176 results found
Cai L, Thornhill NF, Kuenzel S, et al., 2018, Wide-area monitoring of power systems using principal component analysis and k-nearest neighbor analysis, IEEE Transactions on Power Systems, ISSN: 0885-8950
Wide-area monitoring of power systems is important for system security and stability. It involves the detection and localization of power system disturbances. However, the oscillatory trends and noise in electrical measurements often mask disturbances, making wide-area monitoring a challenging task. This paper presents a wide-area monitoring method to detect and locate power system disturbances by combining multivariate analysis known as Principal Component Analysis (PCA) and time series analysis known as k-Nearest Neighbor (kNN) analysis. Advantages of this method are that it can not only analyze a large number of wide-area variables in real time but also can reduce the masking effect of the oscillatory trends and noise on disturbances. Case studies conducted on data from a four-variable numerical model and the New England power system model demonstrate the effectiveness of this method.
Cai L, Thornhill NF, Kuenzel S, et al., 2017, Real-time detection of power system disturbances based on k-nearest neighbor analysis, IEEE Access, Vol: 5, Pages: 5631-5639, ISSN: 2169-3536
Efficient disturbance detection is important for power system security and stability. In this paper, a new detection method is proposed based on a time series analysis technique known as k nearest neighbor (kNN) analysis. Advantages of this method are that it can deal with the electrical measurements with oscillatory trends and can be implemented in real time. The method consists of two stages which are the off-line modelling and the on-line detection. The off-line stage calculates a sequence of anomaly index values using kNN on the historical ambient data and then determines the detection threshold. Afterwards, the on-line stage calculates the anomaly index value of presently measured data by readopting kNN and compares it with the established threshold for detecting disturbances. To meet the real-time requirement, strategies for recursively calculating the distance metrics of kNN and for rapidly picking out the kth smallest metric are built. Case studies conducted on simulation data from the reduced equivalent model of Great Britain power system and measurements from an actual power system in Europe demonstrate the effectiveness of the proposed method.
Cai L, Thornhill NF, Pal BC, 2017, Multivariate detection of power system disturbances based on fourth order moment and singular value decomposition, IEEE Transactions on Power Systems, Vol: 32, Pages: 4289-4297, ISSN: 1558-0679
This paper presents a new method to detect power system disturbances in a multivariate context, which is based on Fourth Order Moment (FOM) and multivariate analysisimplemented as Singular Value Decomposition (SVD). The motivation for this development is that power systems are increasingly affected by various disturbances and there is a requirement for the analysis of measurements to detect these disturbances. The application results on the measurements of an actual power system in Europe illustrate that the proposed multivariate detection method achieves enhanced detection reliability and sensitivity.
Yang Y, Velayudhan A, Farid S, et al., 2017, High-throughput data analysis for rapid ranking of high-concentration monoclonal antibody formulations using manufacturability indices, 253rd National Meeting of the American-Chemical-Society (ACS) on Advanced Materials, Technologies, Systems, and Processes, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
Yang Y, Velayudhan A, Thornhill NF, et al., 2017, Multi-criteria manufacturability indices for ranking high-concentration monoclonal antibody formulations, Biotechnology and Bioengineering, Vol: 114, Pages: 2043-2056, ISSN: 1097-0290
The need for high-concentration formulations for subcutaneous delivery of therapeutic monoclonal antibodies (mAbs) can present manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are key considerations for high-concentration formulations. This work presents novel frameworks for deriving a set of manufacturability indices related to viscosity and thermostability to rank high-concentration mAb formulation conditions in terms of their ease of manufacture. This is illustrated by analysing published high-throughput biophysical screening data that explores the influence of different formulation conditions (pH, ions and excipients) on the solution viscosity and product thermostability. A decision tree classification method, CART (Classification and Regression Tree) is used to identify the critical formulation conditions that influence the viscosity and thermostability. In this work, three different multi-criteria data analysis frameworks were investigated to derive manufacturability indices from analysis of the stress maps and the process conditions experienced in the final UF/DF step. Polynomial regression techniques were used to transform the experimental data into a set of stress maps that show viscosity and thermostability as functions of the formulation conditions. A mathematical filtrate flux model was used to capture the time profiles of protein concentration and flux decay behaviour during UF/DF. Multi-criteria decision-making analysis was used to identify the optimal formulation conditions that minimize the potential for both viscosity and aggregation issues during UF/DF.
Zagorowska M, Thornhill NF, 2017, Compressor map approximation using Chebyshev polynomials, IEEE 2017 25th Mediterranean Conference on Control and Automation (MED 2017), Publisher: IEEE, Pages: 864-869, ISSN: 2473-3504
Compressor maps are one of the main elements describing the behaviour of centrifugal compressors. Although the compressor map is often provided by the manufacturer, there may be changes during the lifetime of the compressor due to refurbishments or wear. Since the compressor maps are often used in real-time optimization problems, there is a need for simple approximation methods. This paper focuses on approximation of physical models using Chebyshev polynomials instead of third order polynomials which are unable to capture some aspects of the compressor behaviour. Chebyshev polynomials capture the characteristics better than third order polynomials. They provide a flexible tool for compressor map approximation and analysis.
Bauer M, Horch A, Xie L, et al., 2016, The current state of control loop performance monitoring - A survey of application in industry, JOURNAL OF PROCESS CONTROL, Vol: 38, Pages: 1-10, ISSN: 0959-1524
Budinis S, Thornhill NF, 2016, Supercritical fluid recycle for surge control of CO2 centrifugal compressors, Computers & Chemical Engineering, Vol: 91, Pages: 329-342, ISSN: 0098-1354
This paper presents computer-based design and analysis of control systems for centrifugal compressors when the operating fluid is supercritical CO2.It reports a non-linear dynamic model including a main forward compression line and two different configurations for the recycle antisurge line. Disturbance scenarios are proposed for testing the configurations and performance indicators are suggested to evaluate control performance and power consumption of the compression system.The paper demonstrates that compared to the hot recycle, the process configuration including a cold gas recycle has better overall stability, but higher power consumption and lower values for the control performance indicators. Based on the previous considerations, the paper gives suggestions regarding the choice of the recycle configuration. Moreover it compares subcritical and supercritical compression during surge prevention and highlights the importance of the selection of the gas recycle configuration when full recycle is needed.
Cecilio IM, Ottewill JR, Fretheim H, et al., 2016, Removal of transient disturbances from oscillating measurements using nearest neighbors imputation, JOURNAL OF PROCESS CONTROL, Vol: 44, Pages: 68-78, ISSN: 0959-1524
Cecilio IM, Ottewill JR, Thornhill NF, 2016, Determining the propagation path of a disturbance in multi-rate process and electromechanical systems, CONTROL ENGINEERING PRACTICE, Vol: 49, Pages: 187-193, ISSN: 0967-0661
Chioua M, Bauer M, Chen S-L, et al., 2016, Plant-wide root cause identification using plant key performance indicators (KPIs) with application to a paper machine, CONTROL ENGINEERING PRACTICE, Vol: 49, Pages: 149-158, ISSN: 0967-0661
Xenos DP, Kahrs O, Cicciotti M, et al., 2016, Challenges of the application of data-driven models for the real-time optimization of an industrial air separation plant, European Control Conference (ECC), Publisher: IEEE, Pages: 1025-1030
Xenos DP, Kopanos GM, Cicciotti M, et al., 2016, Operational optimization of networks of compressors considering condition-based maintenance, COMPUTERS & CHEMICAL ENGINEERING, Vol: 84, Pages: 117-131, ISSN: 0098-1354
Xenos DP, Lunde E, Thornhill NF, 2016, Optimal Operation and Maintenance of Gas Compressor Stations: An Integrated Framework Applied to a Large-Scale Industrial Case, JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, Vol: 138, ISSN: 0742-4795
Xenos DP, Noor IM, Matloubi M, et al., 2016, Demand-side management and optimal operation of industrial electricity consumers: An example of an energy-intensive chemical plant, APPLIED ENERGY, Vol: 182, Pages: 418-433, ISSN: 0306-2619
Akinmolayan F, Thornhill N, Sorensen E, 2015, A Detailed Mathematical Modelling Representation of Clean Water Treatment Plants, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 2537-2542, ISSN: 1570-7946
Barocio E, Pal BC, Thornhill NF, et al., 2015, A Dynamic Mode Decomposition Framework for Global Power System Oscillation Analysis, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 30, Pages: 2902-2912, ISSN: 0885-8950
Budinis S, Thornhill NF, 2015, Supercritical gas recycle analysis for surge control of centrifugal compressors, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1583-1588, ISSN: 1570-7946
Budinis S, Thornhill NF, 2015, Control of centrifugal compressors via model predictive control for enhanced oil recovery applications, Pages: 9-14, ISSN: 1474-6670
© 2015, IFAG (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. This paper proposes a control system for integrated pressure and surge control of centrifugal compressors for enhanced oil recovery application. The proposed control system is based on linear model predictive control. A fully validated non-linear dynamic model was developed in order to simulate the operation of the compressor at full and partial load. The model of the compression system includes a main process line with the compressor and a recycle line with the antisurge recycle valve. Different disturbance and control tuning scenarios were tested and the response of the model predictive controller was analysed, evaluated and also compared with a traditional control system. Temperature effects have been taken into account in the model of the process and in the constraint formulation of the MPC optimization problem. The results show that the proposed control technique is able to meet the process demand while preventing surge and also minimizing the amount of gas recycle.
Cecílio IM, Ottewill JR, Thornhill NF, 2015, Determining the propagation path of a disturbance in multi-rate systems, Pages: 784-789, ISSN: 1474-6670
© 2015, IF AC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Several methods to derive the propagation path of a disturbance in process plants are applicable only to systems whose measurements are all available with the same sampling rate. This paper proposes a multi-rate method to identify the propagation path when measurements have different sampling rates. This is relevant for including in the analysis fast-sampled measurements from electromechanical equipment. The method is based on non-linear mutual prediction, which yields the directionality in the relationship between two time series. The method was demonstrated and validated, giving the expected outcome in an experimental case study, in which the root cause and propagation path of the disturbance were known.
Cecílio IM, Ottewill JR, Thornhill NF, 2015, Adapting nearest neighbors-based monitoring methods to irregularly sampled measurements, Pages: 448-454, ISSN: 2325-0178
© 2015, Prognostics and Health Management Society. All rights reserved. Irregularly spaced measurements are a common quality problem in real data and preclude the use of several feature extraction methods, which were developed for measurements with constant sampling intervals. Feature extraction methods based on nearest neighbors of embedded vectors are an example of such methods. This paper proposes the use of a timebased construction of embedded vectors and a weighted similarity metric within nearest neighbor-based methods in order to extend their applicability to irregularly sampled measurements. The proposed idea is demonstrated within a method of univariate detection of transient or spiky disturbances. The result obtained with an irregularly sampled measurement is benchmarked by the original regularly sampled measurement. Although the method was originally implemented for off-line analysis, the paper also discusses modifications to enable its on-line implementation.
Cecilio IM, Ottewill JR, Fretheim H, et al., 2015, Multivariate Detection of Transient Disturbances for Uni- and Multirate Systems, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 23, Pages: 1477-1493, ISSN: 1063-6536
Cicciotti M, Xenos DP, Bouaswaig AEF, et al., 2015, Physical modelling of industrial multistage centrifugal compressors for monitoring and simulation, PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, Vol: 229, Pages: 3433-3448, ISSN: 0954-4062
Ersdal AM, Imsland L, Uhlen K, et al., 2015, Model predictive load–frequency control taking into account imbalance uncertainty, Control Engineering Practice, Vol: 53, Pages: 139-150, ISSN: 0967-0661
Nonlinear model predictive control (NMPC) is investigated for load frequency control (LFC) of an interconnected power system which is exposed to increasing wind power penetration. The robustified NMPC (RNMPC) proposed here uses knowledge of the estimated worst-case deviation in wind-power production to make the NMPC more robust. The NMPC is based on a simplified system model that is updated using state- and parameter estimation by Kalman filters, and it takes into account limitations on among others tie-line power flow. Tests on a proxy of the Nordic power system show that the RNMPC is able to fulfill system constraints under worst-case deviations in wind-power production, where the nominal NMPC is not.
Kopanos GM, Xenos DP, Cicciotti M, et al., 2015, Optimization of a network of compressors in parallel: Operational and maintenance planning - The air separation plant case, APPLIED ENERGY, Vol: 146, Pages: 453-470, ISSN: 0306-2619
Leng D, Thornhill NF, 2015, Process disturbance cause and effect analysis using Bayesian Networks, Pages: 1457-1464, ISSN: 1474-6670
© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Process disturbances can propagate over entire plants and it can be difficult to locate their root causes from observed effects. Bayesian Networks offer a way to represent unit operations, processes and whole plants as probabilistic models which can be used to infer and rank likely causes from observed effects. This paper presents a methodology to use deterministic steady-state process models to derive Bayesian Networks based on alarm event detection. An example heat recovery network is used to illustrate the model building and inferential procedures.
Mehleri ED, Mac Dowell N, Thornhill NF, 2015, Model Predictive Control of Post-Combustion CO2 Capture Process integrated with a power plant, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 161-166, ISSN: 1570-7946
Noor IM, Thornhill NF, Fretheim H, et al., 2015, Quantifying the Demand-Side Response Capability of Industrial Plants to Participate in Power System Frequency Control Schemes, PowerTech, 2015 IEEE Eindhoven, Publisher: IEEE
Romero DD, Graven T-G, Thornhill NF, 2015, Linking process, electrical and logical connectivity for supported fault diagnosis, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 965-970, ISSN: 1570-7946
Xenos DP, Cicciotti M, Kopanos GM, et al., 2015, Optimization of a network of compressors in parallel: Real Time Optimization (RTO) of compressors in chemical plants - An industrial case study, APPLIED ENERGY, Vol: 144, Pages: 51-63, ISSN: 0306-2619
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