George Lo

Managing residential-level EV charging using network-as-automation platform (NAP) technology

The amount of power that can be provided for charging the batteries of the electric vehicles connected to a single neighborhood step-down transformer is constrained by the infrastructure. This paper presents a distributed and collaborative residential-level power grid management application to alleviate the need of costly infrastructure upgrade. The application is designed to be hosted in our in-house developed network-as-automation platform (NAP) technology where most of the control functionalities may be moved onto the networking devices. Moreover, we have adapted a service-oriented software engineering principle to achieve scalability, autonomous, and architecture agnostic properties for the residential-level EV charging. We demonstrate a functional prototype where off-the-shelf networking devices capable to host a Linux Operating system are used to showcase the NAP technology. Furthermore, we developed a web-based user interface that may be accessible from any standard computing device, e.g. iPhone, to monitor the runtime operation of this application.

Automatic HVAC fault detection and diagnosis system generation based on heat flow models

This article introduces a new graph-based modeling methodology called heat flow modeling (HFM) for the purpose of mapping building information model (BIM) of HVAC systems automatically into fault detection and diagnosis (FDD) systems that can be integrated into HVAC control systems. The goal is an efficient and effective support of the maintenance of HVAC systems to detect and locate faults that may reduce energy efficiency, user comfort, or system lifetime. The nodes of the HFM model have a one-to-one relationship with HVAC system components and related building entities. The nodes are connected by arcs that model the flows in the HVAC systems, e.g., air, water, and information flows. The functionality of the nodes includes state variable estimations and failure rule evaluations. The failure rule outputs can be fed to an associative network based diagnosis engine to locate the faults. Since HFM nodes are instances of generic classes derived from small libraries, HVAC FDD systems can be automatically generated. The simulation result has shown the effectiveness of a proposed FDD approach and two software prototypes demonstrating the reduced engineering effort of fault detection for a small bank HVAC system.