GIS-Integrated Agent-Based Modeling of Residential Solar PV Diffusion
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GIS-Integrated Agent-Based Modeling of Residential Solar PV Diffusion. Scott A. Robinson, Matt Stringer, Varun Rai, & Abhishek Tondon. Energy Systems transformation. Motivation. Agent Based Modeling. -> Time. Agents:. Follow decision rules ( functions ) Have memory

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GIS-Integrated Agent-Based Modeling of Residential Solar PV Diffusion

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Gis integrated agent based modeling of residential solar pv diffusion

GIS-Integrated Agent-Based Modeling of Residential Solar PV Diffusion

Scott A. Robinson, Matt Stringer, Varun Rai, &

Abhishek Tondon

Energy Systems transformation


Gis integrated agent based modeling of residential solar pv diffusion

Motivation


Gis integrated agent based modeling of residential solar pv diffusion

Agent Based Modeling

-> Time

Agents:

Follow decision rules (functions)

Have memory

Perceive their environment

Areheterogeneous

Are autonomous

From: Deffuant, 2002.


Gis integrated agent based modeling of residential solar pv diffusion

Agent Attribute Example: Wealth

PV Adoption by Quartile

Average Income by Quartile


Gis integrated agent based modeling of residential solar pv diffusion

Agent Attribute: Wealth


Gis integrated agent based modeling of residential solar pv diffusion

Environment Example: Tree Cover

> 60% Tree cover

< 15% Tree cover


Gis integrated agent based modeling of residential solar pv diffusion

Agent Initialization: Small World Network of n% Locals, 1-n% Non-locals. Assign initial Attitude

Behavioral Model

No further activity

Are there PV owners in my network?

From: Watts, 1998.

ADOPT

Attitudebecomes socially informed: SIA

Modify SIA. Is SIA>= threshold?

RA: select one network connection. Is connection credible?

Financially capable? Wealth + NPV + PP (Control)

Yes

No


Gis integrated agent based modeling of residential solar pv diffusion

Implementation

Focus Test Site:

One zip code in Austin, TX

7692 households

146 PV Adopters (1.9%) as of Q2 2012City of Austin had approx. 1750 PV Adopters

Time Period:

Q1 2008 – Q2 2012

Methods:

Multiple runs in each batch to allow for inherent randomness in network initialization and interaction effects

Runs in a batch have identical parameters

Validation: Batches test different parameters against real test site data.


Gis integrated agent based modeling of residential solar pv diffusion

Temporal Validation

Empirical

Many strong interactions, radial neighborhoods, 90% local connections. Adopters are EOHs.

Weak interactions, contiguous neighborhoods

More non-local connections

Weak interactions

Few weak interactions, no EOHs


Gis integrated agent based modeling of residential solar pv diffusion

Spatial Validation


Gis integrated agent based modeling of residential solar pv diffusion

Current Work

-> Time

Agent Class: Installers


Gis integrated agent based modeling of residential solar pv diffusion

Summary

ABMs are virtual laboratories

PV diffusion is a complex process with rich interaction effects:

Agent behavior: theory of planned behavior

Agent networks: small world networks

Agent interaction: relative agreement algorithm

Multidimensional validation (space and time) allows the robustness of the ABM to be tested against “ground truth” events.

Early testing:

Strong, monthly interactions

90% geographic locals.

2000ft radial neighborhoods

Existing adopters with low uncertainty in attitude.

Low RMSE (3.6), and accurate clustering (1 false positive).


Gis integrated agent based modeling of residential solar pv diffusion

Q & A

Selected References:

Robinson, S.A., Stringer, M, Rai, V., Tondon, A., "GIS-Integrated Agent-Based Modeling of Residential Solar PV Diffusion,“ USAEE North America Conference Proceedings 2013, Anchorage, AK.

Rai, V. and Robinson, S. A. "Effective Information Channels for Reducing Costs of Environmentally-Friendly Technologies: Evidence from Residential PV Markets," Environmental Research Letters 8(1), 014044, 2013

Rai, V. and Sigrin, B. "Diffusion of Environmentally-friendly Energy Technologies: Buy vs. Lease Differences in Residential PV Markets," Environmental Research Letters , 8(1), 014022, 2013.

Rai, V., and McAndrews, K. “Decision-making and behavior change in residential adopters of solar PV,” World Renewable Energy Forum, 2012, Denver, CO.


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: TPB

Other options:

  • Theory of Reasoned Action

  • Rational Choice

  • Continuous opinions, discrete actions (CODA)

  • Consumat Framework

  • Stages of Change

  • …and many more


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: Relative Agreement Algorithm

From Deffuant et al. 2012.

Energy Systems transformation


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: Data Streams

AE Program Data

+ App. Status

+ Address

+ Date

+ System Specs

COA Parcel Data

+ Home value

+ Address

+ Land Use

+ Sq. footage

GIS of Parcels

+ Coordinates

+ DEM

+ Geometry

+ Tree cover

Financial Model

+ Cash flows

+ Discount Rates

UT Solar Survey

+ Sources of Info.

+ Decision-making

  • Agent:

  • Attitude

  • Uncertainty

  • Wealth

  • Home sq. footage

  • Age of home

  • Network

  • PP

  • Discount rate

  • Environment:

  • Tree Cover

  • Shade

  • Electricity Price


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: Model Design


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: Seasonal Effects


Gis integrated agent based modeling of residential solar pv diffusion

Appendix: Key Batch Parameters

Energy Systems transformation


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