SBIR Phase I: Isolating Specific Appliance Energy Usage from Whole Building Energy Consumption

SBIR 第一阶段：将特定设备的能源使用与整个建筑的能源消耗隔离开来

• 批准号: 0912914
• 负责人: Hampden Kuhns
• 金额: $ 10万
• 依托单位: Load IQ Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0912914&HistoricalAwards=false
• 关键词: SBIR; Phase; Isolating; Specific; Appliance

This Small Business Innovation Research Phase I project will test the feasibility of a signal processing algorithm to separate energy used by individual appliances from the total natural gas and electricity entering a home. Utility ratepayers may benefit from this detailed information by more-effectively identifying and mitigate inefficient appliances and activities. The new generation of smart electric meters currently being deployed for automated reading and time of use pricing are not be able to provide this level of detail. The signal processing algorithm evaluated in this study is innovative in its use of non-parametric statistical measures and specific conductance signatures to accurately distinguish individual appliance loads. Tests will be performed in three residences to compare the performance of the load disaggregation system with that of isolated electrical power measurements from ten or more appliances. The intended outcome of this project is to create an easy-to-use tool that will continually educate consumers to reduce energy consumption. When coupled with adoption of renewable energy sources, improving energy efficiency reduces greenhouse gas emissions. The commercial potential of this technology is high since residential and small business ratepayers could reduce energy costs if they can reliably identify inefficient appliances or activities. If successful, the energy savings from the average household using this technology would pay for the installed cost of the device in less than three years. Providing appliance specific level load information would transform ratepayers' ability to conserve energy and significantly impact resource consumption.This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

这个小型企业创新研究第一阶段项目将测试信号处理算法的可行性，该算法将单个电器使用的能源与进入家庭的天然气和电力总量分开。公用事业纳税人可以通过更有效地识别和减少低效的设备和活动来从这些详细信息中受益。目前用于自动抄表和按使用时间定价的新一代智能电表无法提供这种级别的详细信息。本研究评估的信号处理算法具有创新性，它使用非参数统计测量和特定电导特征来准确区分各个电器负载。测试将在三个住宅中进行，以将负载分解系统的性能与来自十个或更多设备的隔离电力测量的性能进行比较。该项目的预期成果是创建一种易于使用的工具，不断教育消费者减少能源消耗。与采用可再生能源相结合，提高能源效率可以减少温室气体排放。这项技术的商业潜力很大，因为住宅和小型企业纳税人如果能够可靠地识别效率低下的设备或活动，就可以降低能源成本。如果成功，使用该技术的普通家庭节省的能源将在不到三年的时间内支付该设备的安装成本。提供设备特定级别的负载信息将改变纳税人节约能源的能力，并显着影响资源消耗。该奖项根据 2009 年美国复苏和再投资法案（公法 111-5）提供资金。