Recent Advances in Distributed M onitoring of HVAC Systems and the Impact on Modern P ower G rids Babak Fahimi PhD University of Texas at Dallas REVT Renewable Energy and Vehicular Technology Lab ID: 674340
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REVT
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Renewable Energy and Vehicular Technology Lab
Recent Advances in
Distributed Monitoring of HVAC Systems and the Impact on Modern Power Grids
Babak Fahimi, PhD
University of Texas at DallasSlide2
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Renewable Energy and Vehicular Technology Lab
Renewable Energy & Vehicular Technology Laboratory
2Slide3
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Renewable Energy and Vehicular Technology Lab
1 post-doctoral scientist, 11 PhD, 3 MS, 2 Undergraduates, 3 visiting scholars
2017 Research Expenditure: $1.2M2017 publications: 12 journal articles, 25 conference papers, 2 invention disclosuresRenewable Energy & Vehicular Technology Laboratory3Scientific StaffSlide4
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Transportation Electrification
Electric and hybrid vehicle propulsion
Fault tolerant drives
Mobile wireless charging
Maglev and linear drives
Electric aircraft propulsion
Electric marine propulsion
Electric auxiliary drives
Distributed Power Generation
Solar energy systems
Wind energy systems
Energy management
Smart micro-grids
Reliability analysis and life time monitoring
Grid integration
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
GaN
,
SiC
utilization
Low power electronics
Areas of Research:Slide5
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Your
Company
Corporate Engagement Strategy Slide6
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Modern GridSlide7
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Evolution of Grid
Source: http://www.edsoforsmartgrids.eu/home/why-smart-grids/Slide8
Combined Heat
& Power
Heatling Grid
Turbines
Electricity Grid
Hydrogen
Electrolysis
Transportation Fuel
Nat. Gas Pipelines and Storage
Storage
Biogas
Natural Gas Hydrogen
Variable mixing
Gasoline
Diesel
Biofuel
Integrated Energy Systems
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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
enhancementSlide10
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Opportunities
Potential Solar energy map
Potential Wind energy map
By 2030 DOE predicts that 20% of US electricity should
be generated in wind farmsSlide11
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Multi-port Power Electronic Interface (MPEI)
Features:
Distributed generation
Economic dispatching
Reliability
Disaster mitigation
Power quality improvement
Communication
Cyber security protocolsSlide12
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Multi-port Power Electronic Interface (MPEI)Slide13
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Multi-port Power Electronic Interface (MPEI)
Base Power Management – Intelligent hybrid
microgridSlide14
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Multi-Port
ElectronicsInterface (MPEI)Solar-ExpansionGenerator-ExpansionWind Turbine-ExpansionBattery-Expansion
Expansion Slot
Expansion Slot
Minimal Storage
Solar Array
Diesel Generator
Wireless Communication
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 kW (Forward Operation units) to MW (Base Systems
)
Wind Turbine
Battery Storage
System
Multi-port Power Electronic Interface (MPEI)
Base Power Management – Intelligent hybrid
microgridSlide15
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Multi-port Power Electronic Interface (MPEI)
Base Power Management – Intelligent hybrid
microgridSlide16
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Multi-port Power Electronic Interface (MPEI)Slide17
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Multi-port Power Electronic Interface (MPEI)Remote computation and Data analyticsTransferring computational resources to a remote locationreduces hardware requirements provides access to unlimited computational capabilityallows long term field data collection and analysisApplications:Supply-demand managementEconomic dispatchingDisaster mitigationRemote fault diagnosis
Fault prediction/prevention
Improvement of grid reliabilitySlide18
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Source: Calculation of Voltage Sag Indices for Distribution Networks. Juan A. Martinez-Velasco, Jacinto Martin-Arnedo
Change in Frequency spectrum
Multi-port Power Electronic Interface (MPEI)
Remote computation and Data analyticsSlide19
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Feature 1Feature 2
Feature 3
Feature 4
Feature 5
…
Example1
Time
Weather
Voltage 1_1
Current 1_1
Voltage 1_2
…
Example2
Time
Weather
Voltage 2_1
Current 2_1
Voltage 2_2
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
X =
Example solution: The voltage sag experienced
in Richardson around
6pm during bad weather usually leads to
an
outage!
Multi-port Power Electronic Interface (MPEI)
Remote computation and Data analyticsSlide20
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Multi-port Power Electronic Interface (MPEI)Availability of variable output portsCriticalSub-criticalNormal loadCapability of variable output signals Normal loadVariable load – Integrated adjustable speed drives: pool pumps, AC compressor ModularitySlide21
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HVAC ConcentrationSlide22
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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
Rate of increase of HVAC equipment = 6.8% annually
HVAC equipment market size, year 2019 = $20.4 billion
(Source: “HVAC Equipment” -
Freedonia
)
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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)
.
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Total
energy consumption breakdown of US in 2012
Residential
energy consumption breakdown of US in 2012Slide24
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Typical System
Current HVAC systems, mostly residential units, utilize line start induction motors.
Compressor
Evaporator
CondenserSlide25
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-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:
An adjustable speed driver.
A bi-directional communication platform supported by cloud computing and machine learning algorithms.Slide26
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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).
Conventional
Variable Frequency Drives
VFD market
size for 2018
= $1.08
billion.Slide27
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Monitoring system
11230 Btu/h – 3290 W1125 W (Input Power)
Data Parsing
DB Storage
Computation
Analytics
Sensor Cluster
Some Data filtering
Communication Channel
Sensor array
VFD
AggregatorSlide28
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Hardware
Sensor TypeLocationVoltageMachine Phase input, Electronics
Current
Machine Phase input, Electronics
Machine T.
Machine frame, Electronics
Voltage
Grid
input/User behavior
Current
Grid
input/User behavior
Ambient T.
Aggregator
Humidity
Aggregator
Pressure
Aggregator
Vibration
Aggregator
/Machine
Frame
Current Sensors
Voltage Sensors
Temp. & Humidity Sensors
Sensor Outputs, I2C, SPI
Specifications:
Power level – U
p to 3kW.
Input – Grid.
Output – Up to 3 motors control outputs.
MCU – TMSF28335
Sensors – Voltage, Current, on boards Temperature and Humidity sensors
Peripherals –
Analog
interface,
I2C and SPI communication.Slide29
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Communication
ServicesSlide30
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Communication
Data BaseData is stored with a node identifier (3) followed by a time stamp (4-5-2017 17:58:36) for query purposes.Slide31
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Software/Algorithm
Induction Motor Fault classification using neural networksTraining 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.Slide32
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Software/Algorithm
Characteristics of the compressor motor:Single speed operation.Multiple on-off cycles.High inrush current.Main FaultsBased on collected, 3 tier filtered data.
Inter Turn Winding Fault -
Temperature and Current.
Bearing Fault -
Vibration signature
.
Output
: classes, where each class represents the category of interest
Inter Turn Fault
Bearing Fault
Additional 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 ProtectionSlide33
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Thank you!!