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Thermal Energy Mapping for Net-Zero Carbon Emission

  • Sheetal Shinkhede,
  • Sanskriti Mujumdar

摘要

The demand for electricity is a major indicator of a country’s economic growth. Technological development and environmental factors significantly contribute to the increasing demand for electricity. In India generation of electrical energy is from thermal, hydro, nuclear, and renewable sources. The major contributor is thermal energy. Coal, oil, and gas are the main sources that are also called fossil fuels. The burning of fossil fuels emits CO2 and other pollutants. Since the industrial revolution, CO2 emission has increased drastically. But due to technological development, advanced power generation technologies, and a rise in per capita income, there is a rise in residential energy consumption too. The incorporation of renewable energy is the solution to reducing the use of fossil fuels for the generation of electrical energy, thereby lowering carbon emissions. But the integration of renewable energy into the existing grid is a challenge. Due to this, the security and reliability of the power system may be at stack. It is essential to understand the energy consumption pattern, region-wise. Many research studies have been presented, to determine energy consumption efficiency in urban cities, but the construction of a thermal energy map that shows land surface temperature (LST) for a specific urban city and energy consumption has not been considered. Therefore, this research generates a thermal energy map that shows the relation between temperature and energy consumption of Vadodara city in Gujarat. The thermal map (LST) is obtained from LSTSat8 data and energy consumption is determined by a fuzzy logic model with three linguistic variables that provide effective decisions to manage the electricity demand in four zones of Vadodara city. The thermal energy mapping can be replicated in developing countries for any region of similar climatic conditions. With this mapping, heat pockets and energy consumption can be studied, and policies can be suggested to reduce the electricity demand with proper planning management.