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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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