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Managing Complexity MUSCos Co-Is meeting WP3 modeling update Dr Liz Varga [email protected] M. Robinson, P. M. Allen 15 th Sep 2014 Leeds University

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Page 1: Managing Complexity - SuRe-Infrastructuresure-infrastructure.leeds.ac.uk/muscos/wp-content/... · Managing Complexity MUSCos Co-Is meeting WP3 modeling update Dr Liz Varga liz.varga@cranfield.ac.uk

Managing Complexity MUSCos Co-Is meeting WP3 modeling update

Dr Liz Varga [email protected] M. Robinson, P. M. Allen 15th Sep 2014 Leeds University

Page 2: Managing Complexity - SuRe-Infrastructuresure-infrastructure.leeds.ac.uk/muscos/wp-content/... · Managing Complexity MUSCos Co-Is meeting WP3 modeling update Dr Liz Varga liz.varga@cranfield.ac.uk

Research Question: WP3

§  What assumptions in take-up of Musco-like contracts would lead to a transition towards more resource-efficient, service-oriented utility provision? § Market assumptions: inertia, energy costs, … § Company parameters: staffing, business

strategy,..

© Cranfield University 2013 2

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Research objective: WP3

§  The objective in our modeling is to show the comparative speed at which it would take for MUSCOs to invade the market using different incentives. The output of our modeling is the extent to which UK homes are resource efficient, and we show this in 10 centile categories. § Our model includes traditional energy providers,

and two types of energy service providers

© Cranfield University 2013 3

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Firms take Measures & Interventions §  Assumptions:

§ Muscos contracts create lock-in in return for economically attractive reduction in service costs

§  Muscos exploit: §  Technologies (e.g. in house grey water reuse) § Operation modes (e.g. car sharing) §  Policies (e.g. relaxation of water price control)

© Cranfield University 2013 4

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Scale

§  Temporal scale will be the shortest time which matters (1 quarter for traditional contracts, or 1 year for performance evaluation)

§  Spatial resolution/distribution will be artificial but calibrated to observed housing population: 27 million homes

© Cranfield University 2013 5

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Phased approach to development §  Phase 1: traditional utility companies / existing

cases §  Phase 2: evolutionary systems dynamics model,

including: §  two types of Muscos §  Analysis of profits for energy company

§  Phase 3: agent based model, additionally with: §  Household tracking §  Company tracking

© Cranfield University 2013 6

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Phase 2: 40 years ahead

© Cranfield University 2013 7

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Phase 2: Company profits

© Cranfield University 2013 8

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Phase 3: Attributes of Household Agents: §  Energy efficiency rating §  Contract status: “on” or “off” market §  Active or Inert §  Current energy provider §  Finance

§ Upgrades paid upfront § Upgrades spread over contract period

© Cranfield University 2013 9

0 0.2 0.4 0.6 0.8 10

20

40

60

80

100

Total Musco Market Share

% In

ert

I0=40%

I0=60%

I0=80%

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Market Dynamics §  Marketing

§  Contact customers - sales staff efficiency §  Sales

§  Internal: current customers upgrade §  External: new customers

§  Resizing §  Sales staff adjusted for available customers §  Service staff adjusted for current customers

§  Inertia §  As MUSCos gain customers, more households willing to

switch §  Construction

© Cranfield University 2013 10

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Market Share Captured

© Cranfield University 2013 11

§  Business models: §  MUSCo A: 5 year contract §  MUSCo B: 10 year contract

§  Cost of upgrade with MUSCo repaid over contract period

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Efficiency Distributions

§  Traditional customers hesitant of larger upgrades due to self-financing

© Cranfield University 2013 12

(40 years)

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Customer Retention

§  Majority of households change provider once or twice in 40 years

§  Many households remain with provider after contract expiration

© Cranfield University 2013 13

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Sensitivity to Market

§  Initial inert household population influential

© Cranfield University 2013 14

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Sensitivity to Business Model §  Aggressive sales strategy optimal §  Traditional provider remains competitive

© Cranfield University 2013 15

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Academic Papers

§  Agent based modeling of energy networks. §  Gonzalez de Durana JM, Barambones O, Kremers E, Varga

L (2014) , Energy Conversion and Management, 82 () 308-319. §  A framework for targeting household energy savings through

habitual behavioural change. §  Pothitou, M, Kolios, AJ, Varga, L, Gu, S. (2014): §  International Journal of Sustainable Energy, DOI:

§  A Simple Model to Explore the Growth of Multi-Utility Service Companies §  L.Varga, M.Robinson and P.M.Allen §  Target: Futures

§  An agent-based model for Multi-Utility Service Companies §  M. Robinson, L. Varga, P. Allen §  Target: Applied Energy

© Cranfield University 2013 16

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Conference Papers

§  ITRC – Cambridge March 2014 §  Infrastructure, Growth and Sustainable Living

§ L Varga

§  ISNGI – Vienna Sep 2014 §  Adaptation and resilience of interdependent

infrastructure systems: a complex systems perspective § L Varga, J Harris

© Cranfield University 2013 17

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Conferences attended

§  Policy and practice in complex systems, Welcome Trust, Feb 2014

§  Complex Models for Real World Policy, Royal Society, Apr 2014

© Cranfield University 2013 18

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Practice engagements

§  Fred Roche Foundation, Milton Keynes, July 2014 §  Low carbon liveable cities: A complex systems

perspective §  Invited speaker and panelist

© Cranfield University 2013 19

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Budget

§  Will be spent by end Nov 2014 §  Staff:

§  T Grubic and S Varga finished Sep 2013 §  P Allen finished 31 July 2014 § M Robinson finishes 30 Sep 2014

© Cranfield University 2013 20

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Managing Complexity MUSCos Co-Is meeting WP3 modeling update Thank you