Smart Integration and Control Strategies for Multi-Fuel Residential Hybrid Integrated HVAC Systems

该项目的目标是调查和评估两套混合住宅天然气-电力HVAC系统的智能集成和控制策略，以同时降低能源成本和温室气体（GHG）排放，同时提供远程设备诊断功能以进行预测性维护。拟议的系统将利用云计算平台，ICT，物联网传感器，WiFi连接的恒温器和AI/ML/数据分析技术来开发这样的控制器。所研究的混合HVAC系统包括1）空气源热泵（ASHP）和天然气炉，以及2）寒冷气候ASHP、无箱天然气热水器和电热水箱，所有这些都与可变容量液体循环空气处理单元耦合。为了应对这些挑战，Cricket Energy和瑞尔森大学正在合作开发一种智能HVAC控制器，该控制器可以在住宅中实施和部署，以1）最佳地决定是否应该实时（每小时）使用电动ASHP或天然气炉/锅炉，利用空间加热需求，设备容量和效率，能源定价，和短期天气预报; 2）使用数据分析提供远程设备诊断以进行预防性维护。该系统还可以连接到当地公用事业的需求响应（DR）系统，以便与当地智能电网基础设施完全集成和参与，从而为房主和公用事业提供更大的灵活性和利益。预计基于云的智能预测住宅HVAC控制系统将为业主提供用户友好的成本节约机会，同时使行业合作伙伴能够为远程设备诊断和预测性维护创建新的基于订阅的服务。因此，所提出的系统将有利于房主，以较低的能源成本提供更灵活的能源供应，以及公用事业（电力，天然气和服务提供商/聚合器）。对社会而言，更多天然气被清洁电力来源（例如安大略、魁北克、不列颠哥伦比亚省及马尼托巴）取代用作供暖，将转化为较低的整体温室气体排放。

The objective of the project is to investigate and evaluate the smart integration and control strategy of two sets of hybrid residential natural gas-electric HVAC systems for simultaneous reduction of energy cost and greenhouse gas (GHG) emission while providing remote equipment diagnostics capability for predictive maintenance. The proposed system will utilize the cloud computing platform, ICT, IoT sensors, wifi-connected thermostat, and AI/ML/data analytic techniques to develop such controller. The studied hybrid HVAC systems include 1) an air source heat pump (ASHP) and a natural gas furnace and 2) a cold climate ASHP, a tankless natural gas water heater, and an electric hot water tank all coupled with a variable capacity hydronic air handling unit. To address these challenges, Cricket Energy and Ryerson University are collaborating to develop a smart HVAC controller that can be implemented and deployed in residential homes to 1) optimally decide whether an electrically driven ASHP or a natural gas furnace/boiler should be used on a real-time (hourly) basis, utilizing temporal information on space heating demand, equipment capacities and efficiencies, energy pricings, and short-term weather forecasts and 2) provide remote equipment diagnostics for preventive maintenances using data analytics. This system could also be linked to the local utility's demand response (DR) system for full integration and participation with local smart grid infrastructure, thus, offering even greater flexibility and benefit to both home owners and utilities. The expected cloud-based smart predictive residential HVAC control system will offer a user-friendly cost saving opportunity to home owners while enabling the industry partner to create new subscription-based services for remote equipment diagnostics and predictive maintenance. Therefore, the proposed system will be benefical to both home owners, by having a more flexible energy supply at a lower energy cost, and utilities (electric, natural gas, and service provider/aggregator) alike. For the society, more natural gas being displaced by the clean source of electricity (such as in Ontario, Quebec, British Columbia and Manitoba) for heating will translate into lower overall GHG emission.