© Metis Monitoring 2017 – All Rights Reserved
COSTS, SAVINGS,
the IoTand
REFRIGERATION
Michael BellstedtCEO Minus 40 Group
Refrigeration – a pervasive technology• Industries
• Food processing• Plastics manufacturing• Pharmaceutical• Chemical
Application Liquid chillers / process cooling Blast chilling and freezing Cold storage Air conditioning
Key challenges!!!
• Refrigerant phase-downALL common synthetic refrigerants are on the way OUT. Did you know this?
• High Electricity AND Fuel costsWe all know why!!
• Maintenance and Service costs rising: Major skills shortage and training deficit in the industry. Are you getting ripped off?
Opportunities• Energy efficiency and energy re-use
• Long term refrigerants – CO2, NH3, HFOs
• Integrated heating and cooling
• Integrated Solar PV and refrigeration
• Remote energy management and EEO identification
• Preventive and predictive fault diagnosis
Thermal Processes during Food Manufacture• Singeing• Cooking• Sterilizing / CIP• Scalding• Washdown• Handwash• Process cooling• Chilling• Freezing• Blast freezing• Snap freezing
Conventional Processing Plant
• Singeing
Steam boiler
Cooling tower
Direct gas burner Liquid
chiller
Refrigeration units
Liquid N2
Chilling Freezing Blast freezing
Cooking Sterilizing Scalding Wash down Hand wash Space heating
Process cooling
Snap freezing
Hot Water Generator
A typical example
Single 4MW steam boiler operating at <10% capacity
28 individual air-cooled refrigeration units
Key steps to better energy use• Centralize all refrigeration
• Central ammonia or CO2 plant, or• Central chilled glycol/chilled water plant• Booster units for freezing as needed
• Centralize all heat rejection into one cooling water system (process cooling and refrigeration)
• Recover heat from refrigeration for handwash and washdown
• Use water-source heat pump to extract heat from cooling water, for sterilizers/scalders/wash down
• Gas-fired boilers /heaters for cooking and top-up only
Integrated Heating and Cooling
• Singeing
Steam boiler
Cooling tower
Direct gas burner
Water chiller
Refrigeration units
Liquid N2
Process cooling Chilling Freezing Blast freezing Wash down Hand wash
Cooking
Snap freezing
Sterilizing Scalding Space
heating
Heat pumps
Solar PV + Integrated Heating and Cooling
Cooling tower
Water chiller
Refrigeration units
Process cooling Chilling Freezing Blast freezing Wash down Hand wash
Sterilizing Scalding Space heating
Heat pumps
+
SITE-WIDE ENERGY MANAGEMENT(THE ENERGY AUDIT ALTERNATIVE)
Business Case development of selected EEOs
Interactive project implementation
Verify Saving; Claim Energy Certificates
(NSW and VIC)
Energy Efficiency
Opportunity identificationSite Scoping of
Monitoring (IoT)
Deployment, Dashboard and AI setup
Meatworks example: Power data Measurement and processing
Feeders
• 2 feeders• West End• Central
Transformers
• 12 Transformers• Top workshop• Tannery TX1 & 2• Engine Room TX1 - 5• Boning• Cold Chain• By Product TX1 & 2
Switchboards
• 83 Switchboards• Pump House• Boiler House• Ice Plant• Etc
Measured values
• 128 values• 3-Ph, 1-Ph, CT,
calculated• Individual boards• Large users, like
compressors
Process or service
• 12 Metrics, e.g: • Ammonia plant room• Air compressors• Tannery• Boning room• Plate Freezers• By Products• Waste Water Pumps• Hot Water Pumps• Boiler• Vacuum Pumps• Carcass Chillers• Kill Floor
Refrigeration plant data and metrics
Measured parameters (via sensors and PLC)• Plant pressures (suction and discharge)• Ambient conditions (temperature and humidity)• Compressor load state and speed • Motor currents/power throughout (compressors, fans, pumps)
Calculated metrics• HS and LS capacity in KWR- instantaneous and daily/weekly total or average• HS and LS COP – instantaneous and daily/weekly average• HS and LS power cost - $/kWR
Monitoring Hardware and Software ConfigurationCloud based system
• Unlimited memory• Accessible even when the site is down• Rapid access to the data
App and Dashboard access :• Raw and derived data visualization and
download for EEO analytics• Notes feature• Custom Energy Dashboard• Custom Site Data Analytics and KPIs
Applicable to a large range of applications• Site power submetering: 3Ph & 1Ph• All refrigerant functions : Ammonia, CO2, HFC,
HC • Refrigeration, HVAC, Fluid Chillers, Heat pumps
full cycle monitoring with fault detection• All electric devices full power monitoring
(Tarnsformers, Pumps, Fans, Heaters, Boilers….)
LIVE DASHBOARDS
Increase reporting by further metering• Ammonia flow meters (suction)
• Assign Refrigeration Plant energy use and cost to processes (Boning, Plate Freezers, Carcass Chilling, etc)
• Check compressor condition (calculate KWR vs measured via flow meter)• Autodetect changes to compressor condition over time (Metis AI)
• Town water sub metering• Benchmark town water usage and assign water costs to processes (Engine Room, Boiler,
Tannery, Boning, etc)
• Waste water metering• Benchmark waste water against production per area and assign waste water treatment
and energy costs
• Boiler fuel? Steam flow?• Benchmark fuel use against production per area, assign fuel costs.• Report boiler efficiency and benchmark against production, etc
Production and Consumption Metrics• Production metrics (input) / time interval (daily, weekly)
• Standard Hot Carcass Weight in kg• # animals processed• # cartons packed/shipped• etc
• Consumption metrics (calculated as daily/weekly trend)• Refrigeration power & power cost/ SHCW• Refrigeration duty/SHCW• Plate freezer power & power cost / carton• Kill floor power / animal• etc
REMOTE REFRIGERATION FAULT DIAGNOSIS
TIME TO PROBLEM DETECTION
REFR
IGER
ATIO
N M
AIN
TEN
ANCE
ST
RATE
GY
REACTIVE
PROACTIVE
PREDICTIVE
FIND PROBLEMS FASTER
Analytics?
• Artificial intelligence• Machine learning• Pattern detection• Anomaly detection• Data mining• Statistical regression• Etc
Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed.
Machine LearningLearning to predict behaviour or operation
• Learn “normal” behaviour and detect deviations from it (anomaly detection)
• Use trained symptom detection to detect specific issues (pattern detection)
• Ability to detect even very brief errors invisible to human examination
• Ongoing algorithm improvement for ever increasing accuracy and precision
• Create intelligent and predictive alerts, rather than fixed threshold alarms
Typical results achievable
• Fuel use on some sites can be reduced 90%
• Electricity use reduced up to 50%
• Eliminate refrigerant costs
• Eliminate boiler inspection costs
• Reduce refrigeration service/maintenance costs by >80%
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