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Energy Planning

Energy Planning. Energy Economy Linkage Energy Consumption=F(Population,Activity Level,Energy Intensity...) E=(Energy/GDP)x(GDP/Capita)xPop Gross Domestic Product proxy for Activity Energy Intensity – dependent on Structre of Economy, energy efficiency Energy critical input for development.

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Energy Planning

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  1. Energy Planning

  2. Energy Economy Linkage • Energy Consumption=F(Population,Activity Level,Energy Intensity...) • E=(Energy/GDP)x(GDP/Capita)xPop • Gross Domestic Product proxy for Activity • Energy Intensity – dependent on Structre of Economy, energy efficiency • Energy critical input for development

  3. Energy Planning • Dis-aggregation by sector • Dis-aggregation by end-use • Decide planning unit – village,town,state,nation,world • Decide planning horizon(base year ,targetyear) • Need to have model

  4. Load Forecasting / Energy Economy Models • Time Series Models • Input Output Models • Econometric Models • End-Use Models • Optimisation Framework • Accounting Framework

  5. Uncertainties • Demand System • Supply • Equipment / System downtime • Biomass Availability • Supply variations • Weather

  6. Load Profile • Consumers have usage patterns that vary with time • Load profile – aggregate pattern of all consumers • Peaks – Periods of maximum demand • Valleys – periods of manimum demand • Shoulders (Partial peak) - periods of intermediate demand

  7. Analysis of System Load Curve • A load curve defines power vs time • Load Factor = (Average Power) Peak Power System Load Factor • Capacity Factor (Plant load factor) = Energy generated by a Plant . Energy generated if operation at max capacity

  8. Classification • Time intervals • Daily Load Curves (hourly/half hourly) • Seasonal (Winter/Summer/Monsoon) • Annual Load Curves • User classes • Residential • Industrial • Agricultural • Commercial • End Uses – Lighting, pumping,motors,heating,AC

  9. Load curve of a typical day – MSEB8/11/2000 source : WREB annul report -2001 Demand , MW 9892MW Time hours

  10. Scenario Generation • Scnario - A possible future state of the system • Identify drivers • Study possible ranges of value of drives • Construct combination of drivers • Check for consistency • Detail out scenario • Assess impact / actions

  11. World Energy Consuption Trend Total Energy Consuption EJ Year

  12. World Population Trend Population (Billion) Year

  13. World Specific Energy Consuption Trends Specific Energy (GJ / capita /year) Year

  14. Electricity Demand Estimation • DST - UNDP project – Bankura district in West Bengal • Demand Scenarios • 1994 base year, Target year 2005 • Decion Support System for Energy planning

  15. SECONDARY DATA DIGITISED MAPS REMOTE SENSED DATA PRIMARY DATA DATA BASE Identity indicator/Variable affecting energy DEVELOPMENT PROFILE Trends in indicators ENERGY DSS DEMAND MODULE SUPPLY MODULE FUTURE ENERGY DEMANDS BY SECTOR / END USE FEASIBLE ENERGY SUPPLY SCENARIOS D S S FRAMEWORK IMPACT ASSESSMENT EVALUATION

  16. Drivers for Demand Scenarios

  17. Select Scenario cases

  18. Electricity Demand in 2005 (GWh)

  19. Remote Sensed images Ground Truthing Crop residue factors Total crop residues available CROP RESIDUE MODULE GAS ANALYSIS Estimation of crop areas Digitized maps Map showing Landuse Classification Areal extent of forest non-forest Average fuelwood density non-forest(Survey/hterature) Fuel wood non-forest Secondary Data Sub classification of Sal. And Mixed forests Estimation of wood volume correlations FUELWOOD MODULE Total fuelwood available ACCOUNTING MODULE Height,Density measurements Fuelwood available from forest areas Standing wood estimate forest areas ACCOUNTING MODULE % of Fuelwood Supply module for Biomass Estimation

  20. Demographics 1 Number of Households(HH) 2 % of HH in each income class Appliance ownership data by each income class Total no of Appliance in Area Technology Characteristics 1 Rating (kW) 2 Effiency Electricity consuption in Residential sector(including the load curve) for each seasona/Annual Usage Pattern 1 Daily variation 2 Seasonal variation Number of Electric pump sets Total Electricity Demand.Daily load curve summer /Winter Agriculture load Usage and Seasonal variation Techanical specification Appliance ownership Number of commercial shops Total Appliances Tecnical Characteristics and usage Commercial load

  21. Income class distribution in Rajamele in 1994

  22. Number of Electric appliances / 100 Households Appliance ownership is zero for below poverty income class

  23. Appliance rating used for calculation

  24. Assumptions for Electricity estimation of Agriculture and Commercial load

  25. Rajamele Electricity demand

  26. Daily load curve for Rajamele village in summer in 2005 Load (kW)

  27. Summing Up • Scenario generation – Useful tool for dealing with uncertainty • Models Useful for planing • Energy required critically depend on development profile • Matching of Supply –Demand • Dengers of over /Under estimates

  28. End Note If a man begains with certainties , he will end in doubt, if he begins with doubts he will end in certainties. Anon

  29. Emission Inventories

  30. An emission inventory is an accounting of the amount of pollutants discharged into the atmosphere. An emission inventory usually contains the total emissions for one or more specific GHGs or air pollutants, originating from all source categories in a certain geographical area and within a specified time span, usually a specific year. • An emission inventory is generally characterized by the following aspects: • Why: The types of activities that cause emissions, • What: The chemical or physical identity of the pollutants included, • Where: The geographic area covered, • When: The time period over which emissions are estimated, • How: The methodology to use.

  31. Emission Inventories

  32. Methodology • Estimate apparent fuel consumption in original unit Apparent consumption= production + import – export • Convert to a common energy units • Multiply by emission factor to compute the carbon contents • Compute carbon stored • Correct for incomplete combustion • Convert carbon oxidized to CO2 emissions Cost of CO2 emission: Establish a base line Monitoring and verification

  33. Emission of carbon= Sum(Efabc + Activity) • Ef = emission factor kg of carbon/TJ • Activity Energy input (TJ) • a= fuel type crude oil – 20 toc/TJ • b=sector- activity LPG – 17 toc/TJ • c technology type Coal anthrecite 26.8 toc/TJ

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