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Pinch Analysis

Fanny Hübner, M.Sc.

Pedro Horta, Ph.D.

Fraunhofer Institute for Solar Energy Systems ISE

SPB Train-the-Trainer Workshop

São Paulo, 12-14 Nov 2019

www.ise.fraunhofer.de

SOLAR PAYBACK - TRAIN-THE-TRAINER SOLAR HEAT FOR INDUSTRIAL PROCESSES

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Content

� Pinch Analysis

� Objective

� Principles

� Impact (example)

� Tools

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Pinch AnalysisObjective

� Pinch analysis enables an overview of cross-process heat exchange possibilities

� Classical method for analyzing heat recovery potential

� Requires a detailed knowledge of the heating and cooling requirements

� Each stream is defined by mass flow, specific heat and inlet and target temperature

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[1] https://www.einstein-energy.net/index.php/training-activities/training-materials, English.zip\English_Intro.zip\English_IT\Slides\Day 2\ EINSTEIN-II_training_slides_M2_1_heatRecovery.pdf

Pinch AnalysisObjective

� The pinch analysis can be used to determine two targets:

� Maximum heat recovery

� Most efficient energy supply

� These are visualized via hot and cold composite curves (CCs)

� Show temperature enthalpy profiles of the hot and cold streams

� A pinch point is identified: lowest vertical temperature difference between the CCs

� The curves can be used to optimize the heat recovery.

In deep… [1]

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Pinch AnalysisImpact (example)

� Laundry

� Energy- and water distribution of reference-laundry without efficiency measures

� Thermal energy demand:

� 2,02 kWh/kg dry laundry

� 4.200 MWh/a

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Pinch AnalysisImpact (example)

� Solar heat can be integrated to either:

� Specific Unit Operations (process level)

� Utility System (supply level)

� There are 2 main challenges for the integration of solar heat by pinch analysis:

� Time dependency of solar heat

� Solar heat gains are not known in detail until the solar process heat system concept (required temperatures and flows) is defined

� The completion of the Pinch Analysis in combination with solar heat integration is iterative.

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Pinch AnalysisImpact (example)

� Initial status

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Pinch AnalysisImpact (example)

� Energy efficiency measures identified:

� Steam generator: 5 % higher efficiency due to optimization of the parameters

� Steam distribution: losses reduced from 15 % to 10 % by isolating the tubes and closing the leakages

� Condensate: closed, pressurized return flow system

� Make-up water: pre-heating from 10 °C to 70 °C by exhaust gas-(condenser)

� Feed-water: heating from 102 °C to 135 °C due to cooling of the exhaust stream in the economizer

� Tunnel washer: pre-heating of washing water by heat recovery and by using the exhaust air and flash steam from the mangle

� Washing machine: pre-heating the washing water by heat recovery

� Dryer: energy consumption reduced due to direct gas firing

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Pinch AnalysisImpact (example)

� Energy efficiency measures identified

� Energy- and water distribution of reference-laundry with efficiency measures

� Thermal energy demand:

� 0,88 kWh/kg dry laundry

� 1.830 MWh/a

� Savings 2.360 MWh/a(-56 %)

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Pinch AnalysisImpact (example)

� Final status

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� Freeware

� Einstein

� Pinchleni

� Commercial Programmes

� Super Target

� PinCH

� Aspen Plus

Pinch AnalysisTools

[1]

[2]

[3]

[1] https://www.einstein-energy.net/

[2] https://pinch-analyse.ch

[3] https://www.aspentech.com/en/products/engineering/aspen-energy-analyzer-and-aspen-utilities

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Thank you for your Attention!

Fraunhofer Institute for Solar Energy Systems ISE

Fanny Hübner, M.Sc.

Pedro Horta, Ph.D.

www.ise.fraunhofer.de

fanny.huebner@ise.fraunhofer.de