SBIR Phase I: Low-Cost, Vision-Enhanced, High-Efficiency Heat Cable Control System

SBIR 第一阶段：低成本、视觉增强、高效热电缆控制系统

• 批准号: 2224907
• 负责人: Thomas Clardy
• 金额: $ 27.49万
• 依托单位: POWDER WATTS, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2224907&HistoricalAwards=false
• 关键词: SBIR; Phase; Low; Cost; Vision

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be realized through the development of vision-enhanced, smart control for heat cables. Heat cables are installed on millions of roofs in North America to prevent build-up of roof-damaging ice dams but they currently have flawed, rudimentary controls, and consume large amounts of energy (tripling the energy consumption of a typical home during the winter months). Combining information from easy-to-install roof cameras, temperature sensors, and local weather forecasting, a machine learning system will turn on heat cables only when needed. A total of 8 billion installed feet of heat cable on roofs and gutters in North America annually consume 135 Terawatt-Hours of electricity and emit 52 Megatons of carbon dioxide and methane. Preliminary data indicate this consumption, the associated costs, and carbon dioxide and methane emissions can be reduced significantly, creating a large commercial impact for residential and commercial building owners, a payback period for the customer of one winter season, and a considerable decrease of the nation's carbon footprint. Because of heat cables' large electrical power consumption, the technology will also provide electrical utility companies with a tool to stabilize the electrical grid and load balance, contributing to national energy security and competitiveness.This SBIR Phase I project proposes to pursue innovations to enhance the energy efficiency of heat cable systems. This system will including an energy harvesting system to power a roof-mounted, camera-based, sensor system that uses machine-vision and machine-learning to precisely control roof heat cables based on their primary function: the prevention of ice dams. Surprisingly, little is known about optimal heat cable control, including key input variables such as temperature, weather and the variability and role of roof features (type, angle, orientation). Collecting and analyzing these data will further the understanding of optimal heat cable control. Heat cable power consumption will be compared to historical and model-derived power consumption. Technoeconomic analysis will help to fine-tune and scale the revenue model. The energy harvesting technology based on trickle-charging the roof-based camera system battery will make the system cordless, easy to retrofit to existing installations, and low-maintenance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力将通过开发用于热电缆的视觉增强型智能控制来实现。在北美，数百万个屋顶上安装了热电缆，以防止破坏屋顶的冰坝的堆积，但它们目前存在缺陷，基本的控制，并消耗大量的能源（在冬季的几个月里，一个典型的家庭的能源消耗是三倍）。结合来自易于安装的屋顶摄像头、温度传感器和当地天气预报的信息，机器学习系统将仅在需要时打开热电缆。在北美，屋顶和排水沟上总共安装了80亿英尺的热电缆，每年消耗135太瓦时的电力，排放52兆吨二氧化碳和甲烷。初步数据表明，这种消耗、相关成本以及二氧化碳和甲烷排放量可以显著减少，为住宅和商业建筑业主带来巨大的商业影响，为客户提供一个冬季的投资回报期，并大大减少国家的碳足迹。由于热电缆的耗电量很大，该技术还将为电力公司提供稳定电网和负载平衡的工具，为国家能源安全和竞争力做出贡献。SBIR第一期项目旨在通过创新来提高热电缆系统的能源效率。 该系统将包括一个能量收集系统，为屋顶安装的基于摄像头的传感器系统提供动力，该系统使用机器视觉和机器学习来精确控制屋顶加热电缆，其主要功能是防止冰坝。令人惊讶的是，人们对最佳热电缆控制知之甚少，包括关键输入变量，如温度，天气和屋顶特征（类型，角度，方向）的变化和作用。收集和分析这些数据将进一步了解最佳的热电缆控制。将加热电缆功耗与历史和模型导出的功耗进行比较。技术经济分析将有助于调整和扩大收入模式。基于屋顶摄像机系统电池涓流充电的能量收集技术将使系统无线化，易于改造现有安装，并且维护成本低。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。