1. MIT Laboratory for Energy and the Environment
Scenario-Based Multi-Attribute Tradeoff Analysis: Vermont Public Service Board Presentation
Stephen R. Connors Analysis Group for Regional Energy Analysis MIT Laboratory for Energy and the Environment One Amherst St. Room E Cambridge, MA , USA

2. Multi-Attribute Tradeoffs
MIT “Framework”
Originated in the late 1980s (IRP) // Not a “model”
Designed as Extensive/Inclusive Approach for Multi-Stakeholder/Controversy-Laden Decision Environments
Multi-Attribute ≠ Multi-Objective
Calculate every imaginable attribute (automatically)
Few “Decision Attributes”/Numerous “Performance Attributes”
Used in Two Modes:
Exploratory/Learning Mode [Joint Fact-Finding, Rough Consensus on Long-Term “Vision”]
Decision/Negotiated Settlement Mode [Choose among superior portfolios of option]

3. Whose Attributes? The “Usual Suspects” The Black Sheep Attributes
Rates vs. Bills vs. Revenues
Price/Rate Volatility
Costs vs. Investments
Continuous vs. “Lumpy” Expenditures
Three E’s: Efficiency, Equity, Employment
The “Incalculable”
Those Darn “Externalities”
Indirect Economic Impacts
Those Pesky Markets

4. “Markets Are Our Friends”
Competition - Boston Style
Who’s in Charge?

5. You Want to Predict This?
$/MWh
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec

6. … And, the “Ability to Site”
Common NIMBYs
NIMBY Not in My Backyard
NOTE / NOPE Not Over There Either Not On Planet Earth
BANANA Build Absolutely Nothing Anywhere Near Anybody
AGREA NIMBYs
NUMBY Not Under My Backyard
Originally for pipelines
Equally good for carbon sequestration
NIMO Not In My Ocean
Ocean Disposal of CO2
NOMH (‘gnome’) Not On My Horizon
Originally conceived for offshore wind
Equally good for onshore-ridge wind

7. Direct Stakeholder Input
A Structured Dialogue...

8. Tradeoff Analysis (1)
Scenario-Based Multi-Attribute Tradeoff Analysis is a scenario planning approach developed to facilitate dialogue and learning among multi-stakeholder audiences.
Large Number of Activities/Options (Multi-Option Strategies)
Large Number of Uncertainties (Multiple Futures, Scientific Uncertainty)
Large Number of Goal States/Attributes (Multiple Stakeholders, Conflicting Goals)

9. A multi-option strategy for a given future is a scenario
Tradeoff Analysis (3)
“Crafting” Scenarios to Help Guide Policymakers
A multi-option strategy for a given future is a scenario

10. Tradeoff Analysis (2) “Features”
Identifies “Good” and “Bad” Strategies
Identifies Competing/Complementary Sets of Options
Recognizes Different “Deployment Schedules” of Different Options
Use to Identify “Robust/Flexible” versus “Optimal” Strategies
Helps Facilitate Stakeholder Dialogues

11. Shandong Province Population ≈ 90 Million Area ≈ Size of Florida
Installed Capacity (‘00) ≈ 18.5 GW (mostly coal)

12. Shandong Strategies Strategy Components (1008 strategies)
Existing Generation
Additional Unit Retirements (2)
FGD Retrofits (2)
Use of “Prepared” Coals (3)
New Generation
Baseload Technology Mix (7)
Extra-Regional Generation (2)
End-Use Options
Peak Load Management (2)
Improved End-Use Efficiency (EUE) (3) (Note: The first option in any option-set is by definition the “reference option.”)

13. Tradeoff Analysis Results

14. So, What Does It Cost?

15. Ann. SO2 & PM10 Emissions
For the Strategy with Prepared Coal in Existing Units, Existing Unit Retirements and FGD Retrofits, Aggressive (20%) End-Use Efficiency, Peak Load Management and New Conventional Coal, Nuclear and Natural Gas Generation
<- Sulfur Reductions from Fuel Switch (from Reference Strategy)
<- PM Reductions from Fuel Switch
Reductions from Fuel Switch, End-Use Efficiency & New Generation Choice ->
Reductions from Fuel Switch, End-Use Efficiency & New Generation Choice ->
Reference Future

16. Key Results (Shandong)
Significant cost-effective opportunities exist for reducing power plant criteria pollutants (SO2, PM, NOx), and reducing increases of greenhouse gas emissions (CO2).
The best performing strategies were a combination of the following options:
Use of prepared coal to reduce PM and SO2
Select retirement or emissions retrofits of existing generation
Implementation of peak load management and end-use efficiency programs
Addition of non-carbon emitting generation technologies
Do not forget the fuel supply infrastructure and markets

17. Demand-Side and CO2

18. Existing Units and PM10

19. What’s Required?
Develop an “infrastructure management” perspective. What is the resulting “vision?”
Explore options in greater detail
Develop “in-depth” knowledge of energy consumption patterns and renewable energy resources
Identify and implement “essential” robust options, and develop “promising” future flexible options.

20. Now Looking at Tougher Options
Technology Development, Deployment and Use
Renewable Resources…
Non-dispatchable
Variable across multiple time scales
Temporal dynamics interact with other important dynamics (markets, consumer behavior)
Decentralized Decisions
Choice and use of distributed generation
Energy efficiency options that use information technology to reduced demand (smart loads)
Influenced by Market Prices and other Situational Aspects
Example: Wind Resource Dynamics

21. Wind in Space and Time Electricity Demand Generation from Wind
Source: Mass Renewable Energy Trust TrueWind Solutions

22. Seasonal & Daily Variability
Generation Summed by Month and Hour-of-Day (2004)
Hotel
Buzzards Bay
Boston
Nantucket
Logan

23. One Site for Many Years…
Nantucket (Sleigh Ride?)
Windspeed: SD: 1-2 m/s; CV: 10-20%. CF: SD: 10-20%; CV: 25-35%

24. Operating Modes and “Resource” Portfolios
Renewable Resource Variability
Wind and Sun (Magnitude and Timing)
Rainfall (Hydropower, Biomass)
Fuel Markets
Fuel Prices/Price Differentials (esp. Natural Gas)
Infrastructure Investments (Pipelines/Storage/LNG)
Conventional Generation
Nuclear Availability, Hydro Potential
Power Market Structure (Capacity Markets, Bid Rules)
Power Grid Operations (Reliability/Contingency Practices)
Energy Demands
Demand Growth – Relative to Supply Growth
Heating Degree Days/Cooling Degree Days

25. Identifying Robust Strategies
A Robust Strategy has Robust and Flexible Options
Commonalities and Differences

26. Closing Observations/Questions
At Which Stage Are You?
Short/Medium-Term in the Context of a Long-Term Plan/Vision/Whatever
Are All the Major Factors Been Included/Considered?
Have the Major Organizational/ Institutional Factors Been Overlooked? (Brains and Bodies)

27. Have We Had It Too Easy?
We need to develop the information, tools, implementable visions, and the policies and people to realize them.