2014 Integral Analytics, Inc.

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8 Company Overview Putting Advanced Analytics into Software to Manage Utility Costs & Risks Smart Grid Solutions T&D Planning Storage & Renewable Evaluation DSM Planning & Evaluation Marketing Effectiveness Offices in Ohio, Vermont, Massachusetts and Colorado 8

9 Agenda Avista Pullman project overview DSMore Benefit Cost Analysis LoadSEER Spatial Load Forecasting SmartSpotter Targeted Marketing IDROP Intelligent Load Management 9

10 Distributed Marginal Prices (DMP) Distributed Marginal Prices (DMP) $/MWH Local DMP Prices (4pm) Transactive Price Signal from IDROP (Circuit 11XX, Western US Utility) 4 5 PM 1 Mile Copyright 2014 Integral Analytics Power Flow Power Flow Substation Substation 10

11 Avista Smart Grid Project 11

12 The Leading Cost-Effectiveness Tool for Smart Grid Programs 2007 AESP Innovative Product Award Winner 12 12

13 The DSMore Overview Accurate Hourly Valuations Using weather effects, and covariance of prices and loads, hourly by weather station. Using hourly end use load savings, without costly meters. Valuing low probability, high consequence events. Compare Across Supply and Demand Resources Calculating cost-based and market-based valuations. Customize avoided costs to specific customer loads and weather Option value accurately values DSM the same way that asset planners value supply Flexible and Adaptive Supports gas & electric programs, numerous rates and program types. Values portfolio of programs and measures. Used to calculative measure and program incentives. Allows what if scenario analysis

14 Covariance Matters Covariance is a key concept in supply-side asset planning. Ignored in DSM valuation, but consequential in determining risk and value. Hourly Covariance example Scenario 1 represents valuation using a unrelated avoided cost and load profile. Scenario 2 the load profile and avoided cost are co-varied. Difference ($500 v. $620) is due to the co-varying of prices with loads, or covariance. Average Loads & Prices Hourly Loads & Prices Hour MW $/MWh Total $ MW $/MWh Total $ 1 2 $50 $100 1 $20 $ $50 $100 1 $20 $ $50 $100 2 $50 $ $50 $100 3 $80 $ $50 $100 3 $80 $240 Avg. 2 $50 2 $50 Total $500 $620 Both scenarios average 2 MW and $50 per MWH, but total costs differ when viewed hourly. Covariance value (or risk) is what suppliers pay when supply is short, or weather extreme. Accurate valuation of energy requires detailed covariance analysis

15 Hourly Covariance Example 300 kwh Savings for each measure Comparison of energy cost savings 15 15

16 700 Scenarios Loads and prices are both driven by weather covariance. If we use averages we lose the high end values. Avoided Generation Costs ($$) Increasing Market Prices More Extreme Weather $70/MWH Cool Weather Hot Market Price $20/MWH 16 16

17 Test Distributions and Risk Test results are driven (significantly) by market prices and weather Tests Min Value Max Value Today s Value Alternative Value Option Value Lowest market prices, mildest weather Highest market prices, extreme weather Today s market prices Alternative choice for Today s prices Long Run Value over many market prices, all weather Minimum Today's Alternate Option Maximum Value Value Value Value Value Utility Test TRC Test RIM Test RIM (Net Fuel) Societal Test Participant Test RISK Assessment Probability That Test Result Is Less Than X Prob (Value) Option Value Min Value Today s Value Average Value Max Value Test Values Based On Varied Market Price / Weather Scenarios 17 17

18 The DSMore Interface Easy to Use Excel Interface Familiar interface Allows custom calculations to feed model inputs One file per measure Fast Processing Vary fast processing of hourly analysis Batch processing and aggregation of measures Summary Reports Accurate weather normal participant savings and program economics. Annual cash flows Present value of cash flows using discount rates 18 18

19 Spatial Load Forecasting to Target EE/DR/RE Resources 19

20 Spatial Covariance Where resources get deployed MATTERS DR, EE, solar tend to cluster spatially Natural load growth (and sprawl) is spatially correlated EV adoption is clustered, causing risk to specific circuits Need to account for Spatial Covariance to maintain grid integrity 20

21 Locational Avoided Costs Locational Avoided Costs Depend on Forecasts of New Load, Distributed Generation and EV growth 21

22 Locational Targeting and Valuation GIS-based spatial forecasting modeling 20 years of satellite imagery, usage, growth and land use changes. Multiple layers of Smart Grid value can be co - optimized Commodity (DR, EE, supply risk, IRP) Marketing (EE earnings, billing options) Locational Assets (T&D, voltage, switching, phase balancing) Enables TRUE Integrated Resource Planning for EE, SmartGrid 22

23 LoadSEER Projections INPUTS Customer Locations / Per Capita Growth Demand Side Management / Load Control Optimal Solar Power Sites Plug-in Electric Vehicle Penetration Transportation Future Land Use OUTPUTS Hourly Peak kva per acre

24 Satellite Analytics 24

25 Circuit Level Analysis 25

26 Copyright 2013 Integral Analytics 26 26

27 South Fresno DPA 2013 Relative Loading 125 % 100 % 75 % 50 % Copyright 2013 Integral Analytics 27 27

28 South Fresno DPA 2019 Relative Loading 125 % 100 % 75 % 50 % Copyright 2013 Integral Analytics 28 28

29 South Fresno DPA 2022 Relative Loading 125 % 100 % 75 % 50 % Copyright 2013 Integral Analytics 29 29

30 LoadSEER Load at Risk Capacity Load at Risk, MVA per acre Height ~ MVA Density // Ratio of Top:Base ~ Load At Risk 30

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32 Analytics help find the sweet spot for portfolio programs 1. Greater participation 2. Lower customer acquisition costs 3. Higher Net Savings 4. Greater Yield (kw/kwh) 5. Higher avoided cost of service 32

33 Avoided Costs By Customer Average Costs (6 cents) vs Marginal Costs (3 to 10 cents) Even with standard tariff pricing, we can target higher cost customers with more unique energy efficiency programs to lower costs for all Average: $42/ MWH. Range $30 to $120/MWH. RED LINE shows a distribution of COST OF SERVICE And smart meter data now allows us to calculate the actual cost to serve for each customer, individually. Newspaper Smart Charged Electric Vehicle Manufacturer With Co-Gen Street Lights University Flat Loads (lower price) Office Tower Peak Charged Electric Vehicle Water Park Peaky Loads (higher price) 33

34 10x More Value in Targeted Approaches Microtargeting Broad segments Market Research/Offer promotion ($300,000) ($250,000) # Customer Getting Offers 25,000 25,000 # Participants (Response Rate) 1, Avoided Costs: Energy.65/kWh.45/kWh 2,000 kwh (micro) vs. 1,400kWh (broad) saved $1,300,000 $472,500 T&D, Capacity Value NPV $1,820,000 $567,000 $800 incentive x participants ($800,000) ($600,000) VALUE $2,020,000 $189,500 34

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41 We Bring Key Demographic Variables We Know Matter We Interact Demographic Variables with Load Shapes to Score Potential 41

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43 Most valuable Least valuable 43

44 Cost of Service 44

45 Integrating Distributed Resources into Optimal Portfolios 45

46 Load Control Options 46

47 Choreograph End-Uses Coordinate the natural duty cycles of appliances across customers, produces substantial savings in total peak demand, flattening peak load but keep energy sales constant. Optimizations have been applied in practice with no reported complaints by customers. Reductions in peak demand reduce volatility, and risk. Result can be multi-million dollar changes in utility capital plans and spinning reserve requirements. Creating the Virtual Power Plant Load follows Supply 47

48 Optimizes Load Control Determines least cost resources to dispatch mathematically guaranteed Choreographs loads across customers To maximize value to utility Renewable generation integration Peak demand reduction Cost to serve reduction Load balancing Plant following 48

49 IDROP Method Collect Network and Customer Data Send Dispatching Commands to Load Control Hardware Develop Resource Level Forecasts Use Data to Develop Dispatching Collect Constraints 49

50 Dispatchable Resources Actively micro-dispatches resources Water Heaters Air Conditioners Heat Pumps Commercial Refrigeration Electric Vehicle Chargers Onsite Renewables Storage Batteries Fast: < 5 seconds dispatching possible 50

51 IDROP Applications 51

52 MW Load Circuit Load Leveling Load Choreography Minimize Volatility While Maintaining kwh 52

53 Minimize Cost of Service Demand is shifted away from the highest cost periods and customers' total demand for heating/cooling is still met, without customer involvement. 53

54 Plant Following Total Load kw Generation Costs Assumes 10% Smart Charge Dynamic Dispatching AC 2 to 5 degrees WH 1 to 4 hours Smart Charging EV Plant Following 54

55 Thermal Storage IDROP maximizes value of RE Generation by controlling thermal storage 55

56 IDROP Benefits Drive down procurement costs Offset power procurement and bid demand into the market Balance the grid, avoid outages and extend asset life Reduce system peaks Reduce spinning reserves and Offset renewable intermittency 56

57 Covariance Matters Covariance used in supply-side asset planning is ignored in DSM valuation, key to determining DSM risk and value Hourly and Spatial Covariance (grid) Time value of energy savings Natural load growth cluster spatially DR, EE, EV, solar cluster spatially Problems arise when Covariance is Ignored Cinergy hub 1999, California 2000, Texas (now), Alberta Accurate energy valuation requires detailed covariance analysis Energy prices are non-normal to use Black Scholes methods Value at risk analytics miss key risks at 99 th percentile 57

58 Distributed Marginal Prices (DMP) DMP are like LMP for distribution grid Values Supply-side (kw) avoided cost and grid-side costs (KVAR, voltage, power factor) simultaneously Single price signal per house, per customer to spark innovative savings at exactly The right PLACE The right TIME The right AMOUNT DMP Paper located at: 58

59 Distributed Marginal Prices (DMP) Distributed Marginal Prices (DMP) $/MWH Local DMP Prices (4pm) Transactive Price Signal from IDROP (Circuit 11XX, Western US Utility) 4 5 PM 1 Mile Copyright 2014 Integral Analytics Power Flow Power Flow Substation Substation 59

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