLD/HT)

I-Corps：成本有限的家用恒温器 (CLD/HT)

• 批准号: 1249175
• 负责人: Jonathan Sprinkle
• 金额: $ 5万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1249175&HistoricalAwards=false
• 关键词: Corps; Cost; Limited; Home; Thermostat; Corps; Cost; Limited; Home; Thermostat

This projects describes a new kind of thermostat, where the setpoint is not necessarily an array of times and temperatures. Rather, the setpoint is a cost, and the output of the thermostat program is the expected setpoints to achieve this cost over the next month, based on typical weather patterns. The approach is possible given the innovative system model effort, which models the home in such a way as to account for Gaussian disturbances in weather and model error, resulting in cumulative costs that are within a certain bound of the system?s prediction. For more than a decade, the promise of smart-thermostats has been to lower energy costs?but to date, the exact amount that energy costs can be lowered is non-trivial to calculate, or even predict. This work allows homeowners to equate a setpoint schedule with cost of anticipated energy usage, and is shown (in previous publications) to predict that anticipated energy usage within 10% error. Further, if a homeowner sets a desired spending setpoint (e.g., $100 for this month), the setpoint schedule can be generated and (using data gathered previously from that home) can be bounded by certain error amounts that are derived from predicted weather deviations.Home energy made up nearly 25% of all energy consumed in the US in 2010, and 31% of this energy is estimated to come from home heating, ventilation, and air conditioning (HVAC) systems. Yet, the inputs available to a homeowner for those systems are not easily correlated to the energy consequences, making it difficult (if not impossible) for a homeowner to choose setpoints in order to meet a budget each month. The proposed work will produce technology that can impact this very large percentage of the energy market in the US (and abroad), with little or no necessary construction changes required to the home. Using this technology, current manufacturers can use data they are already collecting to put the consumer in control or a large portion of their home energy use.

该项目描述了一种新型的恒温器，其中设定点不一定是一系列时间和温度。相反，设定点是一个成本，恒温器计划的输出是根据典型的天气模式在下个月实现此费用的预期设定点。鉴于创新的系统模型工作，该方法是可能的，该模型以对房屋的方式进行建模，以说明天气和模型错误的高斯干扰，从而导致累计成本在系统预测的一定范围内。十多年来，智能热量的承诺一直是降低能源成本？但是到目前为止，可以降低能源成本的确切数量是不平凡的，即计算甚至预测。这项工作使房主可以将设定点时间表与预期的能源使用成本相等，并在以前的出版物中显示（在以前的出版物中）预测预期的能源使用量在10％的误差范围内。 Further, if a homeowner sets a desired spending setpoint (e.g., $100 for this month), the setpoint schedule can be generated and (using data gathered previously from that home) can be bounded by certain error amounts that are derived from predicted weather deviations.Home energy made up nearly 25% of all energy consumed in the US in 2010, and 31% of this energy is estimated to come from home heating, ventilation, and air conditioning (HVAC) systems.但是，房主可用于这些系统的投入不容易与能源后果相关，因此房主很难（如果不是不可能）选择设定点以满足每个月的预算。拟议的工作将生产可能影响美国（国外）的这一很大比例的能源市场的技术，而房屋几乎没有必要的施工更改。使用这项技术，当前的制造商可以使用他们已经收集的数据将消费者控制或大部分家庭能源使用。