Optimizing post-combustion CO2 capture in response to volatile electricity prices

Cohen, Stuart; Rochelle, Gary T.; Webber, Michael E.

doi:10.1016/j.ijggc.2012.02.011

Cited by 74 publications

(50 citation statements)

References 33 publications

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“…Even though the porosity increase of the rock cores occurred at the early stage of the reaction because of crack extension and perforation dominated by the dissolution, this was moderated within a few months, showing a logarithmic increase vs. reaction time (Figure 10a). The average dry density of the sandstone cores decreased from 2.390 to 2.384 g/cm 3 for 120 reaction days (0.25% decrease from the initial value) ( Table 5). The average seismic wave velocities of the sandstones also decreased in a logarithmic manner to 5.67% for P-wave and to 5.75% for S-wave from the initial values for 150 reaction days (Figure 10b and Table 5).…”

Section: Measurement Of the Surface Roughness Value For The Sandstonementioning

confidence: 99%

“…Various CO 2 capture and sequestration technologies have been developed to reduce CO 2 emissions and the International Energy Agency (IEA) has announced that CO 2 capture and sequestration (CCS) technology will cover 19% of the total CO 2 reductions by 2050 [1][2][3][4][5][6]. Among them, geological sequestration will be deeply considered to reduce CO 2 emissions at low cost [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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The Use of the Surface Roughness Value to Quantify the Extent of Supercritical CO2 Involved Geochemical Reaction at a CO2 Sequestration Site

et al. 2017

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Changes in the physical properties of the supercritical CO 2 (scCO 2 ) reservoir rock is one of the most important factors in controlling the storage safety at a scCO 2 sequestration site. According to recent studies, it is probable that geochemical reactions influence changes in the rock properties after a CO 2 injection in the subsurface, but quantitative data that reveal the interrelationship of the factors involved and the parameters needed to evaluate the extent of scCO 2 -rock-groundwater reactions have not yet been presented. In this study, the potential for employing the surface roughness value (SR RMS ) to quantify the extent of the scCO 2 involved reaction was evaluated by lab-scale experiments. For a total of 150 days of a simulation of the scCO 2 -sandstone-groundwater reaction at 100 bar and 50 • C, the trends in changes in the physical rock properties, pH change, and cation concentration change followed similar logarithmic patterns that were significantly correlated with the logarithmic increase in the SR RMS value. These findings suggest that changes in surface roughness can quantify the extent of the geochemical weathering process and can be used to evaluate leakage safety due to the progressive changes in rock properties at scCO 2 storage sites.

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Section: Measurement Of the Surface Roughness Value For The Sandstonementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Use of the Surface Roughness Value to Quantify the Extent of Supercritical CO2 Involved Geochemical Reaction at a CO2 Sequestration Site

et al. 2017

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“…However, existing studies have not carefully addressed the water impacts on a lifecycle basis; existing low-carbon studies do not broaden their outlook for new-generation CCS technologies [26,27]; the implementation of CCS may start with partial CO 2 capture in response to the EPA's proposed CO 2 emission regulations. In addition, flexibly operating CO 2 capture at partial load in response to volatile electricity prices could help maintain grid reliability and meet peak demand [28]. However, many studies look into the full CO 2 capture (90 %) via CCS for fossil-fuel-fired power plants rather than partial carbon capture; the feasibility of highly aggressive penetration (50-80 % of the fleet) of renewable energy in the future generation fleet needs further technical and economic assessments.…”

Section: Water Impacts Of Low-carbon Electricity Generationmentioning

confidence: 99%

Water Impacts of a Low-Carbon Electric Power Future: Assessment Methodology and Status

Zhai

Rubin

2015

Curr Sustainable Renewable Energy Rep

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Water is an integral element of energy production. Future US energy production will increasingly be driven by the need to mitigate climate change, posing complex water challenges. The water impacts of electricity generation in a carbon-constrained future have been a subject of active research. This paper reviews technologies and regulatory policy options for low-carbon electricity generation, including systems that use fossil fuels with carbon capture and storage, renewables such as wind, solar, and biomass, and nuclear energy. We also review cooling technologies in support of thermoelectric power generation, report and discuss current assessment methods and results on water use for low-carbon energy production, and identify adaptive approaches that could reinforce resilience for low-carbon electricity generation. Some recommendations are made for future research.

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“…CO 2 is one of the main gases that cause the greenhouse effect. Carbon capture and storage is the process of capturing and storing the CO 2 in industrial production by various means, such as cryogenic carbon capture [1,2], chemical absorption [3], oxyfuel combustion [4] and so on. Carbon capture technologies that result in significant reduction in energy-related CO 2 emissions, specifically from coal-fired power plants, can relieve the greenhouse effect.…”

Section: Introductionmentioning

confidence: 99%

Forecasting of Energy-Related CO2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability

2018

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Presently, China is the largest CO 2 emitting country in the world, which accounts for 28% of the CO 2 emissions globally. China's CO 2 emission reduction has a direct impact on global trends. Therefore, accurate forecasting of CO 2 emissions is crucial to China's emission reduction policy formulating and global action on climate change. In order to forecast the CO 2 emissions in China accurately, considering population, the CO 2 emission forecasting model using GM(1,1) (Grey Model) and least squares support vector machine (LSSVM) optimized by the modified shuffled frog leaping algorithm (MSFLA) (MSFLA-LSSVM) is put forward in this paper. First of all, considering population, per capita GDP, urbanization rate, industrial structure, energy consumption structure, energy intensity, total coal consumption, carbon emission intensity, total imports and exports and other influencing factors of CO 2 emissions, the main driving factors are screened according to the sorting of grey correlation degrees to realize feature dimension reduction. Then, the GM(1,1) model is used to forecast the main influencing factors of CO 2 emissions. Finally, taking the forecasting value of the CO 2 emissions influencing factors as the model input, the MSFLA-LSSVM model is adopted to forecast the CO 2 emissions in China from 2018 to 2025.

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Optimizing post-combustion CO2 capture in response to volatile electricity prices

Cited by 74 publications

References 33 publications

The Use of the Surface Roughness Value to Quantify the Extent of Supercritical CO2 Involved Geochemical Reaction at a CO2 Sequestration Site

The Use of the Surface Roughness Value to Quantify the Extent of Supercritical CO2 Involved Geochemical Reaction at a CO2 Sequestration Site

Water Impacts of a Low-Carbon Electric Power Future: Assessment Methodology and Status

Forecasting of Energy-Related CO2 Emissions in China Based on GM(1,1) and Least Squares Support Vector Machine Optimized by Modified Shuffled Frog Leaping Algorithm for Sustainability

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