Dynamic behavior investigations and disturbance rejection predictive control of solvent-based post-combustion CO2 capture process

Increasing demand for flexible operation has posed significant challenges to the control system design of solvent-based post-combustion CO2 capture (PCC) process: 1) the capture system itself has very slow dynamics; 2) in the case of wide range of operation, dynamic behavior of the PCC process will change significantly at different operating points; and 3) the frequent variation of upstream flue gas flowrate will bring in strong disturbances to the capture system. For these reasons, this paper provides a comprehensive study on the dynamic characteristics of the PCC process. The system dynamics under different CO2 capture rates, re-boiler temperatures, and flue gas flow rates are analyzed and compared through step-response tests. Based on the in-depth understanding of the system behavior, a disturbance rejection predictive controller (DRPC) is proposed for the PCC process. The predictive controller can track the desired CO2 capture rate quickly and smoothly in a wide operating range while tightly maintaining the re-boiler temperature around the optimal value. Active disturbance rejection approach is used in the predictive control design to improve the control property in the presence of dynamic variations or disturbances. The measured disturbances, such as the flue gas flow rate, is considered as an additional input in the predictive model development, so that accurate model prediction and timely control adjustment can be made once the disturbance is detected. For unmeasured disturbances, including model mismatches, plant behavior variations, etc., a disturbance observer is designed to estimate the value of disturbances. The estimated signal is then used as a compensation to the predictive control signal to remove the influence of disturbances. Simulations on a monoethanolamine (MEA) based PCC system developed on gCCS demonstrates the excellent effect of the proposed controller

Reinforced coordinated control of coal-fired power plant retrofitted with solvent based CO2 capture using model predictive controls

Solvent-based post-combustion CO2 capture (PCC) provides a promising technology for the CO2 removal of coal-fired power plant (CFPP). However, there are strong interactions between the CFPP and the PCC system, which makes it challenging to attain a good control for the integrated plant. The PCC system requires extraction of large amounts of steam from the intermediate/low pressure steam turbine to provide heat for solvent regeneration, which will reduce power generation. Wide-range load variation of power plant will cause strong fluctuation of the flue gas flow and brings in a significant impact on the PCC system. To overcome these issues, this paper presents a reinforced coordinated control scheme for the integrated CFPP-PCC system based on the investigation of the overall plant dynamic behavior. Two model predictive controllers are developed for the CFPP and PCC plants respectively, in which the steam flow rate to re-boiler and the flue-gas flow rate are considered as feed-forward signals to link the two systems together. Three operating modes are considered for designing the coordinated control system, which are: (1) normal operating mode; (2) rapid power load change mode; and (3) strict carbon capture mode. The proposed coordinated controller can enhance the overall performance of the CFPP-PCC plant and achieve a flexible trade-off between power generation and CO2 reduction. Simulation results on a small-scale subcritical CFPP-PCC plant developed on gCCS demonstrates the effectiveness of the proposed controller

Variational approximation for mixtures of linear mixed models

Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm. The conventional approach to determining a suitable number of components is to compare different mixture models using penalized log-likelihood criteria such as BIC.We propose fitting MLMMs with variational methods which can perform parameter estimation and model selection simultaneously. A variational approximation is described where the variational lower bound and parameter updates are in closed form, allowing fast evaluation. A new variational greedy algorithm is developed for model selection and learning of the mixture components. This approach allows an automatic initialization of the algorithm and returns a plausible number of mixture components automatically. In cases of weak identifiability of certain model parameters, we use hierarchical centering to reparametrize the model and show empirically that there is a gain in efficiency by variational algorithms similar to that in MCMC algorithms. Related to this, we prove that the approximate rate of convergence of variational algorithms by Gaussian approximation is equal to that of the corresponding Gibbs sampler which suggests that reparametrizations can lead to improved convergence in variational algorithms as well.Comment: 36 pages, 5 figures, 2 tables, submitted to JCG

Interacting new agegraphic Phantom model of dark energy in non-flat universe

In this paper we consider the new agegraphic model of interacting dark energy in non-flat universe. We show that the interacting agegraphic dark energy can be described by a phantom scalar field. Then we show this phantomic description of the agegraphic dark energy and reconstruct the potential of the phantom scalar field.Comment: 8 pages, no figur

New Agegraphic Dark Energy in f(R)f(R) Gravity

In this paper we study cosmological application of new agegraphic dark energy density in the $f(R)$ gravity framework. We employ the new agegraphic model of dark energy to obtain the equation of state for the new agegraphic energy density in spatially flat universe. Our calculation show, taking $n<0$, it is possible to have $w_{\rm \Lambda}$ crossing -1. This implies that one can generate phantom-like equation of state from a new agegraphic dark energy model in flat universe in the modified gravity cosmology framework. Also we develop a reconstruction scheme for the modified gravity with $f(R)$ action.Comment: 8 pages, no figur

A New Type of Dark Energy Model

In this paper, we propose a general form of the equation of state (EoS) which is the function of the fractional dark energy density $\Omega_{d}$. At least, five related models, the cosmological constant model, the holographic dark energy model, the agegraphic dark energy model, the modified holographic dark energy model and the Ricci scalar holographic dark energy model are included in this form. Furthermore, if we consider proper interactions, the interactive variants of those models can be included as well. The phase-space analysis shows that the scaling solutions may exist both in the non-interacting and interacting cases. And the stability analysis of the system could give out the attractor solution which could alleviate the coincidence problem.Comment: Minor modifications, references adde

Probing interaction and spatial curvature in the holographic dark energy model

In this paper we place observational constraints on the interaction and spatial curvature in the holographic dark energy model. We consider three kinds of phenomenological interactions between holographic dark energy and matter, i.e., the interaction term $Q$ is proportional to the energy densities of dark energy ($\rho_{\Lambda}$), matter ($\rho_{m}$), and matter plus dark energy ($\rho_m+\rho_{\Lambda}$). For probing the interaction and spatial curvature in the holographic dark energy model, we use the latest observational data including the type Ia supernovae (SNIa) Constitution data, the shift parameter of the cosmic microwave background (CMB) given by the five-year Wilkinson Microwave Anisotropy Probe (WMAP5) observations, and the baryon acoustic oscillation (BAO) measurement from the Sloan Digital Sky Survey (SDSS). Our results show that the interaction and spatial curvature in the holographic dark energy model are both rather small. Besides, it is interesting to find that there exists significant degeneracy between the phenomenological interaction and the spatial curvature in the holographic dark energy model.Comment: 11 pages, 5 figures; to appear in JCA

Interacting New Agegraphic Dark Energy in a Cyclic Universe

The main goal of this work is investigation of NADE in the cyclic universe scenario. Since, cyclic universe is explained by a phantom phase ($\omega<-1$), it is shown when there is no interaction between matter and dark energy, ADE and NADE do not produce a phantom phase, then can not describe cyclic universe. Therefore, we study interacting models of ADE and NADE in the modified Friedmann equation. We find out that, in the high energy regime, which it is a necessary part of cyclic universe evolution, only NADE can describe this phantom phase era for cyclic universe. Considering deceleration parameter tells us that the universe has a deceleration phase after an acceleration phase, and NADE is able to produce a cyclic universe. Also it is found valuable to study generalized second law of thermodynamics. Since the loop quantum correction is taken account in high energy regime, it may not be suitable to use standard treatment of thermodynamics, so we turn our attention to the result of \citep{29}, which the authors have studied thermodynamics in loop quantum gravity, and we show that which condition can satisfy generalized second law of thermodynamics.Comment: 8 pages, 3 figure

Reconstructing interacting new agegraphic polytropic gas model in non-flat FRW universe

We study the correspondence between the interacting new agegraphic dark energy and the polytropic gas model of dark energy in the non-flat FRW universe. This correspondence allows to reconstruct the potential and the dynamics for the scalar field of the polytropic model, which describe accelerated expansion of the universe.Comment: 9 page