TERI and Rural Energy Planning
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2 TERI and Rural Energy Planning Rural Energy TERI For MNES Macro Models Rural Energy Model Mandla Ladakh N.Tripura TEESE Model MARKAL Model
3 Survey based rural planning(district level) TERI s experience Aim: To arrive at a feasible mix of energy sources(conventional & conventional) for energy needs. Regions: Ladakh, Mandla,N. Tripura Methodology: Sample surveys, secondary data Output: Different suggestions for the three regions based on their geographic location, resource endowment, feasibility of commercial energy access
4 Extent of inclusion of the rural sector in MARKAL model at TERI Land Preparation Irrigation Cooking Lighting Heating
5 Traditional Fuels Traditional fuels - B AU 300 Million tonnes / / / / / / / / /37 Years Crop residue Firew ood Animal dung 1996/ / / /12 Markal Markal Markal Markal Supply (A+B-C) A. Production Firewood CR Dung Consumption FW Domestic commercial CR Domestic Power Dung Domestic Source:MARKAL output, TERI These figures pertain to Business as Usual(BAU) scenario Source:MARKAL output, TERI Energy Demand Projections Source Scenario Fuelwood FE (Million Tonnes) BAU EFF Dung Cake FE (Million Tonnes) BAU EFF Crop Waste FE (Million Tonnes) BAU EFF BioGas FE (Million Cubic Meters) BAU EFF FE:Frozen Efficiency BAU:Business as Usual EFF:Efficiency Source:Planning Commission, Power and Energy Division, July 2000
6 Rural Energy Model, TERI Developed by Purpose Methodology Mathematical Approach Level Sectoral coverage Time frame Data requirements TERI To identify an optimal mix of centralized/decentralized,conventional/nonconventional energy systems from the point of view of farmer Optimization Mixed Integer Programming(MIP) Village Rural Energy sector Medium to short term Quantitative, primarily survey based
7 Data hurdles Limitations of secondary data Assessing biomass- data available in terms of geographical area and not in volume terms Scanty data on cropping density, crop height, crop diameter; estimation of volume not readily available Highly scattered information; tedious and cumbersome to accumulate them Incomplete and faulty records;less data reliability Sample selection methodology-practical considerations for cluster formation Limitation of considering per capita land without considering the productivity of the land Forest villages: high per capita agricultural land of low quality, unsuitable for agricultural Desire to incorporate per capita livestock population for sample selection through cluster formation:data paucity
8 Modeling Rural Energy Transition Understanding energy transition CONVENTIONAL PERCEPTION REALITY Step jump Reverse movement Increase in efficiency of the same fuel Incomplete switch over
9 Understanding rural India & The economics of energy choice
10 Features Implications Small human settlements-73% of villages have <1000 people or 200 households Geographically dispersed villagesclustered in plains, dispersed in hilly and forest areas Dominance of cooking and agricultural pumping Geographically dispersed locations of irrigation pumps Seasonality of loads Low purchasing power- landless peasants and marginal farmers account for over 50% of rural population Absence of infrastructure Low efficiency of the use of fuel Energy requirements are much lower compared to the urban counterparts, high cost of transmission Sparse nature of demand, economically infeasible to provide power transmission to few houses Two primary energy consuming activities Economically not viable Demand for electricity not uniform throughout the year, drops in monsoon Cannot afford the fixed costs as well as the variable costs of obtaining electricity or LPG Modern energy carriers cannot be supplied Source: Ravindranath & Hall, 1995
11 Factors determining energy choice in rural regions Income To sustain the present as well as future fixed & variable costs Discount rate First cost effects Easy availability of biomass and animal power Quality of electricity supplied Subjective perceptions Fear, superstitions
12 Model selection Purpose of the model Underlying assumptions and their validity for developing regions in developing countries Outlining the methodology for Demand projection Mapping supply options Assessing impacts Appraising different impacts Geographical coverage National, Regional,Local Sectoral coverage Time horizon Data requirements
13 Miles to go. Understanding the components of transition Movement of households up the domestic energy ladder and associated improvement in indoor air quality or vice-versa The shift from animal power to tractors and pumpsets for ploughing and irrigation respectively Shift of dependence from common land to private land and the associated changes in property right regime Increased stakeholder participation Identifying the variables that capture the transition factors Realizing that these factors lie under the broad rubric of transition in the overall rural landscape Obtaining relevant data, disaggregated on different agro-climatic and socio-economic considerations Greater synergy among researchers to coordinate the field and micro studies
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