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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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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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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Carbon dioxide fixation in prokaryotes enables the assimilation of inorganic carbon into organic molecules, supporting biosynthetic pathways, sustaining ecosystems, and contributing to the global carbon cycle. It also has industrial applications in carbon capture and bioproduct synthesis. Autotrophic organisms rely on this process to utilize CO₂ as a carbon source in diverse environments.The Calvin CycleThe Calvin cycle is the most widespread carbon fixation mechanism, primarily used by...
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An interval chance-constrained programming-based optimization model for carbon capture, utilization, and storage

Mingyang Zhai1, Haifeng Jia1, Dingkun Yin1

  • 1School of Environment, Tsinghua University, Beijing 100084, China.

The Science of the Total Environment
|March 27, 2021
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Summary

This study introduces an optimization model for carbon capture, utilization, and storage (CCUS) to manage uncertainties and costs. It helps policymakers balance CO2 reduction, system reliability, and project benefits.

Keywords:
CO(2) compressionCarbon capture, utilization, and storageChance-constrained programmingEnhanced oil recoveryInterval linear programmingUncertainties

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Area of Science:

  • Environmental Engineering
  • Operations Research
  • Climate Change Mitigation

Background:

  • Carbon capture, utilization, and storage (CCUS) is vital for reducing industrial CO2 emissions.
  • High costs and uncertainties impede widespread CCUS adoption.
  • Existing models struggle with probabilistic distributions and dynamic capacity expansion.

Purpose of the Study:

  • To develop an optimization model addressing uncertainties in CCUS projects.
  • To analyze trade-offs between system reliability, CO2 storage, and economic benefits.
  • To aid policymakers in strategic CCUS system management and operational planning.

Main Methods:

  • An interval-chance-constrained programming (ICCP) optimization model was developed.
  • The model was applied to a CCUS project in China.
  • Various violation probability levels were used to generate cost, capacity, and operational schemes.

Main Results:

  • Highest reliability and CO2 storage (4972.05-5429.75 ktpa) occurred at a 0.01 violation probability, with costs at $166.57 million.
  • Maximum net system benefits ($135.45 million) were achieved at a 0.05 violation probability, with reduced CO2 storage (4090.01-4653.24 ktpa) and costs ($138.62 million).
  • The model demonstrates the trade-offs between system reliability, CO2 reduction targets, and project profitability.

Conclusions:

  • The ICCP model effectively manages uncertainties in CCUS system management.
  • Policymakers can use the findings to make informed decisions on CCUS project development and operation.
  • The approach supports adaptive strategies for facility expansion and operational planning in CCUS.