Fairness and cooperation in energy use The wisdom of sustainable communities in the digital era: the case of efficient energy management Alessandro Tavoni Luigi Telesca

The wisdom of sustainable communities in the digital era: the case of efficient energy management

Outline Motivation A Model of Equity-driven Cooperation in Energy Management Two Cases of Agent Interactions (Monitoring) Outlook

Motivation

A Model of Equity-driven Cooperation in Energy Management

Two Cases of Agent Interactions (Monitoring)

Outlook

The commons dilemma “ Tragedy of the Commons” (Hardin, Science, 1968) Individual Gain Shared Disadvantage “ Mutually agreed upon coercion” sustainable resource management only possible with regulation from agency or privatization But … based on restrictive assumptions open access unmanaged (no norms, no institutions) no communication all individuals are selfish, maximize short term returns

“ Tragedy of the Commons” (Hardin, Science, 1968)

Individual Gain Shared Disadvantage

“ Mutually agreed upon coercion”

sustainable resource management only possible with regulation from agency or privatization

But … based on restrictive assumptions

open access

unmanaged (no norms, no institutions)

no communication

all individuals are selfish, maximize short term returns

Avoiding the dilemma – managing the Commons Self-organization of users to develop norms and institutions, to design sanctions, etc. (Ostrom, 1990) to establish and maintain cooperation, i.e. individual restraint from short-sighted resource overexploitation Dependent on characteristics of the resource system and the user community Pictures from http://www.lobsterfrommaine.com

Self-organization of users to develop norms and institutions, to design sanctions, etc. (Ostrom, 1990)

to establish and maintain cooperation, i.e. individual restraint from short-sighted resource overexploitation

Dependent on characteristics of the resource system and the user community

Resource Dynamics - Adaptation Mostly static view on resources in the cooperation literature Resource dynamics -> feedbacks to human behavior Examples: Over time community members have reached an understanding as to what effort level will permit a reasonable exploitation of the resource -> what if the resource dynamics suddenly change? Resource & institutional uncertainty leads to opportunistic behavior such as over-harvesting (field observations) High risk of loss can promote cooperation (Milinski et al. 2008)

Mostly static view on resources in the cooperation literature

Resource dynamics -> feedbacks to human behavior

Examples:

Over time community members have reached an understanding as to what effort level will permit a reasonable exploitation of the resource -> what if the resource dynamics suddenly change?

Resource & institutional uncertainty leads to opportunistic behavior such as over-harvesting (field observations)

High risk of loss can promote cooperation (Milinski et al. 2008)

Factors of success in resource management (after Pretty 2003, Ostrom 2007 and Ostrom, forthcoming) Resource System Social System Clarity of system boundaries Number of users Size of resource system Norms, Rules, Social Capital (incentives/sanction) Resource unit mobility Relations of trust Productivity Connectedness in networks and groups Storage capacity Resource Dynamics/ Predictability

Pro-Social Behavior / Fairness Norms Evidence from experimental economics on deviations from solely self-interested behavior (except for in highly competitive environments) "prosocial" value orientations (other-regarding preferences) e.g. subjects resist inequitable outcomes (Fehr & Schmidt 1999, Goeree & Holt 2004) e.g. the group ostracizes norm violators (Bowles & Gintis 2004) Evidence from field research (e.g. Ostrom 2007) Evidence from a case study on local water management in Uzbekistan

Evidence from experimental economics on deviations from solely self-interested behavior (except for in highly competitive environments)

"prosocial" value orientations (other-regarding preferences)

e.g. subjects resist inequitable outcomes (Fehr & Schmidt 1999, Goeree & Holt 2004)

e.g. the group ostracizes norm violators (Bowles & Gintis 2004)

Evidence from field research (e.g. Ostrom 2007)

Evidence from a case study on local water management in Uzbekistan

Our Aim bring together insights from research on the evolution of cooperation and commons management , i.e. integrating resource dynamics with social (replicator) dynamics Enforcement of norms (Sethi and Somanathan, AER 1996) Social capital (Oses-Eraso & Viladrich-Grau, JEEM 2007) Under which conditions can pro-social, equity-driven behavior lead to establishment of cooperation in a CPR? How can cooperation evolve and be maintained when social and resource conditions change ?

bring together insights from research on the evolution of cooperation and commons management , i.e. integrating resource dynamics with social (replicator) dynamics

Enforcement of norms (Sethi and Somanathan, AER 1996)

Social capital (Oses-Eraso & Viladrich-Grau, JEEM 2007)

Research Background Resources Sustainability is key in the future of the network society ENERGY Today, household consumers perceive electricity as a commodity which can be consumed at will and in unbounded quantity. Why? Poor Feedback (monthly or bi-monthly bill) based on poor estimates -> Now intelligent meters will provide more details but not better system Complex pricing model Effect of individual behaviour is lost! Individual monitoring solutions, if not linked with community profiling, local data conditions and energy production information, will have a limited impact due to lack of visibility and understanding on the user part.

Resources Sustainability is key in the future of the network society

ENERGY

Today, household consumers perceive electricity as a commodity which can be consumed at will and in unbounded quantity.

Why?

Poor Feedback (monthly or bi-monthly bill) based on poor estimates -> Now intelligent meters will provide more details but not better system

Complex pricing model

Effect of individual behaviour is lost!

Individual monitoring solutions, if not linked with community profiling, local data conditions and energy production information, will have a limited impact due to lack of visibility and understanding on the user part.

Energy Aware Paradigms The facts: Energy demand: Fossil production peak close, rapidly increasing demand from emerging countries Climate change: EU must reduce by 8% its CO2 emission by 2012 for first Kyoto protocol phase European Vision of Future Power Network: An order of magnitude more many energy sources (RES) Demand reduction through monitoring, management and local optimization (cogeneration, real-time suply-demand matching) => made possible by ICT (Smart Power Networks) Open problems: Controling the network: bi-directional and stocastic flows, real time production adaptation, complex optimization Speeding up its growth: variety of actors, disparate interest, which policy?

The facts:

Energy demand: Fossil production peak close, rapidly increasing demand from emerging countries

Climate change: EU must reduce by 8% its CO2 emission by 2012 for first Kyoto protocol phase

European Vision of Future Power Network:

An order of magnitude more many energy sources (RES)

Demand reduction through monitoring, management and local optimization (cogeneration, real-time suply-demand matching)

=> made possible by ICT (Smart Power Networks)

Open problems:

Controling the network: bi-directional and stocastic flows, real time production adaptation, complex optimization

Speeding up its growth: variety of actors, disparate interest, which policy?

A visionary approach Advocating a web 2.0 approach: Policies will be too slow An open energy playground would speed-up innovation (see Internet) Future Energy Grid is a complex system We research ICT solutions for such systems: Networks for massively distributed (pervasive) systems Improving CS predictability through distributed control Real-time distributed resource negociation to achieve global optimization Designing large scale simulation and emulation environment

Advocating a web 2.0 approach:

Policies will be too slow

An open energy playground would speed-up innovation (see Internet)

Future Energy Grid is a complex system

We research ICT solutions for such systems:

Networks for massively distributed (pervasive) systems

Improving CS predictability through distributed control

Real-time distributed resource negociation to achieve global optimization

Designing large scale simulation and emulation environment

Assumptions We want to endow communities with a multi-layered technological framework Innovative P2P infrastructure Linked with smart metering systems allowing an open, distributed monitoring and control plan for local energy grids. These, in turn, enable community-level organization of users and new services and business models. Such a bottom-up radical reform of the energy system develop and survive in a world divided between socially-inclined individuals as well as selfish ones?

We want to endow communities with a multi-layered technological framework

Innovative P2P infrastructure

Linked with smart metering systems allowing an open, distributed monitoring and control plan for local energy grids.

These, in turn, enable community-level organization of users and new services and business models.

Such a bottom-up radical reform of the energy system develop and survive in a world divided between socially-inclined individuals as well as selfish ones?

The Model - Environmental Settings Common pool resource such as a groundwater reservoir cooperative agent extracts at socially acceptable level non-cooperative above socially acceptable level two types of resource users: cooperators defectors

cooperative agent extracts at socially acceptable level non-cooperative above socially acceptable level

two types of resource users:

Extraction Levels Adapted from Sethi & Somanathan 1996 Efficient Total Effort Level Static Nash Total Effort Level Total Costs of Effort Total Production <

Equity – driven Cooperation Payoff: Utility: Net Average Product “ equity” Proportion cooperators Community benefit fn Excludable cooperation benefits

Interactions of resource users Note: payoffs are dependent on effort and state of resource Case 1 Perfect Monitoring Case 2 Local Monitoring C D C D C D C D

Population evolution / Learning Replicator Dynamics (evolutionary game theory): imitate successful behavior For case 1: Agents update their strategy with probability equal to utility difference

Replicator Dynamics (evolutionary game theory): imitate successful behavior

For case 1:

Agents update their strategy with probability equal to utility difference

Perfect Monitoring (Case 1A) Utility of prosumer : Cooperation if UC>UD Coexistence if UC=UD

Utility of prosumer :

Cooperation if UC>UD

Coexistence if UC=UD

Perfect Monitoring (Case 1B) Utility of prosumers Cooperation if UC>UD Coexistence for intensity

Utility of prosumers

Cooperation if UC>UD

Coexistence for

Local Monitoring (Case 2) If defector meets another defector they still get the community help (they disguise themselves as prosumers) C D C D

If defector meets another defector they still get the community help (they disguise themselves as prosumers)

Summary of results Defectors are always identified (Case 1A) -> all cooperator equilibrium when rewards > payoff difference (gains of defection) Cooperation among prosumers dependent on the intensity of defection (Case 1B) -> coexistence when effort differences are large With small differences results are same as Case 1A. Defectors can free-ride on prosumer’s cooperation (Case 2) -> bistability when rewards ~ payoff difference otherwise Case 1A Fairness norm can promote sustainable energy management if proportion of norm followers is large enough & monitoring is sufficient norm violations are not excessive

Defectors are always identified (Case 1A) -> all cooperator equilibrium when rewards > payoff difference (gains of defection)

Cooperation among prosumers dependent on the intensity of defection (Case 1B) -> coexistence when effort differences are large With small differences results are same as Case 1A.

Defectors can free-ride on prosumer’s cooperation (Case 2) -> bistability when rewards ~ payoff difference otherwise Case 1A

Fairness norm can promote sustainable energy management if

proportion of norm followers is large enough & monitoring is sufficient

norm violations are not excessive

Outlook Analytic treatment (coexistence & identity matters) Interaction of agents through social networks Impact of shocks in resource dynamics (stability of cooperation) Simulate agents that learn to adjust the extraction level to new resource conditions Uncertainty

Analytic treatment (coexistence & identity matters)

Interaction of agents through social networks

Impact of shocks in resource dynamics (stability of cooperation)

Simulate agents that learn to adjust the extraction level to new resource conditions

Uncertainty

Acknowledgements The Levin Lab and Princeton Environmental Institute Princeton’s Ecology and Evolutionary Biology department Advanced School of Economics in Venice CREATE-NET

The Levin Lab and Princeton Environmental Institute

Princeton’s Ecology and Evolutionary Biology department

Advanced School of Economics in Venice

CREATE-NET