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Impact of Climate Change on Small Scale Hydro-Turbine Selections
Impact of Climate Change on Small Scale Hydro-Turbine Selections
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Hydropower is found to be one of the most reliable and inexpensive options for renewable energy which was now widely been adopted by many countries to substitute fossil fuel sources. This Brief highlights the impact of climate change on hydropower plants, especially on the turbine design, as turbines are responsible for optimal conversion and regular energy production. The vulnerability of turbines is analyzed with the help of Artificial Neural Networks, followed by Multi Criteria Decision Maki…
  • Leidėjas:
  • ISBN-10: 9812872388
  • ISBN-13: 9789812872388
  • Formatas: 15.6 x 23.4 x 0.3 cm, minkšti viršeliai
  • Kalba: Anglų

Impact of Climate Change on Small Scale Hydro-Turbine Selections (el. knyga) (skaityta knyga) | knygos.lt

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Hydropower is found to be one of the most reliable and inexpensive options for renewable energy which was now widely been adopted by many countries to substitute fossil fuel sources. This Brief highlights the impact of climate change on hydropower plants, especially on the turbine design, as turbines are responsible for optimal conversion and regular energy production. The vulnerability of turbines is analyzed with the help of Artificial Neural Networks, followed by Multi Criteria Decision Making methods for development of intelligent indices to represent the level of vulnerability of turbines due to the change in climate.

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  • Autorius: Uttam Roy
  • Leidėjas:
  • ISBN-10: 9812872388
  • ISBN-13: 9789812872388
  • Formatas: 15.6 x 23.4 x 0.3 cm, minkšti viršeliai
  • Kalba: Anglų

Hydropower is found to be one of the most reliable and inexpensive options for renewable energy which was now widely been adopted by many countries to substitute fossil fuel sources. This Brief highlights the impact of climate change on hydropower plants, especially on the turbine design, as turbines are responsible for optimal conversion and regular energy production. The vulnerability of turbines is analyzed with the help of Artificial Neural Networks, followed by Multi Criteria Decision Making methods for development of intelligent indices to represent the level of vulnerability of turbines due to the change in climate.

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