scholarly journals Quasi steady-state models for long-term voltage and frequency dynamics simulation

2005 ◽  
Author(s):  
Marie-Eve Grenier ◽  
Daniel Lefebvre ◽  
Thierry Van Cutsem
Keyword(s):  
Steady State ◽  
Dynamics Simulation ◽  
Quasi Steady State ◽  
State Models

Comparison of Unsteady State and Quasi Steady State Modeling for Hydrocarbons in a Monolithic Catalytic Converter

2008 ◽  
Vol 6 (1) ◽  
Author(s):  
Sanchita Chauhan ◽  
V. K. Srivastava
Keyword(s):  
Steady State ◽  
Numerical Solutions ◽  
Catalyst Surface ◽  
Catalytic Converter ◽  
Heterogeneous Reactions ◽  
Exhaust Gas ◽  
Quasi Steady State ◽  
Unsteady State ◽  
Heat And Mass Transport ◽  
State Models

In this study numerical solutions are obtained using quasi steady state and unsteady state conditions to predict the reduction in concentrations of polluting hydrocarbons. Before their release to the atmosphere these gases undergo catalytic after-treatment in a converter, causing a decrease in their concentrations. Both homogenous as well as heterogeneous reactions are considered for hydrocarbons propylene and propane. Quasi steady and unsteady state models are developed to simulate heat and mass transfer between the exhaust gas and the catalyst surface, convective heat and mass transport, chemical reactions and the related heat release along with heat conduction in the substrate.

A Long-Term Frequency Dynamic Simulation Method of Power System with the Wind Farm Based on Quasi-Steady State Simulation

2013 ◽  
Vol 385-386 ◽  
pp. 1011-1016
Author(s):  
Ying Yun Sun ◽  
Zhao Yu Jin ◽  
Tian Jiao Pu ◽  
Ting Yu ◽  
Wei Wang ◽  
...  
Keyword(s):  
Steady State ◽  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Frequency Control ◽  
Simulation Method ◽  
Quasi Steady State ◽  
Term Frequency ◽  
The Impact

With the continuous improvement of wind power penetration, the impact of the random fluctuation characteristics of wind power on the frequency control of the power system is growing. Currently, researchers began to study the methods of wind farms participation in frequency control to reduce the frequency adjustment pressure of other power plants and increase the wind power penetration. However, the existing simulation software for the short and long term frequency control of the power system is not so good. So in order to analyze the impact of load fluctuations or wind farm power fluctuations on system frequency control, this paper propose a frequency fluctuation simulation method based on the quasi-steady-state method.

scholarly journals Severe Weather-Induced Exchange Flows through a Narrow Tidal Channel of Calcasieu Lake Estuary

2020 ◽  
Vol 8 (2) ◽  
pp. 113
Author(s):  
Jie Wang ◽  
Chunyan Li ◽  
Fumin Xu ◽  
Wei Huang
Keyword(s):  
Steady State ◽  
Regression Model ◽  
Water Level ◽  
Severe Weather ◽  
Quasi Steady State ◽  
Velocity Data ◽  
Exchange Flows ◽  
Cold Fronts ◽  
Steady State Balance

Exchange flows between estuaries and the coastal ocean are important for land-ocean interactions and ecosystem health. This study is aimed at resolving severe weather-induced exchange flows between the Calcasieu Lake Estuary and Gulf of Mexico. For that purpose, we use data from a long-term deployment of side-looking acoustic Doppler current profilers (ADCPs) and conductivity-temperature-depth sensors (CTDs) as well as flow velocity data from a boat operated survey. Regression between the transport measured from a boat mounted ADCP and the velocity data from a fixed side-looking ADCP is done to calculate a long-term transport along the Calcasieu Pass. Analyses have been done for the hydrodynamic response to 16 cold fronts passing the study area. Effects of six strongest cold fronts are discussed in more detail. Results have confirmed that the hydrodynamics is highly correlated with the frequent cold fronts. The highest correlation coefficient is r ~0.75 between the north wind and along channel transport. In general, winds from the southern quadrants push water into the estuary before each frontal passage; after the passage of the front, a rapid change of wind direction to the northern quadrants produces strong outward flows. A quasi-steady state balance between the wind stress and water level difference proposed in recent studies for different systems is further confirmed and discussed in this system. The quasi-steady state balance leads to a relatively high R2 value of greater than 0.8 between the modeled water level gradient and actual observed gradient. We have also applied a regression model, derived from the momentum balance requirement, for the subtidal exchange flow as a function of wind components and their squares which yield an R2 value greater than 0.7. With a confidence in the regression model, we further implement it for twelve years from 26 February 2007 to 10 April 2019. Four extreme events during this 12-year period of time are discussed–they include the Hurricane Ike (2008), Tropical Storm Lee (2011), a warm front, and a cold front. This hindcast of the exchange flows over multiple years can provide a useful tool for coastal management and research for estuarine channels where continuous observations of velocity are not always available.

Atmospheric Carbon Dioxide over Phanerozoic Time

2004 ◽  
Author(s):  
Robert A. Berner
Keyword(s):  
Organic Matter ◽  
Steady State ◽  
Carbon Cycle ◽  
Atmospheric Carbon Dioxide ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Burial Flux ◽  
State Models ◽  
Fundamental Equations

In this chapter the methods and results of modeling the long-term carbon cycle are presented in terms of predictions of past levels of atmospheric CO2. The modeling results are then compared with independent determinations of paleo-CO2 by means of a variety of different methods. Results indicate that there is reasonable agreement between methods as to the general trend of CO2 over Phanerozoic time. Values of fluxes in the long-term carbon cycle can be calculated from the fundamental equations for total carbon and 13C mass balance that are stated in the introduction and are repeated here: . . . dMc/dt = Fwc + Fwg + Fmc + Fmg – Fbc – Fbg (1.10) . . . . . . d(δcMc)/dt = δwcFwc + δwgFwg + δmcFmc + δmgFmg – δbcFbc – δbgFbg (1.11) . . . where Mc = mass of carbon in the surficial system consisting of the atmosphere, oceans, biosphere, and soils Fwc = flux from weathering of Ca and Mg carbonates Fwg = flux from weathering of sedimentary organic matter Fmc = degassing flux for carbonates from volcanism, metamorphism, and diagenesis Fmg = degassing flux for organic matter from volcanism, metamorphism, and diagenesis Fbc = burial flux of carbonates in sediments Fbg = burial flux of organic matter in sediments δ = [(13C/12C)/(13C/12C)stnd – 1]1000. Variants of equations (1.10) and (1.11) have been treated in terms of non–steady-state modeling (e.g., Berner et al., 1983; Wallmann, 2001; Hansen and Wallmann, 2003; Mackenzie et al., 2003; Bergman et al., 2003), where the evolution of both oceanic and atmospheric composition, including Ca, Mg, and other elements in seawater, is tracked over time. However, since the purpose of this book is to discuss the carbon cycle with respect to CO2 and O2, and so as not to overburden the reader with too many mathematical expressions, I discuss only those aspects of the non–steady-state models that directly impact carbon. These are combined with results from steady-state strictly carbon-cycle modeling (Garrels and Lerman, 1984; Berner, 1991, 1994; Kump and Arthur, 1997; Francois and Godderis, 1998; Tajika, 1998; Berner and Kothavala, 2001; Kashiwagi and Shikazono, 2002).

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