NorthWestern Energy Group, Inc. · NASDAQ:NWE
NorthWestern Energy — Technical Presentation (July 2013)
29 slides from NorthWestern Energy's technical presentation, Jul 24, 2013
Slide 1: Resource Planning with Uncertainty for NorthWestern Energy
Resource Planning with Uncertainty for NorthWestern Energy Selection of Optimal Resource Plan for Gary Dorris, Ph.D. 2013 Resource Procurement Plan Ascend Analytics, LLC [email protected] 303.415.0311 July 24, 2013 www.ascendanalytics.com
Slide 2: Outline
Outline • Resource Planning Paradigms and Choices • Resource Selection • Best in Breed Resource Selection • Best in Show Resource Selection • Risk Reduction Value (RRV) for Renewables 22
Slide 3: Resource Planning Paradigms and Choices
Resource Planning Paradigms and Choices 3
Slide 4: Planning in Transition
Planning in Transition • Portfolio perspective Fuel diversity Reliability and intermittent resources Uncertainty in fuel, emissions, and power • Use of market for fuel and power • Analyze generation resource options with respect to market dynamics • Capture new dynamics Weather o Load o Wind
Slide 5: Central Tenants of Resource Selection Modeling
Central Tenants of Resource Selection Modeling • Utilize All Available Information Effectively capture all major elements of uncertainty o Markets o Physical o Environmental Does the decision analysis process meet “include all the available information a reasonable person would use to make a dec
Slide 6: Economic Resource Dispatch
Economic Resource Dispatch Hourly Sources & Uses Liquid Market Utilities • “Economic Dispatch” – Dispatch is determined by generation cost relative to market prices • NorthWestern is a price taker [Generation + Market Purchases] = [Load + Market Sales] • Generation is not used solely to meet load –
Slide 7: Renewable Portfolio Standard Ancillary Service Implications
Renewable Portfolio Standard Ancillary Service Implications • Perception that increasing RPS creates value for flexible resources Negative power prices Large potential swings in supply greater demand for ancillary services and flexibility 25% of Load Supplied from Renewables Wind generation is
Slide 8: Deterministic vs. Stochastic Models
Deterministic vs. Stochastic Models • Heavy dependence on deterministic results with scenarios The likelihood of result is not understood One outcome for Model inputs are variable and interdependent deterministic Inputs probabilistically envelopes future states Simulations consistent with ob
Slide 9: Resource Selection
Resource Selection fo Ascend Analytics »
Slide 10: Measure of Portfolio Costs
Measure of Portfolio Costs Costs = Net Power Costs (NPC) + Fixed Costs (FC) Net Power Costs (NPC)= Fuel + Variable O&M+ Purchase Power – Wholesale Sales + Hedge Payoffs NPCfpy= Net Power Cost of portfolio p in year y of future f Calculated from dispatch model FCfpy= Fixed revenue requirement o
Slide 11: Best-In-Breed
Best-In-Breed Objective: • Find the cheapest capacity expansion plan that satisfies the constraints Cheapest is often defined as the net present value of the revenue requirements Constraints : • Renewables, RECs, limits on market sales and purchases,… Result • Optimal capacity expansion of generat
Slide 12: Best in Breed Expansion Plans: Growth of Renewables – 2030
Best in Breed Expansion Plans Growth of Renewables – 2030 Energy Through Time PowerSimm™ Result
Slide 13: Best-In-Breed
Best-In-Breed Question: • How robust is the plan under variable conditions? • Is this the breed for the future? Issues: • Risks are unknown? Robustness of portfolio is unknown? • What happens when gas prices spike up to 10 $/MBtu for six months?.... Limitations of Scenario Analysis: • Too many views
Slide 14: Simulation Requirements
Simulation Requirements fo Ascend Analytics Y
Slide 15: Integrating Physical and Financial Uncertainty
Integrating Physical and Financial Uncertainty Dispatch Detail During delivery to • Hourly chronological dispatch • Forced Outages modeled as random events simulations • Seasonal and peak period generating characteristics Optimal Resource Selection Forecasted monthly forward prices Unified simulatio
Slide 16: Scenario Analysis
Scenario Analysis Common Scenarios: High, Med, Low • Which forecast are the best? Gas Price Scenario Analysis • Scenarios with prices monotonically increasing 14.00 over time. 12.00 • Are these prices consistent 10.00 with observed patterns? Scenario 1=$4 • What’s the probability $/MBtu 8.00 Scenari
Slide 17: Forward Price Validation History and Simulations: Natural Gas
Forward Price Validation History and Simulations: Natural Gas Forward Price Validation- Simulated forward market prices for Henry Hub Price Paths for Final Evolved Forward Curve Simulation • Large price spikes followed by mean reversion • 2 to five year cycle • Large volatility in prices followed by
Slide 18: Weather, Hydro Flows, Load, Price Simulations
Weather Hydro Flows Load Price Simulations Hydro Flows Intermittent Generation Gas Electric Weather Load Price
Slide 19: Best in Show
Best in Show s Ascend Analytics .
Slide 20: Integrating Physical and Financial Components of Uncertainty
Components of Uncertainty: Integrating Physical and Financial Financial Physical • Fuel Prices • Load Gas (Monthly, Daily) Weather Coal Growth Emission Allowances o Customer Mix o CO2, SO2, Nox o Energy Efficiency RECs • Wind • Electric Prices WeatherLoad Supply Stack Transmission
Slide 21: Tools of Supply Planning Model Attributes
Tools of Supply Planning Model Attributes Uncertainty Factor Production Cost Models Integrated Risk Based Planning Models Load Growth Fixed Simulated Uncertainty Load Patterns “Typical” profile Uncertainty in Profile and Usage Pattern Conservation Fixed Weather Based Demand Response Weather Fixed We
Slide 22: Best-In-Breed & Best-In-Show
Best-In-Breed & Best-In-Show Simulations Simulation 1 Simulation 2 Simulation 3 Simulation 4 Simulation 5 • Capacity planning finds the optimal expansion plan using dynamic programming in a simulation-based framework Best-In-Breed • Optimal plan defined by: Portfolio of generation assets • Simulat
Slide 23: Best In Show: Total Ave Revenue Requirements vs Cost at Risk
Best In Show Total Ave Rev Requirements vs Cost at Risk $800 Case Rank 5 $750 • How do environment Total Ave Revenue Requirements $700 Case Rank 4 controls on coal impact $650 Case Rank 3 risks? ($Millions) $600 Case Rank 1 Case Rank 2 • What resources are more $550 highly valued with growing $500 p
Slide 24: Definition of Common Planning Risk Metrics
Definition of Common Planning Risk Metrics Cost at Risk (CaR) for Rev Req = CaR = 95th percent costs – mean costs How do you decide where to be on the frontier? Avista IRP 2011 24
Slide 25: Total Cost Portfolio Selection
Total Cost Portfolio Selection 25
Slide 26: Risk Reduction Value (RRV)
Risk Reduction Value (RRV) 26
Slide 27: Net Benefits Example Continued
Net Benefits Example Continued What is the net benefit of new strategy? Alternative Supply Portfolio • Cost increases of new strategy are mitigated by decrease in tail risk. f RPS ( x ) Base Portfolio RPS Portfolio • Preference for lower cost base strategy = $25 Million reversed when net benefit in
Slide 28: Risk Reduction Value of Renewables Example Continued
Risk Reduction Value of Renewables Example Continued • Expected costs greater, but risk adjusted costs are less • Value risk premium of renewables as insurance premiums that provide a hedge against potential losses. In this case, option premiums increase the expected value, but provide benefits grea
Slide 29: Planning Steps
Planning Steps • Develop Model Inputs Market prices Load forecasts Resource options • Validate Model Consistency of model o Historic values o Expectations • Analyze Results Least Cost Revenue Requirements Flexible Resource Adequacy (FRA) 29
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