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The Demand Forecast and Conservation Analysis Interface May 16 2008 PNREC Massoud Jourabchi & Tom Eckman
2 Why Interface Matters? Over estimation of conservation potential Capturing proper interaction between demand forecast and conservation resource Capturing Price driven Conservation Effects Capturing Take-back effects
3 Council’s Power Planning Process Economic & Demographic Forecasts Fuel Price Forecasts Conservation Programs and Costs Generating Resources and Costs Demand Forecasting System ResidentialCommercialIndustrialIrrigation Total Electricity Use Supply - Demand Balance Resource Supply (Cost and Amount) Electricity Price
4 Tracking Energy Demand
5 Major Factors Influencing Demand Long-term factors Economic Activity Energy Prices Technology choices Socio-economic changes Short-term factors Weather
6 Basic Building Blocks of long-term Forecasting Model For each enduse in each sector consumption is determined in part by: Number of Units (A) Fuel efficiency choices (B) Fuel choice (C) Energy use by an enduse = A * B * C
7 Number of Units (A) Driven by the economic forecast Number of Existing home Number of New Homes ( Single, Multi, Manuf.) Square footage of existing commercial buildings Square footage of new commercial buildings Level of production from industrial, agricultural and mining firms Source of information Review process: by State economists and Demand Forecasting Advisory Committee
8 Fuel Efficiency Choices (B) Efficiency/capital cost trade-off. Trade-off between high up-front costs and high operating cost. Source of information: Various sources and studies (LBL, DOE,…) Review process : Demand Forecast Advisory Group and In-house
9 Residential Hot Water Heating Efficiency Curve Baseline 2.0 GPM Showerhead Tank Insulation Heat Pump Water Heater Energy Star Clothes Washer (MEF 1.8) Energy Star Dishwasher (EF65) Wastewater Heat Recovery Energy Star Dishwasher (EF68) Energy Star Clothes Washer (MEF 2.0)
10 Fuel Choice (C) Customer trading off one fuel for another on the basis of relative cost of fuels, factors considered include: Capital Cost Operation and maintenance cost Non-price factors such as customer preference for one fuel over another Source of Information: EIA for Historic fuel prices, Utility, NEEA Surveys of customer choices Calibration of actual demand 1985-2005 Review process: Demand Forecast Advisory Group
11 $ / therm $ / kWh Therms / gallon hot water kWh / gallon hot water Number of Gas Water Heaters Number of Electric Water Heaters Gallons per day Hot Water
12 Illustrative Example Demand from Water Heating in New Homes Electric water heaters demand in new homes is calculated as: (A) Number of new single family homes: 20,000/yr (B) Electricity Efficiency: 0.90 Energy Factor = 3600 kWh/yr (c) Market share of electric water heaters: 69% Electricity Demand from New water heaters in new homes 20,000*3600*.69 ~ 49,680 MWH ~ 5.67 MWa Similar approach is used for existing homes. Existing homes are tracked over-time and the energy use is reduced each year based on the physical life of the device (i.e., as existing units fail, they are replaced with units meeting federal minimum efficiency standards).
13 How Conservation Supply Curve for Water Heating is Created The three factors (A, B and C) are provided to Procost model Conservation supply curve estimation starts from the base use and moves along the efficiency-cost trade-off curve. Conservation potential for various points along the curve are estimated in a similar fashion to the forecasted demand calculations.
14 Residential Hot Water Heating Dwelling Unit Supply Curve 2.0 GPM Showerhead Tank Insulation Heat Pump Water Heater Energy Star Clothes Washer (MEF 1.8) Energy Star Dishwasher (EF 65) Wastewater Heat Recovery Energy Star Dishwasher (EF68) Energy Star Clothes Washer (MEF 2.0) Cost-Effectiveness Limit
15 Demand Forecast, Conservation supply & Resource Optimization Frozen-efficiency Forecast and the Conservation supply curves consistent with the forecast is provided to Portfolio model In the Portfolio model, load forecast is subjected to 750 different futures and optimum level of conservation acquisition as well as other resource options is determined. The optimum conservation level is fed back to the demand forecast model A new Sales forecast reflecting impact of conservation targets and costs is produced.
16 Demand forecast and Conservation Interface Demand Forecast Price effectPrice effect Frozen efficiencyFrozen efficiency SalesSales Conservation Potential Assessment Model Resource Portfolio Optimization Model Other Supply Resource Options Cost-effective Cons. Frozen Eff. Usage & units OptimumConservation Targets Targets Conservation Supply SupplyCurves Frozen Eff. Load Eff. Load
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