Novel method for the determination of unknown biomass fuel properties based on results of an online monitoring in a 300 kW CFB pilot plant Daniel Bernhardt, Michael Beckmann

8th International Freiberg Conference, 12-16 June 2016, Cologne, Germany

Faculty of Mechanical Science and Engineering,

Institute of Process Engineering and Environmental Technology, Chair for Energy Process Engineering

Slide 1

Motivation – Increasing Fuel Flexibility in biomass energy use

Fuel range

- Small amounts (<10.000 t/a) - Different sources Variable fuel properties

Varying Flue gas emissions

Deposits/Corrosion vs. Availability/Costs

Source: Frandsen, 2011

Challenges

Flexible Biomass utilization needs biomass specific process optimization

Power Plants

- Design and operation is optimized on „regular fuel“

Source: BEB Bioenergie Baden

Slide 2

Model-based process control

New targets for control variables

Fuel (C,H,O,N,S)

?

Fuel, Air, Additives

Control Variables

Identification of unknown fuel properties

Power Plant (e. g. CFBC)

Source: BEB Bioenergie Baden

Process data acquisition

Monitoring (Sensors + Models)

Process analysis (Online-Balancing)

Prediction & Optimization

0 10 20 30 40 50 60

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

Massenverteilung des Rezimaterials

Cellulose [wt.-% daf] Cellulose [wt.-% daf]

Slide 3

Characterization of the feedstock material – Organic composition of natural biomass

Hem

icel

lulo

se [w

t.-%

daf

]

Lign

in [w

t.-%

daf

]

Extr

activ

es [w

t.-%

daf

] - Cellulose, Hemicellulose & Lignin are main components (Σ = 92 wt.-% daf) - Distribution varies in wide range - No similarities within biomass groups - Linear correlation between Hemicellulose & Cellulose

Cellulose [wt.-% daf]

Slide 4

Characterization of the feedstock material – Fuel Properties of Organic material

Slide 5

Identification of Unknown Fuel Properties – Exemplary for 300 kWth CFB pilot plant

Energy-Balance

Slide 6

Identification of Unknown Fuel Properties – Online - Balancing

Elemental-Mass-Balances Assumptions: ξFuel,N = ξFuel,S = 0

ξC, ξH, ξO, ξH2O

& hu

Additional Statistic

ξC, ξH, ξO, ξH2O

Slide 7

Identification of Unknown Fuel Properties – Results Online-Balancing (C, H, O, H2O)

Slide 8

Identification of Unknown Fuel Properties – Structural Analysis

Elemental composition and heating value of structural components

i…C, H, O, N, S j…Structural component

Slide 9

Identification of Unknown Fuel Properties – Structural Analysis - Mathematics

Objective function

Constraints

Slide 10

Identification of Unknown Fuel Properties – Results of Structural Analysis

Slide 11

Identification of Unknown Fuel Properties – Results of Structural Analysis

Summary

- Presented method provides “Online” information about unknown fuel properties of biomasses:

- Online Balancing: ξC, ξH, ξO, ξH2O and hu

- Structural analysis: ξCel, ξHCel, ξLig, ξExtr and ξN, ξS

- Validation was realized for three biomasses with different compositions

- Method exemplarily developed for CFB combustion of biomass is transferable to other firing systems (e. g. grate systems)

- Deeper information about extractive composition would improve the accuracy of the method

Slide 12

Further work – novel process model for CFB combustion of biomass

Slide 13

Process data -fuel (structural composition!) - reaction gas - temperature and pressure

Forecast: - burn out - emissions and Process optimization - air distribution - air preheating - additives

Simplified process model based on structural composition

Acknowledgement

Slide 14

Thank You for Your Interest! (Riverfront of Dresden )

»Knowledge Builds Bridges«