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Development of a Decision Aiding Framework For Energy Infrastructure Siting. Ganesh Doluweera & Joule Bergerson Institute for Sustainable Energy, Environment and Economy, University of Calgary. 32 nd USAEE/IAEE North American Energy Economics Conference July 30, 2013. Motivation.

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development of a decision aiding framework for energy infrastructure siting

Development of a Decision Aiding Framework For Energy Infrastructure Siting

Ganesh Doluweera & Joule Bergerson

Institute for Sustainable Energy, Environment and Economy, University of Calgary

32nd USAEE/IAEE North American Energy Economics Conference

July 30, 2013

motivation
Motivation
  • Demand for new energy infrastructure is growing
    • rising energy demand, ageing infrastructure and environmental concerns
  • Siting energy infrastructure is a complex process that involves multiple stakeholders with multiple and conflicting objectives
  • In recent years, siting energy infrastructure has become increasingly difficult
    • one reason is oversimplification of stakeholder complexities
research objective
Research Objective
  • Develop a framework to construct alternative siting options
  • This framework has more complete incorporation of stakeholder objectives
  • Developed by combining energy system modeling with decision analysis techniques
proposed framework
Proposed Framework

Consequence tables

Preference structure and rankings

case study
Case Study
  • Selection of a route for an electricity transmission line in Alberta, Canada
  • Decision makers’ objective: Select the transmission line route that is in public’s best interest

Focus on an approximately 100km section of EATL

(Andrew-Holden section)

Eastern Alberta Transmission Line (EATL)

(500kV HVDC; ̴ 500km)

methods stakeholder objectives
Methods: Stakeholder Objectives
  • Minimize Residential and property value impacts
    • Minimize the proximity to residential properties
    • Avoid densely populated areas (Urban areas)
  • Minimize Environmental impacts
    • Minimize river and water body crossings
    • Minimize proximity to environmentally sensitive areas
    • Avoid highly sensitive ecosystems
  • Optimize economic and engineering factors
    • Parallel existing linear disturbances (roads, power lines)
    • Minimize cropland disturbances
    • Minimize building on high slopes (terrain features)
    • Minimize cost
methods system model
Methods: System Model

[1,2]

  • Stakeholder objectives (ie. xi) and preferences (ie. Vi(∙) and wj) are inferred using transcripts of EATL regulatory hearings

References:

Gregory R, Failing L, Harstone M, Long G, McDaniels T, Ohlson D. Structured Decision Making: A Practical Guide to Environmental Management Choices. Chichester, UK: Wiley-Blackwell; 2012.

Keeney RL. Utility Functions for Multiattributed Consequences. Management Science. 1972; 18:276-87.

methods system model1
Methods: System Model
  • A geographic information system (GIS) model
  • In each cell, magnitude of the combined value function is calculated
  • Using least cost path selection algorithms, combination of cells that forms the least cost path is identified
slide11

Area of interest and routes and routes proposed by the project proponent (ATCO Electric)

  • An alternative segment has been proposed by a land owner group
slide12

Alternative route option 1

All high level objectives are weighted equally

(W_res = W_env = W_eng)

slide13

Alternative route option 2

Preference for minimizing residential impacts is twice as that of other high level objectives

(W_res = 2W_env = 2W_eng)

slide14

Alternative route option 3

Preference for minimizing environmental impacts is twice as that of other high level objectives

(W_env= 2W_res= 2W_eng)

conclusions
Conclusions
  • Our proposed framework inherently takes the multiple stakeholder objectives into account
  • The framework provides the decision maker a set of alternatives and information about their consequences
  • The case study demonstrated the application of the framework and the insights that can be obtained
    • spatial impact of decisions
    • information to facilitate trade-off analysis
next steps
Next Steps
  • Incorporate uncertainty analysis
    • data limitations and uncertainties
    • value judgments
  • Extend to a larger framework
    • full stakeholder engagement
    • tradeoff analysis
  • Extend to other energy system decisions
ad