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Legislative Policy Conference “Making Hard-Headed Decisions Pay Off” Dale Wahlstrom CEO, The BioBusiness Alliance of Minnesota January 14, 2009 Strategic Flexibility Strategic Flexibility: Renewable Energy Advanced Scenario Planning Scenario planning or scenario thinking is a strategic planning method to develop flexible long-term plans • Uncover and anticipate hidden weaknesses • Minimize the probability of an unintended consequence • Bring together divergent opinions to focus on a most probable scenario Various Scenario Planning Methods: • Contingency Planning • Sensitivity Analysis • Computer Simulations Enriching Minnesota’s Future through the Biosciences Why is it Important to Do This Kind of Modeling? System Dynamics Modeling • All planning is based on models – mental or simulated • Planning in the business and policy worlds relies heavily on the use of mental models • Mental models are difficult to surface, share and test for completeness and accuracy • Goal: integration of various mental models into one shared model • Overall – it is a cost-effective way of reducing errors and increasing the odds of being successful Enriching Minnesota’s Future through the Biosciences Real World Information Feedback 1. Problem Articulation (Boundary Selection) Organization Decisions 5. Implementation of Results 4. Model Testing & Validation Strategy, Structure, Decision Rules 2. Dynamic Hypothesis 3. Model Formulation Mental Models of Real World Base Case Results: Share of Renewables 20.50% 8.84% Enriching Minnesota’s Future through the Biosciences Thank You! Dale Wahlstrom [email protected] 952-746-3847 651 276 5735 www.biobusinessalliance.org BACK UP SLIDES Finally: Review Linking What-How-Whom Know Whom Know What Know How Cluster of Knowledge & Competency Enriching Minnesota’s Future through the Biosciences • To be successful, Collaborative Knowledge Teams must integrate across lines of experience and trends in technical applications around specific market, economic and/or societal challenges. • Clusters of Knowledge & Competency are formed when the Know-How, Know-What, and Know-Whom are linked throughout a region. Model Interface Enriching Minnesota’s Future through the Biosciences Model Specifics Minnesota Energy Divided into 5 Sectors • Electricity • Transportation • Industrial • Commercial Commercial 7% Residiential 10% Electricity 32% • Residential Industrial 19% Overall Objectives and Measures: • Share of Renewable Fuels by 2025 • Jobs • GSP • Carbon Emissions Enriching Minnesota’s Future through the Biosciences Transportation 32% Renewable Energy Analysis Team • Core Team: 20 Experts from Across Minnesota • Feedback Sessions Throughout the State •Michael Sparby, AURI •Cecil Massie, 6 Solutions LLC • Bruce Stockman, MN Corn Growers • Mark Willers, MinWind Energy • Mike Bull and Lise Trudeau, Dept. of Commerce • MaryJo Zidwick, Cargill • Mike Youngerberg, MN Soybean Growers • Rolf Nordstrom and Brendan Jordan, Great Plains Institute • Vernon Eidman, UofM • Richard Magnusson, MN Wheat Growers • Kate VandenBosch, UofM • Ralph Groschen, MN Dept of Ag • Elaine Hoffman, Bemidji State • Shalini Gupta, Izaac Walton League • Bruce Jones and John Frey, MN State U at Mankato • Greg Chamberlain, Xcel Energy Enriching Minnesota’s Future through the Biosciences Modeling Process To use a model, you need a process 1. Discussion to capture the diversity of opinions 2. Debate the issues until the team reaches agreement on a possible scenario (this becomes the “base case”) 3. Input the data and run the scenario 4. Analyze outcomes to understand the behavior Enriching Minnesota’s Future through the Biosciences Understanding the Model Results Three Reoccurring Options when Reviewing Model Results 1. Results are true and showing insights or unintended consequences that we wouldn’t have expected to see using traditional analysis tools 2. Results are skewed by incorrect data 3. Results are skewed by incorrect model structure » Validation and testing needed - never really ends » Includes • Reviewing with experts • Tracking against historical data • Sensitivity analysis Enriching Minnesota’s Future through the Biosciences Current, Unconstrained Base Case Assumptions The base case developed by the team suspends reality and assumes an unconstrained environment This means that the challenges in the following areas are resolved: • Funding • Workforce • Research and Technology • Construction Materials and Feedstock Availability • Feedstock Storage and Distribution • Regulatory Requirements, etc. • Land and Water Use An unconstrained model is not reality Enriching Minnesota’s Future through the Biosciences Current, Unconstrained Base Case Assumptions • All energy units converted to BTUs • Annual 0.5% growth rate in Minnesota energy demand • Nuclear is not replaced • Wind turbine capacity doubles during the 25 year period • Percentage of wind generation utilized – 37.5% • Corn available for ethanol production – 35% • Corn Yield Growth Rate – 2% • Cellulosic ethanol technology becomes viable by 2008 • Available Biomass = 300 trillion BTUs Enriching Minnesota’s Future through the Biosciences Current, Unconstrained Base Case Assumptions Ethanol Targets Wind Targets (RPS) • 2000-2010 – 10% • 2010 – 11% • 2013-2020 – 20% • 2012 – 15% • 2020-2030 – 30% • 2016 – 21% Biodiesel Targets • 2000 – 0% • 2005 – 2% • 2020 – 22.5% • 2025 – 25% Biomass • 2010 – 5% • Industrial – 20% by 2025 • 2015-2030 - 20% • Commercial – 20% by 2025 • Residential – 5% by 2025 Solar Target – 0.1% by 2025 Hydrogen Target – 0% Enriching Minnesota’s Future through the Biosciences • Electricity – 5% by 2025 Current, Unconstrained Base Case Assumptions Time to Construct Plants: • Ethanol and Biodiesel – 3 years • Cellulosic Ethanol – 5 Years • • • • Wind Lead Time – 2 Years Solar – 1 Year Hydrogen – 5 Years Biomass: » Commercial/Industrial – 2 Years » Residential Biomass – 1 Year » Electricity Biomass – 4 Years Enriching Minnesota’s Future through the Biosciences Base Case Results: Share of Renewables Enriching Minnesota’s Future through the Biosciences Base Case Results: Net Renewable Electricity Jobs Enriching Minnesota’s Future through the Biosciences Base Case Results: Wind Turbines Enriching Minnesota’s Future through the Biosciences Base Case Results: Transportation Jobs Enriching Minnesota’s Future through the Biosciences Base Case Results: Ethanol Jobs Enriching Minnesota’s Future through the Biosciences Base Case Results: CO2 Enriching Minnesota’s Future through the Biosciences Base Case Results: CO2 Enriching Minnesota’s Future through the Biosciences Conclusions • With food and energy demand increasing, even with our most optimistic projections, we can’t keep up with need…. • Doubtful that humans will respond in time with conservation methods to avert a crisis • Energy and food production and consumption will be distributed • We believe the agricultural community is our primary hope • Given the known constraints on workforce, construction materials, funding, feedstock distribution, etc., we now need discussions with our communities on how to resolve the constraints in order to achieve our goals for Minnesota • We believe that each community can benefit if they “think globally, but act locally”…… start with what can be done now. Enriching Minnesota’s Future through the Biosciences • • • • • • • • • • • • • • Systems dynamic modeling Dale’s four lessons to keep in mind: Benchmark Look forward Make informed decisions, prioritized Track if the prioritized decisions are being implemented KEY AREAS for you to cover: -Use tools like System Dynamics Modeling and Strategic Flexibility (it is the process and not just a tool) -Focus on what you know and don’t know and make investments where you know and explore what you don’t know (There was a third point here that I missed but think it might be in the few lines above under the “Dale cover” line.)