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関連する概念動画

Quantifying Heat02:46

Quantifying Heat

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Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a...
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Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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Heating and Cooling Curves02:44

Heating and Cooling Curves

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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
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Heat Flow and Specific Heat01:12

Heat Flow and Specific Heat

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Heat is a type of energy transfer that is caused by a temperature difference, and it can change the temperature of an object. Since heat is a form of energy, its SI unit is the joule (J). Another common unit of energy often used for heat is the calorie (cal), which is defined as the energy needed to change the temperature of 1 g of water by 1 °C, specifically between 14.5 °C and 15.5 °C, since the energy needed shows a slight temperature dependence. Another commonly used unit is...
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Heat Engines01:10

Heat Engines

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A heat engine is a device used to extract heat from a source and then convert it into mechanical work used for various applications. For example, a steam engine on an old-style train can produce the work needed for driving the train.
Whenever we consider heat engines (and associated devices such as refrigerators and heat pumps), we do not use the standard sign convention for heat and work. For convenience, we assume that the symbols Qh, Qc, and W represent only the amounts of heat transferred...
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Load-frequency control01:28

Load-frequency control

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Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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関連する実験動画

Updated: Sep 10, 2025

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
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Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

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インドの石炭火力発電所806基の稼働ステーションの熱率に関するデータセット

Yifu Ding1, Jansen Wong2, Serena Patel1

  • 1MIT Energy Initiative, Massachusetts Institute of Technology, United States.

Data in brief
|August 21, 2025
PubMed
まとめ

この研究は機械学習を用いて インドの石炭火力発電所の効率性に関する包括的なデータセットを作成した. インドを裏付けています

キーワード:
石炭火力発電所インドの電力システム機械学習ステーションの熱率

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関連する実験動画

Last Updated: Sep 10, 2025

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科学分野:

  • エネルギー政策
  • 環境科学
  • 機械学習

背景:

  • インドは2070年までに排出をゼロにし,2030年までに再生可能エネルギーの500GWを目標としています.
  • 石炭発電は依然として支配的であり,2025年には発電能力の47%,発電量の70%以上を占める.
  • 既存の石炭火力発電所の脱炭素化は インドのエネルギー移行に不可欠です

研究 の 目的:

  • インドの石炭火力発電所の稼働率 (SHR) に関する包括的なデータ不足を解決する.
  • インドの石炭火力発電所806の最も広範なSHRデータセットを開発する.
  • インドの再生可能エネルギー目標のためのエネルギーと環境政策立案を支援する.

主な方法:

  • 既存のデータベースを活用して 石炭火力発電所の稼働データを作成しました
  • SHRデータセットを作成するために機械学習 (ML) モデルを使用しました.
  • 予測の精度を高めるため,水圧や石炭価格などの環境要因を組み込みました.

主要な成果:

  • インドの石炭火力発電所806基をカバーする包括的なデータセットを開発しました.
  • このデータセットは,熱効率の変動に関する詳細な洞察を提供します.
  • 統合された環境要因は,SHRの予測の精度を向上させました.

結論:

  • 作成されたSHRデータセットは,インドの石炭火力発電所にとってこれまでで最も包括的なものです.
  • このリソースは,石炭工場の効率を理解し,改善するのに役立ちます.
  • インドのエネルギーと環境政策の情報に基づいた意思決定を促進します.