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EXAMPLE OF A TYPICAL CASE

• Area - 150 000 m2
• Peak electricity load - 8,7 MW
• Peak – heating load - 7,5 MW
• Heating provided by a gas-fired boiler
• Annual electricity consumption – 40 mn kWh
• Annual heat consumption – 11 mn kWh
• Annual natural gas consumption – 1 mn m3

CO2 emissions:

• Scope 1 – 2,200 t
• Tier 1+2 – 16,800 t

STANDARD SOLUTION

• Area - 150 000 m2
• Peak electricity load - 8,7 MW
• Peak – heating load - 7,5 MW
• Heating provided by a gas-fired boiler
• Annual electricity consumption – 40 mn kWh
• Annual heat consumption – 11 mn kWh
• Annual natural gas consumption – 1 mn m3

CO2 emissions:

• Scope 1 – 2,200 t
• Tier 1+2 – 16,800 t

Capital cost

Cost savings

Payback period

NPV (@10%)

Incl

GSHP

Grid connection

Fuel cost reduction

Carbon emission reduction

14,1 mn

Eur 6,9 mn

Eur 7,1 mn

0,277 mn

-9,6 mn

Eur 0,078 mn

Eur 0,199 mn

51 years

STANDARD SOLUTION


• Substitute boiler with 7,5 MW ground source heat pump (GSHP)
• Electricity consumption goes up to 44 mn kWh p.a.
• Peak electric load goes up to 10,6 MW. which is above the current substation capacity of 10 MW – construction of a new substation is required

SMART MICROGRID


• Demand side control IoT based system
• Demand side IoT based control system - >3000 sensors – power load, thermal comfort, lighting, air quality, equipment parameters
• Integration with the BMS system, use existing controls
• Integration with commercial metering
• Integration with existing submetering
• Integration with customer counters
• Integration with external data sources – weather forecast, electricity market data
• Digital twin

Microgrid

• IoT Equipment control, sensors
• Power loads, DR, emissions
• Big Data
• Analysis/visualization

Microgrid generation and energy flow control

Smart Energy Storage

Mesh optimization: Digital Twin + Machine Learning

ENERGY DROID AI CONTROL SYSTEM

Energy storage

• Energy router with battery storage replacing UPS
• Ice storge
• Thermal storage

Generation

• Solar PV
• Ground source heat pumps

SYSTEM INSTALLATION RESULT AND SOLVED PROBLEMS


• Total system cost Eur 2,6 mn
• Payback -3,5 years
• Demand side optimization

IoT based model predictive (digital twin) HVAC and other electric load control:

• reducing heat consumption by 56%
• Reduced peak heat consumption by 58%
• Increase heat pump efficiency (COP) by 20%
• Decrease total electricity consumption by 9%
• Decrease peak electric consumption by 18%

Energy storage and demand response:

• Thermal storage
• Ice storage
• Battery storge instead of UPS
• Cut peak thermal consumption by 30%
• Cut peak electric consumption by 12%
• Reduce balancing and capacity charge, earn revenues in the demand response and frequency control markets

Generation
GSHP -1,2 MW
Use biofuel for peak loads (<3% a year) and as reserve fuel

An AI based Microgrid dispatch system chooses the optimal mode of operation of all equipment – demand-side, storage, supply

Economics of the smart microgrid solution

Capital cost

Cost savings

Payback period

NPV (@10%)

Incl

GSHP

Smart microgrid

Fuel cost reduction

Carbon emission reduction

2,6 mn

Eur 1,1 mn

Eur 1,5 mn

0,797 mn

36,6 mn

Eur 0,256 mn

Eur 0,199 mn

3,3 years

Electricity cost reduction

Eur 0,343 mn

(energy storage and control)

THE SMART MICROGRID CREATED VALUE OF EUR 37 MN

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Standart solution

Smart microgrid

Standart solution

Smart microgrid

Smart microgrid

Standart solution

Smart microgrid

Standart solution

Payback period, years

NPV Eur, mn

Opex savings mn Eur

Capital cost, Euro mn

EnZu Energie Zukunft GmbH

DE320942794
+49 302 061 6200
Friedrichstr, 95
10117 Berlin

Office in Dubai

Tel. +1 847 323 8651
admin@en-zu.de

Office in Europe

Tel. +39 331 782 8481
admin@en-zu.de