Inderscience Publishers

An optimal energy allocation model using fuzzy linear programming for energy planning in India for the year 2020

0
- By: ,

Courtesy of Inderscience Publishers

Development of an energy allocation model will help in the proper allocation of the energy sources in meeting the future energy demand in India. In this paper, an attempt has been made to develop a fuzzy-based linear programming optimal energy model that minimises the cost and determines the optimum allocation of different energy sources for the centralised and decentralised power generation in India. The potential, energy demand, efficiency, emission and carbon tax are used as constraints in the model. The model allocates the energy distribution pattern for the year 2020 in India. The results indicate that the energy distribution pattern would be 15 800 GWh (4%) from the coal-based plants, 85 400 GWh (20%) from the nuclear plants, 191 100 GWh (44%) from the hydro plants, 22 400 GWh (5%) from the wind turbine generators, 45 520 GWh (11%) from the biomass gasifier plants, 14 112 GWh (3%) from the biogas plants, 8400 GWh (2%) from the solid waste, 33 600 GWh (8%) from the cogeneration plants and 11 970 GWh (3%) from the mini-hydel plants, for the year 2020. A sensitivity analysis has been done to validate the OEAM model. This study will help in the formation of strategies for the effective utilisation of energy sources in India.

Keywords: energy planning, optimisation model, energy scenarios, sensitivity analysis, energy allocation modelling, fuzzy linear programming, future energy demand, India, power generation, power systems, energy sources, energy distribution patterns, nuclear energy, nuclear power, coal plants, biomass, biogas, solid waste, biodiesel, cogeneration, wind energy, wind power, tidal energy, tidal power, geothermal, mini-hydel, fuel cells, MHD

Customer comments

No comments were found for An optimal energy allocation model using fuzzy linear programming for energy planning in India for the year 2020. Be the first to comment!