development of a decision aiding framework for energy infrastructure siting ganesh doluweera &...
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Development of a Decision Aiding Framework For Energy
Infrastructure Siting
Ganesh Doluweera & Joule BergersonInstitute for Sustainable Energy, Environment and
Economy, University of Calgary
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32nd USAEE/IAEE North American Energy Economics ConferenceJuly 30, 2013
Motivation
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• 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• 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
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Current Practice
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Proposed Framework
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Objective Alt 1 Alt 2
Obj 1 xx xx
Obj 2 xx xx
Obj 3 xx xx
Obj 4 xx xx
Consequence tables Obj
1Obj 2 Obj 3 Obj 4
Alt 1
Alt 2
Alt 3
Obj 1
Obj 2 Obj 3 Obj 4
Alt 1 xx xx Xx xx
Alt 2 xx xx Xx xx
Alt 3 xx xx Xx xx
Preference structure and rankings
Eastern Alberta Transmission Line (EATL)(500kV HVDC; 500km̴ )
Case Study
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• 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)
Methods: Stakeholder Objectives1. Minimize Residential and property value impacts
1. Minimize the proximity to residential properties2. Avoid densely populated areas (Urban areas)
2. Minimize Environmental impacts 1. Minimize river and water body crossings2. Minimize proximity to environmentally sensitive areas3. Avoid highly sensitive ecosystems
3. Optimize economic and engineering factors1. Parallel existing linear disturbances (roads, power lines)2. Minimize cropland disturbances 3. Minimize building on high slopes (terrain features)4. Minimize cost 7
Methods: System Model
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References:1. 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; 2012.2. Keeney RL. Utility Functions for Multiattributed Consequences. Management Science. 1972; 18:276-87.
• Stakeholder objectives (ie. xi) and preferences (ie. Vi(∙) and wj) are inferred using transcripts of EATL regulatory hearings
[1,2]
Methods: System Model
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• 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
Illustrative Results
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• 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
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Alternative route option 1
All high level objectives are weighted equally(W_res = W_env = W_eng)
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Alternative route option 2
Preference for minimizing residential impacts is twice as that of other high level objectives(W_res = 2W_env = 2W_eng)
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Alternative route option 3
Preference for minimizing environmental impacts is twice as that of other high level objectives(W_env = 2W_res = 2W_eng)
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An Example of Tradeoff Analysis
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%54
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Residences within 800mNumber of River crossings
Preference for minimizing residential impacts (W_res)
Number of residenceswithin 800m of the route
Number of river cross-ings
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
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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
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Supplementary Information
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System Model
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Results – Consequence Table
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Objective R1 R2 R31. Residential
1.1 Residences within 200m of ROW 33 14 55
1.2 Residences within 800m of ROW 66 40 892. Environmental
2.1 River and water body crossings 21 32 18
2.2 ESAs within 200m of ROW 0 0 03. Engineering 3.1 Line length 93km 89km 96km
3.2 Length of paralleled linear features 88km 80km 84km
3.3 In-field cropland disturbances 3.4km 5km 8km