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

Global Sensitivity Analysis for Design and Operation of Distributed Energy Systems

Distributed Energy Systems (DES) are set to play a vital role in achieving emission targets and meeting higher global energy demand by 2050. However, implementing these systems has been challenging, particularly due to uncertainties in local energy demand and renewable energy generation, which imply uncertain operational costs. In this work we are implementing a Mixed-Integer Linear Programming (MILP) model for the operation of a DES, and analysing impacts of uncertainties in electricity demand, heating demand and solar irradiance on the main model output, the total daily operational cost, using Global Sensitivity Analysis (GSA). Representative data from a case study involving nine residential areas at the University of Surrey are used to test the model for the winter season. Distribution models for uncertain variables, obtained through statistical analysis of raw data, are presented. Design results show reduced costs and emissions, whilst GSA results show that heating demand has the largest influence on the variance of total daily operational cost. Challenges and design limitations are also discussed. Overall, the methodology can be easily applied to improve DES design and operation

Analysis and evaluation of models predicting the components of global solar irradiance on horizontal surfaces - development of a new empirical model

168 σ.Στην παρούσα εργασία έγινε αρχικά παρουσίαση διαφόρων βιβλιογραφικών συσχετίσεων προσδιορισμού της διάχυτης ακτινοβολίας, όπως η συσχέτιση του Page, του Erbs, των Orgill and Hollands, του Reindl και της Καρατάσου. Οι συσχετίσεις αυτές συγκρίθηκαν μεταξύ τους και με τις καταγεγραμμένες τιμές διάχυτης ακτινοβολίας και έγινε ποιοτική ανάλυση διαμέσου διαγραμμάτων για τις τέσσερις εποχές του έτους και τέσσερις χαρακτηριστικούς τύπους ημερών (ηλιόλουστη, με λίγα σύννεφα, συννεφιασμένη και βροχερή). Στη συνέχεια με τη χρήση των δεδομένων του έτους 2004 για την Αθήνα εξήχθη ένα πολυωνυμικό μοντέλο 2ου βαθμού με διαχωρισμό δύο διαστημάτων μεταξύ του συντελεστή αιθριότητας KT και του λόγου Ιd/I με συντελεστή προσδιορισμού R2=0,8 και RMSE=0,046. Για όλες τις εξεταζόμενες βιβλιογραφικές συσχετίσεις όπως και για το νέο μοντέλο υπολογίστηκαν οι στατιστικοί συντελεστές και παρουσιάζονται υπό τη μορφή πίνακα. Έγινε ποιοτική ανάλυση διαμέσου διαγραμμάτων και σύγκριση της νέας συσχέτισης και της συσχέτισης των Orgill and Hollands, η οποία ήταν η καλύτερη από τις βιβλιογραφικές συσχετίσεις. Επιπλέον, υπολογίστηκαν τα μέσα μηνιαία ΚΤ και ΚD και εξήχθη μια συσχέτιση μεταξύ τους με συντελεστή προσδιορισμού R2=0,91 και RMSE=0,0095.In this work several correlations of predicting diffuse radiation were presented such as Page, Erbs, Orgill and Hollands and Karatasou. These correlations were compared between them and with the recorded data of diffuse radiation. A quality control was performed with the presentation of diagrams for the four seasons of the year and four characteristic days (sunny, with a few clouds, cloudy and rainy day respectively). A new polynomial 2nd order model of predicting diffuse radiation was developed based on the data of one year (2004), for Athens with coefficient of determination, R2=0,8 and Root Mean Square Error, RMSE=0,046. Thereafter, a statistical analysis was performed giving the prediction of the statistical coefficients for a more detailed analysis. A quality control between the new empirical model and the correlation of Orgill and Hollands was accomplished. Finally, the mean monthly values of KT and KD were calculated and a correlation between them was developed giving a coefficient of determination R2=0,91 και RMSE=0,0095.Ευγενία Δ. Μέχλερ