Search or filter publications

Filter by type:

Filter by publication type

Filter by year:

to

Results

  • Showing results for:
  • Reset all filters

Search results

  • Journal article
    Schleburg M, Christiansen L, Thornhill NF, Fay Aet al., 2013,

    A combined analysis of plant connectivity and alarm logs to reduce the number of alerts in an automation system

    , JOURNAL OF PROCESS CONTROL, Vol: 23, Pages: 839-851, ISSN: 0959-1524
  • Conference paper
    Fabozzi D, Thornhill NF, Pal BC, 2013,

    Frequency Restoration Reserve Control Scheme with Participation of Industrial Loads

    , Piscataway, NJ, IEEE PES PowerTech Grenoble 2013, Publisher: IEEE

    In order to accommodate larger amounts of renewable energy resources, whose power output is inherently unpredictable, there is an increasing need for frequency control power reserves. Loads are already used to provide replacement reserves, i.e. the slowest kind of reserves, in several power systems. This paper proposes a control scheme for frequency restoration reserves with participation of industrial loads. Frequency restoration reserves are required to change their active power within a time frame of tens of seconds to tens of minutes in response to a regulation signal. Industrial loads in many cases already have the capacity and capability to participate in this service. A mapping of their process constraints to power and energy demand is proposed in order to integrate industrial loads in existing control schemes. The proposed control scheme has been implemented in a 74-bus test system. Dynamic simulations show that industrial loads can be successfully integrated into the power system as frequency restoration reserves.
  • Conference paper
    P Kunjumuhammed L, C Pal B, F Thornhill N, 2013,

    A Test System Model for Stability Studies of UK Power Grid

    , IEEE PES PowerTech Grenoble 2013
  • Conference paper
    Yang Y, Farid SS, Thornhill NF, 2013,

    Decision tree for rapid prediction of bioprocess facility fit issues

    , 245th National Meeting of the American-Chemical-Society (ACS), Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
  • Patent
    Fabozzi D, Thornhill N, Pal BC, 2013,

    Power System Control

    Summary of InventionIn accordance with an aspect of the invention there is provided a method for allocating a plurality of power reserves to deliver power to a power network to meet a power reserve requirement for balancing a frequency of the power network. The method comprises obtaining, for a plurality of power reserves of a power network, power reserve flexibility characteristics associated with each power reserve. The method further comprises obtaining, for the plurality of power reserves, an indexing value associated with the delivery of power by each of the power reserves. The method further comprises determining a power reserve requirement associated with the power network. The method further comprises assigning one or more of the plurality of power reserves to deliver power to the power network, the plurality of power reserves assigned in accordance with the power reserve flexibility characteristics associated with each of the power reserves, the indexing value associated with each of the power reserves, and the power reserve requirement associated with the power network. The power reserve flexibility characteristics may be indicative of power deliverable to the power network by the respective power reserve with respect to time. The power reserve flexibility characteristics may include characteristics of positive and/or negative power reserve flexibility.The power reserve flexibility characteristics may include one or more of a maximum deliverable power, a period of time to provide the maximum deliverable power from receipt of an instruction for power delivery, a minimum duration for sustaining the maximum deliverable power and a period of time to reduce power delivery from the maximum deliverable power to a minimum deliverable power.The assigning of one or more of the plurality of power reserves may further comprise selecting one or more of the plurality power reserves to provide the power reserve requirement in order of the indexing value associated with t
  • Journal article
    Stonier A, Pain D, Westlake A, Hutchinson N, Thornhill NF, Farid SSet al., 2013,

    Integration of Stochastic Simulation with Multivariate Analysis: Short-Term Facility Fit Prediction

    , BIOTECHNOLOGY PROGRESS, Vol: 29, Pages: 368-377, ISSN: 8756-7938
  • Journal article
    Sharifzadeh M, Thornhill NF, 2013,

    Integrated design and control using a dynamic inversely controlled process model

    , COMPUTERS & CHEMICAL ENGINEERING, Vol: 48, Pages: 121-134, ISSN: 0098-1354
  • Conference paper
    Budinis S, Fabozzi D, Thornhill NF, 2013,

    A control technique based on compressor characteristics with applications to carbon capture and storage systems

    Introduction: Compressors are vital pieces of equipment within the process industry and they are going to be important in the next few years for dealing with carbon dioxide from carbon capture and storage (CCS) systems. Compressor characteristics (also called compressor maps) represent the operation of the machine in a graphical form. They are provided by the manufacturer of the compressor together with the machine and they are generated via experiments at reference conditions. The most common compressor characteristics represent the pressure ratio of the machine (i.e. the ratio between the output pressure and the input pressure) as a function of inlet flowrate and rotational shaft speed. For a single speed machine there is a single characteristic curve rather than a map (where instead the same function is plotted more times for different shaft speeds). While the inlet flowrate of the machine is generally a boundary condition of the compression system, the rotational shaft speed is very often the manipulated variable of the control system for a variable speed compressor. State of the art and open questions: Steady state and dynamic simulations are routinely used by academics and practitioners to represent and analyse the behaviour of a compressor during different activities such as design, control and optimization of the machine. In the literature there are many examples of compressor dynamic models (Botros et al., 1991, Venturini, 2005, Camporeale et al., 2006). Different techniques have been proposed for simulation and control applications. However the models found in the literature do not rely much on the compressor characteristics. The reason for that is that they usually represent simple compressors i.e. single stage lab-size machine that can be tested in a lab to provide the parameters needed for the model calibration. This type of machine is closer to an ideal compressor than an industrial compressor. For this reason a simplified model cannot capture accurate
  • Conference paper
    Sorensen E, Thornhill NF, Akinmolayan F, 2013,

    Predictive modelling of a conventional clean water treatment work
  • Conference paper
    Ikram W, Thornhill NF, 2013,

    Towards the development of a wireless network node lifetime calculation tool

    , IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2013, ISSN: 1946-0740

    The designers, optimizers and maintenance personnel of a wireless sensor network are frequently challenged by system level energy budget considerations. Minimizing the need for battery replacement is often the design goal while ensuring that a balance is maintained between capability and current consumption in order to address application needs. In this paper, a tool is introduced which can be used to calculate the lifetime of a battery operated wireless node. It allows the user to configure different wireless sensor platforms, select a battery of choice, and specify the application which needs to be executed over the configured hardware. As a result, the tool computes an estimate for the expected lifetime of the wireless sensor node. Furthermore, the tool also provides a detailed overview of the energy consumed by each component during a duty cycle. © 2013 IEEE.
  • Conference paper
    Barocio E, Pal BC, Fabozzi D, Thornhill NFet al., 2013,

    Detection and visualization of power system disturbances using principal component analysis

    , IREP Symposium: Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid, IREP 2013

    In this paper, a multivariate statistical projection method based on Principal Component Analysis (PCA) is proposed for detecting and extracting unusual or anomalous events from wide-area monitoring data. The method combines PCA with statistical test to detect and analyze anomalous dynamic events from measured data. Simulations based on a transient stability model of the New England Test System are used to demonstrate the ability of the method to detect and extract system events from wide-area data. © 2013 IEEE.
  • Software
    Cecilio IM, Thornhill NF, 2013,

    FRECOL: Educational Toolbox for Power System Frequency Control

    FRECOL is an educational tool for long-term dynamic simulations of power system frequency control under realistic disturbance scenarios. It is implemented in MATLAB/Simulink and is aimed at power and control engineering students to practice frequency control and to test tuning and control strategies.
  • Conference paper
    Ersdal AM, Imsland L, Cecilio IM, Fabozzi D, Thornhill NFet al., 2013,

    Applying model predictive control to power system frequency control

    , 4th IEEE/PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

    Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) controller, and simulations show that the MPC improves frequency deviation and control performance. © 2013 IEEE.
  • Conference paper
    Thornhill NF, Fabozzi D, Pal BC, 2013,

    Monitoring and management of power transmission dynamics in an industrial smart grid

    , IEEE PES PowerTech Grenoble 2013

    This article is a position paper whose purpose is to give the context for presentations in a special session at PowerTech 2013. The special session is being proposed by the EU FP7 Real-Smart Consortium, a Marie Curie Industry-Academic Pathways and Partnerships project. The paper gives an overview of topics on modeling, monitoring and management of power transmission dynamics with participation from large industrial loads. © 2013 IEEE.
  • Conference paper
    Cicciotti M, Geist S, Schild A, Martinez-Botas RF, Romagnoli A, Thornhill NFet al., 2013,

    Systematic one zone meanline modelling of centrifugal compressors for industrial online applications

    , ASME Turbo Expo 2013, San Antonio, Texas, June 3-7 2013, paper GT2013/95821

    For developing model-based online applications such as condition monitoring and condition-based maintenance or real-time optimization, highly representative and yet simple physical models of centrifugal compressors are necessary. Previous investigations have shown that in this context meanline models represent a valid alternative to the commonly used empirical based modelling methodologies such as polynomial regression models or artificial neural networks. This paper provides a methodology for tailoring meanline models to multistage centrifugal compressors by appropriate selection and adaptation of loss correlations. Guidelines for the selection of the boundary conditions are also provided. The potential of the methodology is demonstrated in the Proof-of-concept section using two sets of data obtained from an air multistage centrifugal compressor operated in BASF SE, Ludwigshafen, Germany. The first set of data was used to calibrate the model whereas the second one was used for validation. The model results show that the predictions of stagnation temperature and pressure at the outlet of the stage deviate from the measurements respectively 0.15-3% and of 0.66-1.1% respectively. The results are discussed in the current paper. Copyright © 2013 by ASME.
  • Conference paper
    Yang Y, Farid SS, Thornhill NF, 2013,

    Prediction of biopharmaceutical facility fit issues using decision tree analysis

    , 23rd European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 61-66, ISSN: 1570-7946
  • Journal article
    Shukla V, Naim MM, Thornhill NF, 2012,

    Rogue seasonality detection in supply chains

    , INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, Vol: 138, Pages: 254-272, ISSN: 0925-5273
  • Conference paper
    Cecílio IM, Rapp K, Thornhill NF, 2012,

    Process Performance Analysis in Large-Scale Systems Integrating Different Sources of Information

    , 8th IFAC International Symposium on Advanced Control of Chemical Processes, 2012, Publisher: International Federation of Automatic Control, Pages: 45-50
  • Journal article
    Meland E, Thornhill NF, Lunde E, Rasmussen Met al., 2012,

    Quantification of valve leakage rates

    , AICHE JOURNAL, Vol: 58, Pages: 1181-1193, ISSN: 0001-1541
  • Journal article
    Sharifzadeh M, Thornhill NF, 2012,

    Optimal selection of control structure using a steady-state inversely controlled process model

    , COMPUTERS & CHEMICAL ENGINEERING, Vol: 38, Pages: 126-138, ISSN: 0098-1354

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://www.imperial.ac.uk:80/respub/WEB-INF/jsp/search-t4-html.jsp Request URI: /respub/WEB-INF/jsp/search-t4-html.jsp Query String: id=668&limit=20&page=5&respub-action=search.html Current Millis: 1732189707293 Current Time: Thu Nov 21 11:48:27 GMT 2024

Contact us

Nina Thornhill, ABB/RAEng Professor of Process Automation
Centre for Process Systems Engineering
Department of Chemical Engineering
Imperial College London
South Kensington Campus, London SW7 2AZ

Tel: +44 (0)20 7594 6622
Email: n.thornhill@imperial.ac.uk