CO2 capture and storage (CCS) cost reduction via infrastructure right-sizing

Carbon capture and storage (CCS) will be a critical component of a portfolio of low-carbon energy technologies required to combat climate change (Technology Roadmap, 2013). As such, an extensive transportation infrastructure will be required to transport captured CO2 from different sources to the available sinks. Several studies in the literature suggest that shared oversized pipeline networks may be the most efficient long term option compared to single source to sink pipelines, based on increased CCS deployment over the years and therefore increased CO2 flowrate to the transport network. However, what is neglected in this vision is that the deployment of intermittent renewable energy tends to displace thermal power generation. This directly reduces the amount of fossil fuel burned, CO2 produced, captured and transported through the network. This paper presents an optimisation methodology to “right-size” CO2 transport infrastructure, explicitly accounting for the transient flow of CO2 arising from the co-deployment of intermittent renewable energy generators. By application of this methodology, we demonstrate that capital cost reductions of up to 28% are possible relative to a business-as-usual design case

The role of CO2 purification and transport networks in carbon capture and storage cost reduction

A number of Carbon Capture and Storage projects (CCS) are under way around the world, but the technology's high capital and operational costs act as a disincentive to large-scale deployment. In the case of both oxy-combustion and post-combustion CO2 capture, the CO2 compression and purification units (CO2CPU) are vital, but costly, process elements needed to bring the raw CO2 product to a quality that is adequate for transport and storage. Four variants of the CO2CPU were modelled in Aspen HYSYS each of which provide different CO2 product purities at different capital and operating costs. For each unit, a price of CO2 is calculated by assuming that it is an independent entity in which to invest and the internal rate of return (IRR) must be greater or equal to the minimum rate of return on investment. In this study, we test the hypothesis that, owing to the fact that CO2 will likely be transported in multi-source networks, not all CO2 streams will need to be of high purity, and that it may be possible to combine several sources of varying purity to obtain an end-product that is suitable for storage. We find that, when considering study generated costs for an example network in the UK, optimally combining these different sources into one multi-source transport network subject to a minimum CO2 purity of 96% can reduce the price of captured CO2 by 17%

Process control strategies for flexible operation of post-combustion CO2 capture plants

With increasing penetration of intermittent renewable energy into the electricity grid, one can expect thermal power plants to be required to operate in a more dynamic fashion, with more frequent departures from design point operation. However, the application of optimal control strategies can offer solutions to these operational challenges, associated with the integration of the power plant with the capture plant. In this paper a process control strategy is developed in order to select the optimal control variables for a PCC process. In addition, economically efficient control structures for operation of a post-combustion capture process with minimum energy requirements for coal and natural gas power plant are designed. The results have shown that with an appropriate and well-tuned control strategy, it is possible to maintain critical parameters, such as the degree of CO2 capture, at the desired set-point, even during periods of significant fluctuation in the power plant load and even if based on simple and well established control technologies, such as PID, avoids the need for more risky solutions such as adding solvent storage tanks to the process

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP- PCC system and fully exert its functions in power generation and CO2 reduction

Operational flexibility options in power plants with integrated post-combustion capture

Flexibility in power plants with amine based carbon dioxide (CO2) capture is widely recognised as a way of improving power plant revenues. Despite the prior art, its value as a way to improve power plant revenues is still unclear. Most studies are based on simplifying assumptions about the capabilities of power plants to operate at part load and to regenerate additional solvent after interim storage of solvent. This work addresses this gap by examining the operational flexibility of supercritical coal power plants with amine based CO2 capture, using a rigorous fully integrated model. The part-load performance with capture and with additional solvent regeneration, of two coal-fired supercritical power plant configurations designed for base load operation with capture, and with the ability to fully bypass capture, is reported. With advanced integration options configuration, including boiler sliding pressure control, uncontrolled steam extraction with a floating crossover pressure, constant stripper pressure operation and compressor inlet guide vanes, a significant reduction of the electricity output penalty at part load is observed. For instance at 50% fuel input and 90% capture, the electricity output penalty reduces from 458 kWh/tCO2 (with conventional integration options) to 345 kWh/tCO2 (with advanced integration options), compared to a reduction from 361 kWh/tCO2 to 342 kWh/tCO2 at 100% fuel input and 90% capture. However, advanced integration options allow for additional solvent regeneration to a lower magnitude than conventional integration options. The latter can maintain CO2 flow export within 10% of maximum flow across 30–78% of MCR (maximum continuous rating). For this configuration, one hour of interim solvent storage at 100% MCR is evaluated to be optimally regenerated in 4 h at 55% MCR, and 3 h at 30% MCR, providing rigorously validated useful guidelines for the increasing number of techno-economic studies on power plant flexibility, and CO2 flow profiles for further studies on integrated CO2 networks

Techno-economic assessment of CO2 quality effect on its storage and transport: CO2QUEST: An overview of aims, objectives and main findings

This paper provides an overview of the aims, objectives and the main findings of the CO2QUEST FP7 collaborative project, funded by the European Commission and designed to address the fundamentally important and urgent issues regarding the impact of the typical impurities in CO2 streams captured from fossil fuel power plants and other CO2 intensive industries on their safe and economic pipeline transportation and storage. The main features and results recorded from some of the unique test facilities constructed as part of the project are presented. These include an extensively instrumented realistic-scale test pipeline for conducting pipeline rupture and dispersion tests in China, an injection test facility in France to study the mobility of trace metallic elements contained in a CO2 stream following injection near a shallow-water qualifier and fluid/rock interactions and well integrity experiments conducted using a fully instrumented deep-well CO2/impurities injection test facility in Israel. The above, along with the various unique mathematical models developed, provide the fundamentally important tools needed to define impurity tolerance levels, mixing protocols and control measures for pipeline networks and storage infrastructure, thus contributing to the development of relevant standards for the safe design and economic operation of CCS

Nonlinear dynamic analysis and control design of a solvent-based post-combustion CO2 capture process

A flexible operation of the solvent-based post-combustion CO2capture (PCC) process is of great importance to make the technology widely used in the power industry. However, in case of a wide range of operation, the presence of process nonlinearity may degrade the performance of the pre-designed linear controller. This paper gives a comprehensive analysis of the dynamic behavior and nonlinearity distribution of the PCC process. Three cases are taken into account during the investigation: 1) capture rate change; 2) flue gas flowrate change; and 3) re-boiler temperature change. The investigations show that the CO2capture process does have strong nonlinearity; however, by selecting a suitable control target and operating range, a single linear controller is possible to control the capture system within this range. Based on the analysis results, a linear model predictive controller is designed for the CO2capture process. Simulations of the designed controller on an MEA based PCC plant demonstrate the effectiveness of the proposed control approach

Flexible operation of post-combustion CO2 capture at pilot scale with demonstration of capture-efficiency control using online solvent measurements

Flexible post-combustion carbon capture and storage (CCS) has the potential to play a significant part in the affordable decarbonisation of electricity generation portfolios. PCC plant operators can modify capture plant process variables to adjust the CO2 capture level to a value which is optimal for current fuel cost, electricity selling price and CO2 emissions costs, increasing short-term profitability. Additionally, variation of the level of steam extraction from the generation plant can allow the capture facility to provide additional operating flexibility for coal-fired power stations which are comparatively slow to change output. A pilot-scale test campaign investigates the response of plant operating parameters to dynamic scenarios which are designed to be representative of pulverized coal plant operation. Online sensors continuously monitor changes in rich and lean solvent CO2 loading (30%wt monoethanolamine). Solvent loading is likely to be a critical control variable for the optimisation of flexible PCC operation, and since economic and operational boundaries can change on timescales 30mins or shorter, the development of methods for rapid, continuous online solvent analysis is key. Seven dynamic datasets are produced and insights about plant response times and hydrodynamics are provided. These include power output maximization, frequency response, power output ramping and a comparison between two plant start-up strategies. In the final dynamic operating scenario, control of CO2 capture efficiency for a simple reboiler steam decoupling and reintroduction event is demonstrated using only knowledge of plant hydrodynamics and continuous measurement of solvent lean loading. Hot water flow to the reboiler is reduced to drop the capture efficiency. The “target” value for the minimum capture efficiency in the scenario was set at 30%, but a minimum CO2 capture efficiency of 26.4% was achieved. While there remains scope for improvement this represents a significant practical step towards the control of capture plant using online solvent concentration and CO2 measurements, and the next steps for its further development are discussed

Optimal design and operation of distributed energy systems: application to greek residential sector

In the present dissertation, the optimal design, operation and control of a distributed energy systems, which incorporates photovoltaic systems, combined heat and power engines (CHP) and electricity and heat storage devices, is under study. The model allows importing electricity from the national grid, while back-up boilers produce heat when the heat produced by the CHP units does not satisfy the needs. Moreover, heat is transferred between dwellings through a heating pipeline network. A new neural network model for the calculation of the hourly global solar irradiance on a tilted surface for the region of Athens was developed, based on neural networks of radial basis function (RBF). The neural network model, predicts more realistically the total solar irradiance on a tilted surface compared to the linear models.A new methodology is developed for the optimal calculation of the inclination and orientation of photovoltaic systems, also based on neural network techniques.Τhe mixed-integer linear model (MILP) which was developed for the design and evaluation of distributed energy systems in Greece, has shown great advantages compared to the conventional system from an economical and environmental point of view, compared to the conventional systems.We examine the adoption of distributed energy technologies in combination with the design of a heating pipeline network and electricity transmission lines. The heating pipeline network is examined in detail with the integration of mass balances and two transfer lines (feed and return).The Model Predictive Control (MPC) rolling horizon approach is adopted to design a control strategy for DER systems. The MPC problem that is solved in each time period is formulated as a Mixed Integer Linear Programming (MILP) model.Στην διδακτορική διατριβή, μελετήθηκε ο σχεδιασμός, η βελτιστοποίηση της λειτουργίας και η ρύθμιση συστήματος διεσπαρμένης παραγωγής ενέργειας, που περιλαμβάνει φωτοβολταϊκά συστήματα, μηχανές συμπαραγωγής θερμότητας και ηλεκτρισμού και μονάδες αποθήκευσης θερμότητας και ηλεκτρισμού, ενώ παράλληλα δίνεται η δυνατότητα αγοράς ηλεκτρικής ενέργειας από το δίκτυο, η παραγωγή θερμότητας με χρήση μπόιλερ και η μεταφορά θερμότητας μεταξύ των χρηστών μέσω του σχεδιασμού κατάλληλου δικτύου μεταφοράς θερμότητας. Αναπτύχθηκε νέο μοντέλο πρόβλεψης της ηλιακής ακτινοβολίας για την περιοχή της Αθήνας χρησιμοποιώντας την αρχιτεκτονική των τεχνητών νευρωνικών δικτύων ακτινικής συνάρτησης βάσης (Radial Basis Function, RBF), ενώ η σύγκριση των αποτελεσμάτων με τα υπόλοιπα μοντέλα της βιβλιογραφίας που εξετάστηκαν και αξιολογήθηκαν, κατέδειξε την υπεροχή του προτεινόμενου μοντέλου.Αναπτύχθηκε μια νέα μεθοδολογία για τον ακριβή υπολογισμό της γωνίας κλίσης και της κατεύθυνσης των ηλιακών φωτοβολταϊκών συστημάτων, βασιζόμενη επίσης στη μεθοδολογία των τεχνητών νευρωνικών δικτύων.Παρουσιάστηκε πρωτότυπο μοντέλο μεικτού ακεραίου γραμμικού προγραμματισμού (MILP-Mixed Integer Linear Programming), για το βέλτιστο σχεδιασμό και την αξιολόγηση των συστημάτων διεσπαρμένης παραγωγής ενέργειας. Τα αποτελέσματα από την εφαρμογή του μοντέλου σε δεδομένα από το ενεργειακό περιβάλλον στην Ελλάδα καταδεικνύουν τα σημαντικά πλεονεκτήματα, τόσο ως προς το κόστος λειτουργίας όσο και ως προς τα περιβαλλοντολογικά οφέλη αυτών των συστημάτων σε σχέση με τα συμβατικά κεντρικά συστήματα παραγωγής ενέργειας.Εξετάστηκε ακόμη ο συνδυασμός των τεχνολογιών διεσπαρμένης παραγωγής ενέργειας με ένα δίκτυο μεταφοράς θερμότητας και γραμμών μεταφοράς ηλεκτρικής ενέργειας. Το δίκτυο μεταφοράς θερμότητας μελετήθηκε λεπτομερώς με την ενσωμάτωση ισοζυγίων μάζας και δύο γραμμών μεταφοράς (τροφοδοσίας και συλλογής).Αναπτύχθηκε μία στρατηγική λήψης αποφάσεων για τη βέλτιστη λειτουργία του συστήματος διεσπαρμένης παραγωγής ενέργειας που βασίζεται στη φιλοσοφία του μοντέλου προβλεπτικού ελέγχου (Model Predictive Control-MPC). Το μοντέλο προβλεπτικού ελέγχου που επιλύεται για κάθε χρονική περίοδο διαμορφώνεται σαν ένα μοντέλο μεικτού ακέραιου γραμμικού προγραμματισμού