AMAP Colloquium Aachen, February 19 th Dipl.-Phys. Christoph Kausch

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AMAP Colloquium

Aachen, February 19

th

2015

Dipl.-Phys. Christoph Kausch

perpendo Energie- und Verfahrenstechnik GmbH

Am Viadukt 3

52066 Aachen

Tel. 0241/412 500 13

Fax 0241/412 500 19

Energy Efficiency

(2)

perpendo

Energie- und Verfahrenstechnik GmbH

perpendere (lat.) – to investigate, to examine, to consider carefully

perpendo

– I investigate, I examine

Who we are:

the energy specialists for analysis & optimisation of complex issues

highly qualified engineers from various different disciplines

experience of more than 500 projects in commerce and industry

What we do:

Energy Design

– For new developments or extensions

Energy Efficiency Analysis

– For existing sites and processes

Energy Management

– Design, controlling and benchmarking

(3)

Energy Design

– For new developments or extensions

Knowing at an early stage if an idea will work – simulation is the way to be sure

Typical aims of using simulation tools:

 minimising energy costs

 ensuring thermal comfort

 avoiding unwanted operating conditions

Benefits of using simulation tools:

optimisation of material usage and

the need for technical equipment (sizing)

minimising investment costs

high planning reliability by using detailled analyses

(4)

Energy Efficiency Analyses

– Methods for Optimisation

Data-based analysis

logging, handling and

evaluation of existing

energy data

increasing transparency of

status-quo

Model-based analysis

quantification of quantities

not-measured

forecast of modifications

or measures

(„what if“)

(5)

Energy Efficiency Analyses

– Spectralanalysis of Electricity

Demand

(6)

Energy Efficiency Analyses

– Weekly Electricity Load Curves

(7)

Energy Efficiency Analyses

– Measurements

Single Compressor rated at 136 kW on load. Min Load Variable Speed 30 %

Min Load

(8)

Energy Efficiency Analyses

– BMS Display of a HVAC System

These values are physically not possible if the cooling register is closed.

(9)

Site Data (Weather) Site Data (Weather) Geometry (Building Plan) Geometry (Building Plan) Usage (Process) Usage (Process) HVAC Systems HVAC Systems Hourly energy balances for one year

Breakdown of the energy demand to single consumer groups

Interaction between the energy consumers

Identification of unusual or unwanted operational conditions

Quantification of the benefit of saving measures

Forecast of the energy demand under changed operating conditions

Design basis for the development of an energy controlling system (

Benchmarks)

(10)

Energy Efficiency Analyses

– Evaluation of the Current State:

Heat Consumption

Zelte 181 MWh 1,3 % Warmwasser 332 MWh 2,3 % Geb. 6 262 MWh 1,9 % Geb. 4 781 MWh 5,5 % Bäder 555 MWh 3,9 % Lackierung 1 / KTL 1.069 MWh 7,6 % Lackierung 2 900 MWh 6,4 % Geb. 1 6.371 MWh 45,0 % Geb. 2 74 MWh 0,5 % Geb. 3 3.627 MWh 25,6 % Building 6 Building 4 Building 3 Building 2 Building 1 Paint Shop 2 Paint Shop 1 Electrolyte Baths Hot Water Tents

…where?

RLT 10.600 MWh 74,9 % Bäder 555 MWh 3,9 % stat. Heizung 696 MWh 4,9 % PLT inkl. Abdunstzonen 1.969 MWh 13,9 % Warmwasser 332 MWh 2,3 % Electrolyte Baths Hot Water Static Heating

Process Ventilation and Evaporation Zones

HVAC-Systems

…what is it used for?

952 MWh/a 1.641 MWh/a 1.751 MWh/a 1.964 MWh/a 3.393 MWh/a PLT Esta4 (Eisenmann) RLT Esta5 (FCM) 101 Produktion 101a Lager 103 Produktion 14 MWh/a 25 MWh/a 35 MWh/a 56 MWh/a 0 500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 102 Speisesaal 102 Besprechung 104 Extruder 103 Büro innen Jahresheizwärmebedarf [MWh/a]

… or specifically by which unit?

(11)

Energy Efficiency Analyses

– Further Simulation Instruments

(if) (if) controller (if) (if) (if) (if) (if) c h (if) (if) c h (if) (if) (if) (if) c h (if) out instrip (if) (if) c h (if) c h c h (if) (if) 1 2 c Fluid (if) c h c h Brunnen_2_1 Brunnen_2_2 _Controller Bedarf_WWW Bedarf_KHW Bedarf_KWW Abw asser_BK Kanal_BK WT_BK Prw_BK RLHydraulik VLHydraulik Prw_HYDR WT_Hydraulik WWW_P5013 WWW_P5018 Abw asser_BW Kanal_BW WT_BW Speicher_KHW Kanal_FW Ionentauscher Speicher_GFK_KWW_100 Prw 3 Bedarf_SPW P5018_AWWasser WT 4 (neu) P5018_Tank_B WT_2 WT_1 Abw asserP5018 Abw asserFW M WT_Mangel Speicher_RGW Bedarf_RGW Pww 5 WT 3.1 (neu) Speicher_GFK_WWW_50 WT 3.2 (neu) Prw_BW 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 0 100 200 300 400 500 600 Temperatur [°C] Rauchgas ECO Rauchgas WT 1 + 2 Mangelabluft Abwasser FW Anwaschwasser P50/18Abwasser BW Abwasser BK Hydraulikkühlung Abw. FW (41 °C) Speisew. Kessel Nachspeisewasser WWW (41,4 °C) WWW (32 °C) WWW (22,2 °C) KWW Speicher Erdtank >> KWW 0 200 400 600 800 1000 0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 Zeit E le ktris ch e Le is tung [k W ] Pumpen / Ventilatoren [kW] Carrier 30HXC / 3 [kW] Carrier 30HXC / 2 [kW] Carrier 30HXC / 1 [kW] Trane CVGF [kW] Trane RTHD [kW]

Example: improvement of thermal integration

Example: improvement of thermal integration

Electrical p o w er [kW ] time

Example: optimising operations of freezing plants

Example: optimising operations of freezing plants

(12)

Energy Efficiency Analyses

– Fields of Application for

Simulations

Buildings

dynamic building and plant simulation (heating, ventilation and air conditioning)

light simulation for determination of daylight proportion

building element simulation for optimisation of individual constructions

computational fluid dynamics (CFD)

Processes and facilities

optimisation of facility plants (heat / cooling energy, vapor, compressed air, ...)

operation strategies

sequential switching

dynamic load adjustement

cogeneration and trigeneration, heat pumps

thermal integration

(13)

Optimisation of a Chilling System

The setting:

5 cold water chillers (KKM)

3 of identical type

2 independent cooling tower

systems

Group of 3 cooling towers

Central cooling water supply

Central cold water distribution

network

Key data:

Required cooling: 350 … 3.400 kW

Annual demand: 9,7 GWh/a

Zentrale Kühlwasser-versorgung 36 / 26 °C KKM 1-3 KKM 5 KKM 6 central cooling water supply

(14)

Commitment control of the chillers based on the actual chilling power delivered:

Switch-on condition for the next chiller:

95 % capacity of the chillers in

operation exceeded for 10 min

Switch-off condition for the last chiller:

85 % of the available capacity

undercut for 15 min

Chilling System Optimisation: Control Strategy

Switching

sequence

Carrier

30HXC / 1

Carrier

30HXC / 2

Carrier

30HXC / 3

Trane

RTHD

Trane

CVGF

Summer

2

3

4

5

1

Winter

1

3

4

2

5

(15)

Chilling System Optimisation: Part Load Efficiency of the Chiller

Types

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Part Load Q0/Q0N

COP

Carrier 30HXC

Trane RTHD

Trane CVGF

Part Load Q

0

/ Q

0,N

(16)

Chilling System Optimisation: Dependency of the COP on the

Fluid Temperatures

4,0

4,5

5,0

5,5

6,0

6,5

7,0

7,5

8,0

8,5

9,0

18

20

22

24

26

28

30

Kühlwasservorlauftemperatur [°C]

COP

Cold water 6/12 °C, COP at 6/12 °C – 28/32 °C = 5, ξ= const.

(17)

Chilling System Optimisation: Switch on / off conditions

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600

K

ä

lt

eleist

un

g in

kW

Schaltreihenfolge Sommer

Trane Turbo Trane Schraube Carrier 3 Carrier 2 Carrier 1 940 kW 1700 kW 2200 kW 2760 kW

Switching sequence for summer time

cooling capacity [kW]

Trane Turbo Trane Screw Carrier 3 Carrier 2 Carrier 1

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Chilling System Optimisation: Results

Measures:

Changing to optimised switching sequences

Swap condenser side pumps for evaporator side pumps

Adapt the cooling water temperature set point

Costs:

Low implementation costs (programming of the existing metering

system and installation work for the pumps)

Effect:

Reduction of power consumption by 730 MWh/a (36 %)

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Energy Management

– ISO 50001 Framework

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Energy Management

– Continuous Cycle

Proven Approaches

on a regular basis

Energy Reports

Status-quo is evaluated

Feedback is given

Make recognition possible

Energy Forum

Workshop discussions

Department-head meeting

Jour-Fix

Internal audit

Energy use check & monitor act do plan

Important Aspects

• Less documents – more content

• Less EnPI‘s – more interpretation

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Adapted to

individual needs

knowledge about

energy

organisational

requirements

technical

requirements

data-based

requirements

- software - interfaces - data management - reporting - … - strategy - responsibilities

- operating cycle (workflow)

- data access - ... - meter structure - sensor technology - central control technology - …

- energy flow diagram

- energy aspects

- energy goals

- savings listing

- …

An efficient energy management has diverse requirements

– which are different for each company

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Energy Controlling

– Different Approaches to Increase

Energy Efficieny

Advantage of a detailed analysis:

gain in time

lower installations costs for the EIS

time

energy

consumption

effective

energy controlling

classical

energy controlling

increasing

energy

knowledge

(25)

Energy Controlling

– Provide Coordinated Information

Consumption Information:

Current values

Alarms

Consumption Information:

Current values

Alarms

Staff

Staff

Data Preparation

Data Preparation

Data Acquisition

Field Level

Data Acquisition

Field Level

Historic Data:

Data for analysis

Historic Data:

Data for analysis

Manager

Manager

Energy

Energy

Key Indicators:

Cost development

Target achievment

Key Indicators:

Cost development

Target achievment

Management

Management

Consumption Data:

Billing data

Product energy costs

Consumption Data:

Billing data

Product energy costs

Controlling

Controlling

Okt. Nov Dez Jan Feb Mrz Apr Mai KS Kostenstelle qm qm qm qm qm qm qm qm 56 Sozialräume 131,0 132,0144,0 147,0 127,0 137,0 111,0100,0 02 Allgem. Werkdienst 06 Schlosserei 536,0 432,0443,0 304,0 337,0 348,0 373,0409,0 07 Elektrowerkstatt 39,0 58,0 192,0 224,0 165,0 97,0 27,0 45,0 10 Fuhrpark Planwagen 64,0 43,0 46,0 52,0 51,0 46,0 47,0 57,0 13 Fuhrpark Silorfahrz. 15 Produktionsleitung 3,0 2,0 2,0 2,0 2,0 2,0 2,0 2,0 16 Labor 4,0 2,5 3,0 3,0 3,0 3,0 2,0 2,0 17 Versuchsbäckerei 2,0 1,5 1,0 1,0 1,0 1,0 1,0 1,0 14 Techn. Einkauf 2,0 1,0 1,0 1,0 1,0 1,0 1,0 1,0 24 Getreide-Silo/-Lager 41 Reinig.1 u. Mühle 536,0 432,0443,0 304,0 337,0 348,0 373,0409,0

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0 500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 1 2 3 4 5 6 7 8 9 10 11 12 accu m u la te d   natur al   ga s   co ns um pti o n   [M W hHs ] Month 2007 (initial state) 2008 (analysis by perpendo) 2009 (measures implementing) 2010 (energy controlling) benchmark (simulation)

Energy Controlling

– Example of Reporting

target values

(by simulation)

target values

(by simulation)

measured

comsumption

(weather corrected)

measured

comsumption

(weather corrected)

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Energy Controlling

– Specification of Benchmarks & EnPI

A. Historical characteristics:

Consumption figures from previous years

Difficulty: Modifications and new construction are not considered.

Potential savings are not revealed.

C. Calculated characteristics:

Determination of theoretical ideal values

Difficulty: Theoretical boundaries are sometimes only known for parts.

Model development is time-consuming.

B. Comparative characteristics:

Consumption figures of comparable sites

Difficulty: Site-specific features are not considered.

Comparable real estate often does not exist.

Consumption figures per production unit

Difficulty: Characteristics only exist for some sectors and specific

production methods.

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Sustainability

– Carbon Footprint and Emissions Reduction

Avoiding emissions begins with knowing the sources

Procedure

determine of appropriate allocations

consider the supply chain

elaborate reduction potentials

advanced experience with food processing

Target

balancing of greenhouse gas emissions according to GHG-protocol

product carbon footprint

company carbon footprint

meat processing works, balance „Cradle to Gate“, without emissions resulting from meat generation

(29)

Thank you for your attention!

Your Contact:

Dip.-Phys. Christoph Kausch

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