Energy and Vehicular REVT Renewable Technology Lab Recent

Energy and Vehicular REVT | Renewable Technology Lab Recent Advances in Distributed Monitoring of HVAC Systems and the Impact on Modern Power Grids Babak Fahimi, Ph. D University of Texas at Dallas

Energy and Vehicular REVT | Renewable Technology Lab Renewable Energy & Vehicular Technology Laboratory 2

Energy and Vehicular REVT | Renewable Technology Lab 1 post-doctoral scientist, 11 Ph. D, 3 MS, 2 Undergraduates, 3 visiting scholars 2017 Research Expenditure: $1. 2 M 2017 publications: 12 journal articles, 25 conference papers, 2 invention disclosures Scientific Staff Renewable Energy & Vehicular Technology Laboratory 3

Energy and Vehicular REVT | Renewable Technology Lab Areas of Research: Transportation Electrification • Electric and hybrid vehicle propulsion • Fault tolerant drives • Mobile wireless charging • Maglev and linear drives Distributed Power Generation • Solar energy systems • Wind energy systems • Energy management • Smart micro-grids • Electric aircraft propulsion • Reliability analysis and life time monitoring • Electric marine propulsion • Grid integration • Electric auxiliary drives • Fuel cell based hybrid power systems Energy Storage, Management and Harvesting • Remote charging of portable electronics and biomedical devices • Energy scavenging from vibration and solar sources • On-chip power supplies • Prognostics, health management, and control • Battery and ultracapacitor management • Hydrogen harvesting and storage Power electronics, Motors & Drives • Electric machine design • Permanent Magnet • Switched Reluctance • Induction • Electric drive optimization • Sensor elimination • Noise, vibration reduction • Efficiency maximization • Cost minimization • Fault tolerance • Resonant and multi-level converters • PWM strategies • High freq. dc-dc converters • High and low temperature power converters • Ga. N, Si. C utilization • Low power electronics

Energy and Vehicular REVT | Renewable Technology Lab Corporate Engagement Strategy Industrial Advisory Council Fellowships, Endowed Chairs, Buildings Federal Research Grants Internships and Entry Level Jobs Your Company Institute and Center Projects UTDesign Unrestricted Gift Company Sponsored Research

Energy and Vehicular REVT | Renewable Technology Lab Modern Grid

Energy and Vehicular REVT | Renewable Technology Lab Evolution of Grid Source: http: //www. edsoforsmartgrids. eu/home/why-smart-grids/

Energy and Vehicular REVT | Renewable Technology Lab Integrated Energy Systems Electricity Grid Turbines Electrolysis Hydrogen Combined Storage Heat & Power Variable mixing Biogas Natural Gas Hydrogen Gasoline Diesel Biofuel Heatling Grid Nat. Gas Pipelines and Storage Transportation Fuel

Energy and Vehicular REVT | Renewable Technology Lab Modern Power Systems Challenges • Reliability for contingency and uncertainty • Quick dynamic response in the event of a failure • Cyber security • Seamless integration of renewable energy sources • Poor efficiency for end users • Capacity enhancement

Energy and Vehicular REVT | Renewable Technology Lab Opportunities Potential Solar energy map Potential Wind energy map By 2030 DOE predicts that 20% of US electricity should be generated in wind farms

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Features: Distributed generation Economic dispatching Reliability Disaster mitigation Power quality improvement • Communication • Cyber security protocols • • •

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI)

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Base Power Management – Intelligent hybrid microgrid

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Base Power Management – Intelligent hybrid microgrid Wireless Communication Minimal Storage Multi-Port Electronics Interface (MPEI) Solar-Expansion Generator-Expansion Wind Turbine-Expansion Battery-Expansion Slot Solar Array Diesel Generator Wind Turbine Battery Storage System Expansion potential includes: • Solar Module(s) • Diesel Gen-set Module(s) • Wind Turbine Module(s) • Fuel Cell Module(s) • Energy Storage Unit(s) • Battery • Flywheel • Others Scales from Watts (for electronic loads) to k. W (Forward Operation units) to MW (Base Systems)

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Base Power Management – Intelligent hybrid microgrid

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) 16

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Remote computation and Data analytics Transferring computational resources to a remote location • reduces hardware requirements • provides access to unlimited computational capability • allows long term field data collection and analysis Applications: • Supply-demand management • Economic dispatching • Disaster mitigation • Remote fault diagnosis • Fault prediction/prevention • Improvement of grid reliability 17

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Remote computation and Data analytics Change in Frequency spectrum Source: Calculation of Voltage Sag Indices for Distribution Networks. Juan A. Martinez. Velasco, Jacinto Martin-Arnedo 18

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Remote computation and Data analytics X = Example 1 Example 2 … … Feature 1 Feature 2 Feature 3 Feature 4 Feature 5 Time Weather Voltage 1_1 Current 1_1 Voltage 1_2 Time Weather Voltage 2_1 Current 2_1 Voltage 2_2 … … … … Example solution: The voltage sag experienced in Richardson around 6 pm during bad weather usually leads to an outage! 19

Energy and Vehicular REVT | Renewable Technology Lab Multi-port Power Electronic Interface (MPEI) Availability of variable output ports • Critical • Sub-critical • Normal load Capability of variable output signals • Normal load • Variable load – Integrated adjustable speed drives: pool pumps, AC compressor • Modularity 20

Energy and Vehicular REVT | Renewable Technology Lab HVAC Concentration

Energy and Vehicular REVT | Renewable Technology Lab HVAC systems HVAC is the largest source of residential energy consumption in the United States, 47% of total household energy requirements (source: U. S. Energy Information Administration) -Value • Market size o Rate of increase of HVAC equipment = 6. 8% annually o HVAC equipment market size, year 2019 = $20. 4 billion (Source: “HVAC Equipment” - Freedonia)

Energy and Vehicular REVT | Renewable Technology Lab • Value • Environmental impact – Out of the total household energy consumption, Central AC is responsible for around 30%. Presented in the figure below is the total and residential energy breakdown (source: “Energy savings potential and opportunities for high-efficiency electric motors in residential and commercial equipment US Dept. of Energy). Total energy consumption breakdown of US in 2012 Residential energy consumption breakdown of US in 2012 23

Energy and Vehicular REVT | Renewable Technology Lab Typical System • Current HVAC systems, mostly residential units, utilize line start induction motors. • Compressor • Evaporator • Condenser

Energy and Vehicular REVT | Renewable Technology Lab -Current Technology HVAC system can play a substantial role in providing a flexible load in the utility network. This flexibility , in the form of a commitment, is equivalent to that of distributed generation and will potentially allow small consumers of electricity to play an active role in setting the market prices and overall stability of the distribution system. However, to effectively exploit this opportunity, a hybrid (cyber-physical) layout is necessary. The main elements of such systems include: 1. An adjustable speed driver. 2. A bi-directional communication platform supported by cloud computing and machine learning algorithms.

Energy and Vehicular REVT | Renewable Technology Lab - VFD The current HVAC compressor motors are mostly line start induction machines without drive electronics, allowing only binary configuration of “On” or “Off”. To satisfy the government set regulations and to gain the market edge, the HVAC manufacturers are continuously trying to improve efficiency (SEER ratings). Hence, inevitable shift of industry trend towards VFDs is apparent. VFDs reduce energy consumption by matching the heating/cooling load with the HVAC system output. However, introduction of drive electronics alters the efficiency, reliability, and cost of the overall system. The typical topology utilized by VFDs are rectifier – inverter circuits with DC bus capacitors, as shown in figure 1 (for single phase inputs). VFD market size for 2018 = $1. 08 billion. Conventional Variable Frequency Drives

Energy and Vehicular REVT | Renewable Technology Lab Monitoring system • • 11230 Btu/h – 3290 W 1125 W (Input Power) • • Sensor array VFD Aggregator • • • Sensor Cluster Some Data filtering Communication Channel • • Data Parsing DB Storage Computation Analytics

Energy and Vehicular REVT | Renewable Technology Lab Hardware Sensor Type Voltage Current Machine T. Voltage Current Ambient T. Humidity Pressure Vibration Location Machine Phase input, Electronics Machine frame, Electronics Grid input/User behavior Aggregator/Machine Frame Specifications: • • • Power level – Up to 3 k. W. Input – Grid. Output – Up to 3 motors control outputs. MCU – TMSF 28335 Sensors – Voltage, Current, on boards Temperature and Humidity sensors Peripherals – Analog interface, I 2 C and SPI communication. Current Sensors Voltage Sensors Temp. & Humidity Sensors Sensor Outputs, I 2 C, SPI

Energy and Vehicular REVT | Renewable Technology Lab Communication Services

Energy and Vehicular REVT | Renewable Technology Lab Communication Data Base Data is stored with a node identifier (3) followed by a time stamp (4 -52017 17: 58: 36) for query purposes.

Energy and Vehicular REVT | Renewable Technology Lab Software/Algorithm Induction Motor Fault classification using neural networks Training the Neural Network: requires a set of data for which the result is known to deduce a model/feature weights depending on this data. This data is then used to predict future outcomes.

Energy and Vehicular REVT | Renewable Technology Lab Software/Algorithm Output: classes, where each class represents the category of interest Characteristics of the compressor motor: Single speed operation. Multiple on-off cycles. High inrush current. Main Faults Based on collected, 3 tier filtered data. • Inter Turn Winding Fault - Temperature and Current. • Bearing Fault - Vibration signature. Inter Turn Fault Additional Fault Bearing Fault Additional Fault Depending on the prediction accuracy of the model, a time function will be used (based on DB data – run the algorithm few seconds before the fault occurs) for fault Protection

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