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Evaluation and Optimization of Model-based Predictive Controllers for Dual-Fuel Switching and Load Shifting in Residential HVAC Sector

Evaluation and Optimization of Model-based Predictive Controllers for Dual-Fuel Switching and Load Shifting in Residential HVAC Sector
住宅 HVAC 领域双燃料切换和负荷转移的基于模型的预测控制器的评估和优化
批准号:
508045-2017
负责人:
Fung, Alan
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
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英文摘要
In many regions of North America, natural gas is typically used for space heating via a furnace/boiler whileelectricity is used for space cooling via a central air-conditioner or heat pump. Due to increased demands forsummer cooling and advancements in air source heat pump (ASHP) technologies, builders of residential homesare adopting ASHP as the main heating, ventilation and cooling (HVAC) system. However, ASHP capacityand efficiency drops with lower outdoor temperatures, typical in Canada, thus requiring a backup heatingsystem, be it electric or otherwise. This trend has increased strain on the aging electrical grid, increases overallenergy costs, and has associated environmental impact, particularly during peak demand periods. To mitigatethese issues, Ecobee and Ryerson University are collaborating to develop a smart HVAC controller that can beimplemented and deployed in residential homes within Ecobee's smart thermostats to optimally decide whetheran electrically driven ASHP or a natural gas furnace/boiler should be used on a real-time basis, utilizingtemporal information on equipment efficiencies, energy pricing, and short-term weather forecasts. This systemcould also be linked to the local utility's demand response (DR) system for full integration and participationwith local smart grid infrastructure, thus, offering even greater flexibility and benefit to both home owners andutilities. The expected smart predictive residential HVAC control system will offer a user friendly cost savingopportunity to home owners. If the controller were widely deployed and aggregrated, it could potentiallyprovide a cost effective and ubiquitous mechanism, as a dispatchable load, for utilities (both electric andnatural gas) to better manage their infrastructure by maximizing the utilitization of their assets through supplyand demand optimization. Therefore, the proposed system will be benefical to both home owners, by having amore flexible energy supply at a lower energy cost, and utilities (electric and natural gas) alike.
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Novel Renewable Energy based Integrated Energy Systems Towards Net-zero Energy Buildings and Communities
  • 批准号:
    RGPIN-2019-06853
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.84万
  • 财政年份:
    2022
  • 负责人:
    Fung, Alan
  • 依托单位:
Novel Renewable Energy based Integrated Energy Systems Towards Net-zero Energy Buildings and Communities
  • 批准号:
    RGPIN-2019-06853
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.84万
  • 财政年份:
    2021
  • 负责人:
    Fung, Alan
  • 依托单位:
Novel Renewable Energy based Integrated Energy Systems Towards Net-zero Energy Buildings and Communities
  • 批准号:
    RGPIN-2019-06853
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.84万
  • 财政年份:
    2019
  • 负责人:
    Fung, Alan
  • 依托单位:
Smart Integration and Control Strategies for Multi-Fuel Residential Hybrid Integrated HVAC Systems
  • 批准号:
    542594-2019
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2019
  • 负责人:
    Fung, Alan
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
供应链管理中的稳健型(Robust)策略分析和稳健型优化(Robust Optimization )方法研究
  • 批准号:
    70601028
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    7.0万元
  • 批准年份:
    2006
  • 负责人:
    王明征
  • 依托单位: