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J. Renewable Sustainable Energy 1, 043103 (2009); doi:10.1063/1.3167282 (24 pages)

Decentralized energy planning through a case study of a typical village in India

R. Hiremath 1,
Bimlesh Kumar 2,
P. Deepak 1,
P. Balachandra 3,
N. Ravindranath 4,
and B. Raghunandan 5

1 AE and CST, IISc, Bangalore 560012, India Map This map
2 Civil Engineering, Indian Institute of Technology, Guwahati 781039, India Map This map
3 Department of Management Studies, IISc, Bangalore 560012, India Map This map
4 CST, IISc, Bangalore 560012, India Map This map
5 Aerospace Engineering, IISc, Bangalore 560012, India Map This map

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Decentralizedenergy planning (DEP) is in the interest of efficient utilization of resources. DEP is one of the options to meet the rural and small scale energy needs in a reliable, affordable, and environmentally sustainable way. The main aspect of the energy planning at the decentralized level would be to prepare an area-based DEP to meet energy needs and development of alternate energy sources at least cost to the economy and environment. The geographical coverage and scale reflect the level at which the analysis takes place, which is an important factor in determining the structure of models. DEP planning involves multiple objectives and different kinds of constraints. The present work presents the methodology for the DEP. The kinds of objective functions and constraints which have to be included in the DEP have been presented in the present work. Decentralized planning involves scaling down energy planning to subnational or regional scales. Energy planning at the village level is the lowest level of the application of decentralized planning principle and district is the uppermost level. The present work for the analysis of DEP at the village level has considered different scenarios. Conflicting objectives are considered in the implementation of DEP at the village level. This implementation has been shown through a case study done in a village named Ungra in the Tumkur district from the Karnataka state in India. DEP is assessed with the help of field studies, available data, and decentralized energy modeling. Through DEP energy demand at 2020 has been presented for the Ungra village.

© 2009 American Institute of Physics

Article Outline

  1. INTRODUCTION
  2. MODELS FOR DECENTRALIZED ENERGY PLANNING
    1. Rationale for selecting GP for DEP
    2. Data needs for DEP
  3. SCENARIOS CONSIDERED FOR MODELING
    1. Business as usual (BAU)
    2. Economic objective scenario (EOS)
    3. Renewable energy scenario (RES)
    4. Sustainable energy development scenario (SDS)
  4. PROBLEM FORMATION
    1. Objective functions
      1. Minimization of cost
      2. Maximization of system efficiency
      3. Minimization of use of petroleum products
      4. Maximization of use of locally available resources (LOCAL)
      5. Maximization of employment generation
      6. Minimization of COX , NOX , and SOX emissions
      7. Maximization of reliability of renewable energy systems
      8. Demand constraints
      9. Supply constraints
    2. Mathematical programming
  5. RESULTS AND DISCUSSION
    1. Cooking energy needs
    2. Water heating energy needs
    3. Home lighting energy needs
    4. Water pumping energy needs
    5. Rural industries
    6. Home appliances
    7. Land required for biomass production for power generation in the Ungra village
    8. CO2 emissions for different scenarios in the Ungra village
    9. Employment potential in the Ungra village
    10. Associated costs and emissions under different scenarios
  6. CONCLUSION

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KEYWORDS and PACS

Keywords

energy resources, power system planning, sustainable development

PACS

ARTICLE DATA

History
Received 16 September 2008
Accepted 10 June 2009
Published 8 July 2009
Permalink
http://link.aip.org/link/JRSEBH/v1/i4/p043103/s1

PUBLICATION DATA

ISSN:

19417012 (print)  
19417012 (online)

Publisher:

$abstract.society.value is a Member of CrossRef American Institute of Physics

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Figures (6) Tables (6)

Figures (click on thumbnails to view enlargements)

FIG. 1
Energy allocations for cooking in the Ungra village under different scenarios.
FIG. 1 View Enlargement | Download High Resolution Image (.zip file)
FIG. 2
Allocations for water heating in the Ungra village under different scenarios.
FIG. 2 View Enlargement | Download High Resolution Image (.zip file)
FIG. 3
Energy allocations for home lighting in the Ungra village under different scenarios.
FIG. 3 View Enlargement | Download High Resolution Image (.zip file)
FIG. 4
Energy allocations for water pumping energy needs.
FIG. 4 View Enlargement | Download High Resolution Image (.zip file)
FIG. 5
Energy allocations for rural industries in the Ungra village for different scenarios.
FIG. 5 View Enlargement | Download High Resolution Image (.zip file)
FIG. 6
Energy allocations for home appliances in the Ungra village for different scenarios.
FIG. 6 View Enlargement | Download High Resolution Image (.zip file)

Tables

Table I. Energy resource allocation for the Ungra village under different scenarios.
Table II. CBG potential for the Ungra village under BAU and SDS.
Table III. Electricity use in kW h/capita/year and kW h/household/year under BAU and SDS in the Ungra village.
Table IV. Land required and wasteland availability for biomass production in the Ungra village.
Table V. CO2 emissions per capita under different scenarios.
Table VI. Associated costs, emissions, and employment under different scenarios.

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