Scenarios for the Smart Energy Region Zurich 2050 · PDF fileLife Quality very high Life Quality Stagnation Reduction of Life Quality ... 2050 for all stakeholders in the Canton Zurich

Zurich University of Applied Sciences, Switzerland zhaw-INE

a Institute of Sustainable Development, INE at ZHAW Zurich University of Applied Sciences, www.ine.zhaw.ch

Prof. Harry Spiess a [email protected], Vicente Carabias a, Diego Sanchez a

Devon Wemyss b.

1

Scenarios for the Smart Energy Region Zurich 2050

http://www.improntaunika.it/wp-content/uploads/2015/02/UE-nuovi-Strumenti-Finanziari-per-Progetti-sullEfficienza-Energetica.jpg, 2.6.2015

150602_Scen_SER_Zurich_2050_Spiess_V1

b Center for Innovation and Entrepreneurship, CIE, at ZHAW Zurich University of Applied Sciences, Switzerland

FFRC’s Futures ConferenceTurku, 11-12 June 2015

http://www.ine.zhaw.ch/

mailto:[email protected]


1. Background• Institute of Sustainable Development, INE-SoE-ZHAW• Swiss Energy Scenario 2050• Energy System: New Challenges• Research Project COST: Smart Energy Regions

2. Scenarios for the Smart Energy Region Zurich 2050• Research Questions • Methods• Results / Discussion• Conclusion / Outlook

Agenda


Institute of Sustainable DevelopmentINE-SoE-ZHAW

• «Context of Technology»

• Interdisciplinary Team25 Persons

aRTD / Services / Education / Further Training


Energy Consumption Switzerland: BackgroundSwiss Energy Scenario 2050

Oil

Heating and

Transport

ElectricityNuclear

New Renewables

FossileHydro

New Renewables

Biomass (Wood)

Gas

Scenario New Energy Policy, Var. C & E,

Reduction of CO2-Immission to 1 - 1,5 t by person and jear


Apart-

ment

Business

HH

Energy

Hub

Local

production

Large

Production

Virtual power

plantStorage

system

Consumers Prosumers Producers

OilGas

Source: Center for Innovation and Entrepreneurship, CIE, at ZHAW

Zurich University of Applied Sciences, Switzerland

Energy System: New Challenges


Research Project COST: Smart Energy Regions

Project COST Action TU1104 / SBFI-Research Project t C13.0147:

„Towards Smart Energy Regions:

Exploring Future Energy-Systems at Regional Level“

Coordination WP4 ‘Validation of steps towards a smart energy region’.

Development of Scenarios «Smart Energy Region Kanton Zurich, 2050»

Prof. Harry Spiess, Diego Sanchez, Institute of Sustainable Development, INE-SoE-ZHAW

COST: European Cooperation in Science and Technology

SBFI: The State Secretariat for Education, Research and Innovation

(Switzerland)

http://www.cost.eu/

http://www.cost.eu/

http://www.sbfi.admin.ch/index.html?lang=de

http://www.sbfi.admin.ch/index.html?lang=de


Research Project COST: Smart Energy Regions

Building Community City Region

Scale

HeatLoss

Demand Supply

Smart _ER: Smart Energy Regions

Case-Studies (stakeholders, foresight)

Case-Studies (end user, technologies)

8

http://www.smart-er.eu/

http://www.smart-er.eu/


Research Project COST Action TU1104: Smart Energy Regions

Work package

2013

II

2014

I

2014

II

2015

I

2015

II

2016

I

1 Project management & dissemination

2 Inventory of energy efficiency efforts, grid models and load profiles, demand and supply side management options, context factors and framework conditions

3 Horizon scanning for promising science & technology initiatives and solutions

4 Validation of steps towards a smart energy region comprising an integrated analysis and scenario development

5 Development of novel business model options, effective behaviour change programme elements, and recommendations

Milestones M1 M2 M3 M4, D M5, P


1. What Scenarios for a Smart Energy Region Canton Zurich, Time Horizon: 205o, are …• consistent?• plausible?• sustainable?• desirable?

2. How will a practicable Road Map towards the ‘Best Case’-scenario for a Smart Energy Region Canton Zurich, 2050 will look like?

3. How can the Methodological Approach of Formative Scenario Analysis be improved, especially for Foresight of Energy Systems?

Research Questions


Methodological Approach: ‘Scenario Trumpet’

[Bernath K. et al.(2012): BAFU Umweltszenarien 2050]


Methodological Approach: Formative Scenario Analysis, Overview

Step 1

Definition of Case and Objectives

Step 2: Brainstorming

and Definition of the

Impact Variables

Step 3

Impact Matrix

Step 6

Consistency Analysis

Step 4

System Grid and

System Graph

Step 7

Evaluation of

Consistency

Analysis

Step 5

Definition of the

Levels of the

Impact Variables

Step 8

Scenario

Selection

Step 9

Description of the

Scenario

Step 10

Validation of the

Scenario

Workshop b

Expert‘s-Workshop I

Expert‘s-Workshop II

System

Analysis

Scenario

creation

Workshop a


Methodological Approach: Formative Scenario Analysis, Impact Variables

MORPHOLOGICAL BOX

Population Development small Increase strong Increase

Level of Education high share of Tertiary

Education

medium share of Tertiary

Education

Life Quality very high Life Quality Stagnation Reduction of Life Quality

Life Style 80% with 2000 W Style 10% with 2000 W Style

Subsidies with Taxes and Subsidies with reduced Taxes and

Subsidies

no Subsidies

Global Policy safer than 2015 safer than 2015

Income (Economy) ongoing growth Stagnation

Energy Prices almost stagnation of Prices strongly rising Prices

Security of Supply stays good reduced

Grid Development europ. super Smart Grid regionale Micro-Grids

Energy Supply strongly decentralised stays centralised

Energy Efficiency High Energy Efficiency Low Energy Efficiency

Electricity Storage compensable diurnal and

annual Variations

simular to 2015

CO2 Emission minus 85 % minus 50 %

Catastrophy no extreme Catastrophies 1 extreme Catastrophy

Renewable Energy (RE) High Share of RE Small Share of RE


Results: System Picture, Overview


Results: System Picture, Detail and Loop Description

4 Life Style

6 Global Policy

3 Life Quality

5 Subventions

9 Energy Prices

8 Income

7 Liberalisaton Electricity Market

2 Level of

Education


Results: System Grid: Indirect Impacts

SER_ZH_V2 System Grid der indirekten Einflüsse, Ordnung 12 13.03.2015

System Grid der indirekten Einflüsse

Indirekte Passivität

Indirekte Aktivität

Aktiv

Passiv

Ambivalent

Puffernd

1 Bevölkerungsentwicklung

13 122 Bildungsstand

12 15

3 Lebensqualität

18 4

4 Lebensstil

7 5

5 Subventionen, Abgaben

3 6

6 Geopolitik

11 16

7 Strommarktliberalisierung

14 17

8 Einkommen

6 11

9 Energiekosten

4 2

10 Versorgungssicherheit

16 911 Kreislaufwirtschaft

15 14

12 Stromnetz-Entwicklung

8 1013 Dezentralisierung Energieversorgung

5 3

14 Energiesparen, Energie-Effizienz

10 8

15 Strom-Speicherung

1 7

16 CO2-Ausstoss & Anteil Erneuerbare

2 1

17 Siedlungsabfälle

17 13

18 Katastrophen

9 18

System-Reduction: Before the ConsystencyAnalysis we could reducethe amount of Impact Variables by omitting No.7, 11 and 17.

Active Ambivalent

PassiveBuffer


Methodological Approach: Formative Scenario Analysis

Step 6

Consistency Analysis

Expert‘s-Workshop I


Methodological Approach: Formative Scenario Analysis, Experts

EXPERTS

Location Suport Canton ZurichUniversity of Berne: Research Topic: Diffusion of environmentally friendly behavior

AWEL, authorities for energy services and policy, Canton ZurichEnergy Utility Company, Canton Zurich

IBM, CompanyCenter for Innovation & Entrepreneurship, ZHAW School of Management and Law

Swissgrid, Swiss national grid companySwisspower Renewables AG

Instiute of Energy Systems, ZHAW School of EngineeringKOFU, Authorities for environment protection, Canton Zurich

Students, ZHAW School of EngineeringImpact Variable

Population Developm. X X

Level of Education X

Life Quality X X X

Life Style X

subsidies X X

Global Policy X X X X

Income (Economy) X X X X

Energy Prices X X X X

Security of Supply X X X X

Grid Development X X X

Energy Supply X X X X X

Electricity Storage X X X X X

CO2 Emission X X X X X

Catastrophy X X X X

Renewable Energy (RE) X X X X X X X X


Methodological Approach: Formative Scenario Analysis, Consistency Analysis Matrix

Variable A Variable B etc.

Level

A1

Level

A2

Level

B1

Level

B2

Variable A Level A1

Level A2

Variable B Level B1 1 2

Level B2 1 -1

etc. 1 -1 0 1

-1 2 1 -1

Meaning Value

Inconsistency -1

Coexistency 0

Support 1

Precondition 2







Step 10

Validation of the

Scenario




Step 10

Validation of the

Scenario



Methodological Approach: Formative Scenario Validation of the Scenarios

Workshop II: Tasks for the Experts:

1. Which Scenario SER ZH-2050 is most…

• plausible?

• sustainable?

• probable?

• desirable? ( Target Scenario)

2. Identification of Elements for the Roadmap to the

Target Scenario.


Results: 3 Scenarios SER Zurich - 2050

Impact Factor / Characteristic Smart Growth Stagnation Survived Catastrophy

Population Development strong Increase small Increase small Increase

Level of Education high share of Tertiary Education high share of Tertiary Education high share of Tertiary Education

Life Quality very high Life Quality Stagnation Stagnation

Life Style 80% with 2000 W Style 80% with 2000 W Style 80% with 2000 W Style

subsidies with taxes and subsidies with taxes and subsidies with taxes and subsidies

Global Policy safer than 2015 unsafer than 2015 unsafer than 2015

Income (Economy) ongoing growth Stagnation Stagnation

Energy Prices strongly rising prices almost stagnation of prices strongly rising prices

Security of Supply stays good stays good stays good

Grid Development europ. super Smart Grid regionale Micro-Grids regionale Micro-Grids

Energy Supply strongly decentralised strongly decentralised strongly decentralised

Energy Efficiency High Energy Efficiency High Energy Efficiency High Energy Efficiency

Electricity Storagecompensable diurnal and annual variations

compensable diurnal and annual variations

compensable diurnal and annual variations

CO2 Emission minus 85 % minus 85 % minus 85 %

Catastrophy no extreme Catastrophies no extreme Catastrophies 1 extreme Catastrophy

Renewable Energy (RE) High Share of RE High Share RE High Share of RE


• Involvement of Experts (Workshops, Moderation)

• Potentials and limits of the Methodological Approach of Formative Scenario Analysis:

• Formative Scenario Analysis vs. Intuitive Scenario Approach

• Formative Scenario Analysis vs. Modelling

• Link form of Formative Scenario Analysis Approach to Backcastingand Road Mapping

Discussion (just started) and Research Gaps


RoadmapSmart Energy Region Canton Zurich-2050

To do:

Development of a practicable Road Map towards the ‘Best Case’-

scenario for a Smart Energy Region Canton Zurich.

• Pathway 2015 - 2050 for all stakeholders in the Canton

Zurich Region and in Switzerland.

• Technologies, Policies, Performance of Strategies and

Activities

• Wildcards, Reaction on Wildcards

http://de.slideshare.net/Presentationsat24point0/internal-product-road-map?related=4

(7.6.2015)

2050

SER

ZH

2015

ER

ZH


1. There exist plausible, sustainable and quite consistent Scenariosfor a Smart Energy Region Canton Zurich, Time Horizon: 205o.This evidence is based on the support of the knowledge of competent Experts in the fields of Technology, Economy, Sociology and Environmental Sciences.

2. Both, barriers and drivers, will emerge rather from the field of Economy and Policy than from new Technologies.

3. The Path from the Evidence of a Best Case Scenario towards a Road Map is a challenging Task.

4. The Formative Scenario Analysis proved to be a suitable Methodological Approach for Future Research of Energy Systems.

Conclusions


• Amt für Abfall, Wasser, Energie und Luft, Baudirektion, Kanton Zürich (2014): Vision Energie 2050, Über-prüfung 2014 (http://www.awel.zh.ch). (05.05.2015)

• Amt für Abfall, Wasser, Energie und Luft, Baudirektion, Kanton Zürich (2013): Energieplanungsbericht 2013, (http://www.awel.zh.ch). (28.05.2015)

• COST Action TU1104 "Smart Energy Regions": http://www.cost.eu/domains_actions/tud/Actions/TU1104 (30.4.2014)

• European Commission (2012). Energy Strategy for Europe. Brussels, European Commission DG Energy.

• European Commission (2011). Energy Roadmap 2050. COM(2011) 885/2. Brussels, European Commission.

• Kreibich, R., B. Oertel, et al. (2011). Futures Studies and Future-oriented Technology Analysis Principles, Methodology andResearch Questions. Paper presented at the 1st Berlin Symposium on Internet and Society.

• Kosow Hannah, Gassner Robert (2008): Methoden der Zukunfts- und Szenarioanalyse, WerkstattBericht Nr. 103. Kurzscript, Institute for Futures Studies and Technology Assessment, IZT Berlin.

• Schneidewind, U. and H. Scheck (2012). Zur Transformationsforschung des Energiesektors - ein Blick aus der Perspektive der Transition-Forschung. Smart Energy: Wandel zu einem nachhaltigen Energiesystem. H.-G. Servatius, U. Schneidewind and D. Rohlfing. Heidelberg, Springer.

• Scholz, R. W. & Tietje, O. (2002). Embedded Case Study Methods: Integrating Quantitative and Qualitative Knowledge. Thousand Oaks: Sage.

• Swiss Federal Council (2011). Energy Perspectives 2050. Federal Council, Berne.

• Wilhelmer, Doris; Nagel Reinhart (2013): Foresight-Managementhandbuch: Das Gestalten von Open Innovation. Carl Auer, Heidelberg.

• World Energy Council, Paul Scherrer Institute (2013): Composing energy futures to 2050. www.worldenergy.org/publications /2013/world-energy-scenarios-composing-energy-futures-to-2050 (10.1.2014)

References


Thank you

11. 06. 2015Prof. Harry Spiess

[email protected]

Institute of Sustainable Development at ZHAW Zurich University of Applied Sciences, www.ine.zhaw.ch

EcoGrid EU, 2012

mailto:[email protected]

http://www.ine.zhaw.ch/

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Scenarios for the Smart Energy Region Zurich 2050 · PDF fileLife Quality very high Life Quality Stagnation Reduction of Life Quality ... 2050 for all stakeholders in the Canton Zurich