high-quality recycling lcm21

Michael SteinfeldtSenior Scientist

University of Bremen

Speakers

08 September 2021

Tobias BrinkmannManaging Partner

brands & values GmbH

HIGH-QUALITY RECYCLING through self-learning and resilient Recycling Network using a combination of Agent-Based Modelling and Life-Cycle Assessment

OBJECTIVES OF THE PROJECTConception of a recycling network, self-learning and resilient, for the sustainable control of the material flows of wind energy plants using the example of rotor blades.

Independent definition of standards within the network on the basis of previously agreed principles.

Robust, i.e. secure approach to high-quality recycling even when framework conditions change (circular economy).

1Self-learning

2Resilient

BACKGROUND Forecast EoL situation in Germany

Assumptions

Source: own database IEkrW on all WTGs installed by 31.12.2020 with material-specific allocations

All other power classes decommissioning/ repowering after expiry of EEG support (20 years)

Plants with outputs <1MW with 36% second life; 1 to 2MW at 9% second life

With <1MW repowering 60% after 15 years; 1 to 2MW repowering 10% after 15 years; end after 25 years

20402038203620342032203020282026

Mas

s (M

g)

Year202420222020201820162014

0

10.000

20.000

30.000

40.000

50.000

60.000

70.000

80.000 1.001 - 2.000 kW2.001 - 3.000 kWfrom 3.001 kWannual total

PROJECT PARTNERS

Supported by

Funded by

Identification of relevant actors

Relevant actors in the process chains

Tasks, influence, responsibilities, interactions of the actors

Options for action

Inventory of recycling system

Quantitative data of components and materials

Decommissioning, recycling technologies

Material qualities and quantities

Material flow models of the process chains

BPMN = Business Process Model and Notation

Development of a central database; Sankey diagrams

1 2

APPROACH AND RESULTS

Main workpackages

*With representatives of all members of the value chain, R&D, public authorities.

Definition of indicators & terms

Recyclability, Circularity

High quality recycling

Recycling rate, secondary material rate

Recovery rate

Concept of recycling network

Designed as a quality association*

Setting objectives

Setting standards with regular evaluations

Control in the planned recycling networkSelf-learning and resilient

3 4


Main workpackages

Tool 5Agent-based modelling (ABM) (Netlogo)

Tool 4Business process modelling (BPMN)

Tool 2Library process data sheets

Tool 3Material & energy flow modelling, LCA (eSankey, Gabi)

Tool 1Database wind turbines (excel)

Evaluation criteria

recyclability

Dismantling processes and

recycling technologies

Database expansion

and update

Development ABM and simulation

Further development of business process

model

Concepts for the quality association and supporting services

RecycleWind 1.0 RecycleWind 2.0

Software-linkingAkteur 1

Akteur 2

Akteur 3Software-linking

Software-linking

Software-linking

Current work for RecycleWind 2.0


TOOL 1-3

WTG

GRP Rotor BladesGRP/CFRP Rotor Blades

Rotor Blades for RecyclingShredded Rotor Blade

Rejects MixtureSecond Life

CFRP MatrixChip Waste

Metal ScrapReject Material


TOOL 1: DATABASE WIND TURBINES (EXCEL)

Forecast WEA onshore 2036

37.196 Mg

21.876 Mg

GPR Rotor BladesGRP/CFRP Rotor Blades

TOOL 1-3

WTG

Dismanteling (C1)

Dismanteling MaterialRecycling

Pyrolysis

Pre-Treatment Scrap / Delamination / Fe-Separator

Waste recycling (C3)

Pre-treatmentGRP


TOOL 2: LIBRARY PROCESS DATA SHEETS (EXCEL)


37.196 Mg

21.876 Mg







TOOL 1-3

WTG

Dismanteling (C1)

Dismanteling

Second Life

424 Mg

37.196 Mg

2.574 Mg

52.952 Mg

1.737 Mg

105.903 Mg

52.952 Mg

21.876 Mg

3.960

Mg

586 Mg

MaterialRecycling

Pyrolysis

54.102 Mg Pre-Treatment Scrap /

Delamination / Fe-Separator

Recycled Carbon Fibres

Bypass Waste-to-Energy Plant

Waste recycling (C3)

GWP

Disposal (C4)

CementPlant

MetalRecycling

Rejects fromPaper Industry

Pre-treatmentGRP


TOOL 2: LIBRARY PROCESS DATA SHEETS (EXCEL)

TOOL 3: MATERIAL AND ENERGY FLOW MODELLING, LCA (ESANKEY, GABI) Actual status: prediction on basis of

current situation/technology available








The picture shows the actors as a parallel, layered structure. This depicts the behaviour among the actors so far: Everyone for themselves.

TOOL 4 BPMN for Process Analysis

Authority

Rotor blade manufacturer

Wind farm operator

Dismanteling company

RecyclerCFRP

GFRP

Agent-based modeling expands the spectrum for the simulation of socio-technical systems in particular, since interactions between different actors are examined quantitatively from a bottom-up perspective.

In simulation models, agent relationships and interactions are depicted in a simplified way by assigning individual options for action to the agents.

Potential developments of individual system components and also of the overall system can be calculated under defined conditions. The results should ultimately show how a system adapts to new framework conditions and how it reacts to changes (resilience).

Project procedure

TOOL 5 Agent-Based Modelling

Analysis of the push and pull influencing factors that affect the recycling network system, based

on the system structure of the turtle model

Adaptation into a model concept with active actor groups (agents) and system elements

(objects)

Development of the model in the ABM software NetLogo

Carrying out the simulations and adapting the model

TOOL 5 Schematic structure of the Agend-Based Model, based on the system structure of the

turtle model

State

Push Factors

PullFactors

WEA-Operator

Influencing decisions

Regulation of demand

Influencing demand and willingness to pay

Influence on demand

Influence on demand

Improvement Sale

Load & Unload

Load & Unload

Demand Yes / No

Demand Yes / No

Sale

Suport / Scandalisation

System Interaction

Agent Interaction

Civil Society

Technology Development

Prices of Substitutes

Industry

End-of-Life (EoL)

Recycling network Operating costs Investment costs

Technology (GRP, CFRP) Recycling products

TOOL 5

Object Agent

Manufacturer (group)

Operator(group)

Customer(group)

Recycler(group)

BusinessCase

RecyclingTechnology

TechnologyType

Pre-Treater

Dismanteling

Subsidizer

Model concept with active actor groups (agents) and system elements (objects)

communicatesneeds andinformation

communicates demand to

communicatesinformation

communicatesdemand to

defines / calculates

cansponsor

enables various options for

partly promoted by

specifiescharacteristics of

satisfies demand

communicatesdemand to

leads to investment in und installation of

CO2 prices

Prices of substitutes

Regulation mechanisms

Enviroment

Installedcapacity

Recyclingrate/quality

Totalproduction

TOOL 5 Screenshot of the current network in NetLogo

Producer

Operator

Recycler

Costumers

SUPPORTING TOOLKIT for a resilient recycling network

1 2

TOOL 1

Inventory WTGs

Invventory EoL Processe

s

MEFA, LCA

BPMN

ABM

TOOL 2

TOOL 3TOOL 5

TOOL 4

WTG inventory databaseLocationManufacturerOperatorTurbine typeForecast type and quantity of materials used

Agend based modelling (ABM)Simulation of the annual development of EoL & Recycling routes for rotorblades based on the MEFA, relevant actors and additional external influences.

Busisness process modell (BPMN)Model of the process chain with the key actors along the entire product life cycle with tasks, influences, responsibilities, interactions of the actors and options for action.

Material & Energy Flow Analysis (MEFA), Life Cycle Assessment (LCA):

Visualization (Overview) of EoL Routes for different szenarios and predictionsCalculation of potential ecological impacts, for example GWPBenchmark of the existing technological End of Life processes

Process database:Involved processes of the EoL technology routes and recycling options.Information on mass balances and energy consumption of the individual processes from practice.

Hub heightRotor diameterEtc.

BENEFITS for the self-learning and resilient recycling network

The various technical, ecological and socio-economic tools and their interaction increase the network actors' overall understanding of the interrelationships in recycling and promote acceptance of the goal of high-quality recycling of wind turbines (esp. rotor blades).

All important influencing factors / parameters (eco-performance, fluctuations in demand, willingness to pay, innovation capacity, technological developments) can be dynamically analysed and simulated in the network model, when framework conditions change (circular economy).

Mapping of the options for action and their effects, taking into account the interests of all relevant actors in relation to the target formulation of the recycling network is facilitated.

New solution spaces and ideas for innovations are made possible, which provide impetus for further optimisation of the self-learning and resilient recycling network.

CONTACT

Tobias BrinkmannPhone: +49 157 [email protected]

brands & values GmbHAltenwall 14D-28195 Bremen

University of Bremen

Michael SteinfeldtPhone: +49 421 218 [email protected]

All the strategies, models, concepts, ideas, calculations and conclusions incorporated into this documentation are the exclusive intellectual property (except sources are referenced) of brands & values GmbH and are protected under copyright. They have been turned over to the client exclusively for his own use for an unspecified period. All information included in them is to be kept confidential and is intended for the client’s eyes only. The client is not permitted to change this documentation, make it public outside his own company or disseminate it in any way. This rule may only be amended or revoked with the express written consent of brands & values GmbH. Verbal agreements shall not be deemed valid.

high-quality recycling lcm21

Documents