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  • CONFERENCE PAPER
    Bachtiar V, Kerrigan EC, Moase WH, Manzie Cet al.,

    Smoothness Properties of the MPC Value Function with respect to Sampling Time and Prediction Horizon

    , 10th Asian Control Conference (ASCC)
  • CONFERENCE PAPER
    Boem F, Reci R, Cenedese A, Parisini Tet al.,

    Distributed clustering-based sensor fault diagnosis for HVAC systems

    , 20th IFAC World Congress, Publisher: IFAC

    The paper presents a distributed Sensor Fault Diagnosis architecture for IndustrialWireless Sensor Networks monitoring HVAC systems, by exploiting a recently proposeddistributed clustering method. The approach allows the detection and isolation of multiplesensor faults and considers the possible presence of modeling uncertainties and disturbances.Detectability and isolability conditions are provided. Simulation results show the effectivenessof the proposed method for an HVAC system.

  • CONFERENCE PAPER
    Cantoni M, Farokhi F, Kerrigan EC, Shames Iet al.,

    A scalable QP solver for optimal control of cascades with constraints

    , Australian Control Conference
  • CONFERENCE PAPER
    Carmichael R, Schofield J, Bilton M, Ozaki R, Strbac Get al.,

    Dynamic pricing of electricity for wind-following?: Understanding demand-response and consumer engagement on the UK’s first trial of a dynamic time-of-use tariff for residential electricity

    , BEHAVE 2014 Conference
  • CONFERENCE PAPER
    Chaffey GP, judge PD, Green TC,

    Energy Requirements for Modular Circuit Breakers in Multiterminal HVDC Networks

    , HVDC 2016, International Conference on. CSEE, 2016.
  • CONFERENCE PAPER
    Di Franco P, Scarciotti G, Astolfi A,

    A note on the stability of nonlinear differential-algebraic systems

    , 20th IFAC World Congress
  • CONFERENCE PAPER
    Di Franco P, Scarciotti G, Astolfi A,

    On the stability of constrained mechanical systems

    , 56th IEEE Conference on Decision and Control, Publisher: IEEE
  • CONFERENCE PAPER
    Ge M, Kerrigan E,

    Noise Covariance Estimation for Time-varying and Nonlinear Systems

    , The 19th World Congress of the International Federation of Automatic Control
  • CONFERENCE PAPER
    Ge M, Kerrigan EC,

    Ocean Wave Forecasting Using an Autoregressive Moving Average Model

    , Control 2016 - 11th International Conference on Control

    In order to predict future observations of a noisedrivensystem, we have to find a model that exactly or atleast approximately describes the behavior of the system sothat the current system state can be recovered from pastobservations. However, sometimes it is very difficult to modela system accurately, such as real ocean waves. It is thereforeparticularly interesting to analyze ocean wave properties inthe time-domain using autoregressive moving average (ARMA)models. Two ARMA/AR based models and their equivalent statespace representations will be used for predicting future oceanwave elevations, where unknown parameters will be determinedusing linear least squares and auto-covariance least squaresalgorithms. Compared to existing wave prediction methods, inthis paper (i) an ARMA model is used to enhance the predictionperformance, (ii) noise covariances in the ARMA/AR model arecomputed rather than guessed and (iii) we show that, in practice,low pass filtering of historical wave data does not improve theforecasting results.

  • CONFERENCE PAPER
    Ge M, Kerrigan EC,

    Relations between Full Information and Kalman-Based Estimation

    , 55th IEEE Conference on Decision and Control, Publisher: IEEE

    For nonlinear state space systems with additivenoises, sometimes the number of process noise signals couldbe less than the dimension of the state space. In order toimprove the accuracy and stability of nonlinear state estimation,this paper provides for the first time the derivation of thefull information estimator (FIE) for such nonlinear systems.We verify our derivation of the FIE by firstly proving theunbiasedness and minimum-variance of the FIE for linear timevarying (LTV) systems, then showing the equivalence betweenthe Kalman filter/smoother and the FIE for LTV systems.Finally, we prove that the FIE will provide more accurate stateestimates than the extended Kalman filter (EKF) and smoother(EKS) for nonlinear systems.

  • JOURNAL ARTICLE
    Ge M, Kerrigan EC,

    Noise Covariance Identification for Nonlinear Systems using Expectation Maximization and Moving Horizon Estimation

    , Automatica, ISSN: 0005-1098

    In order to estimate states from a noise-driven state space system, the state estimator requires a priori knowledge of bothprocess and output noise covariances. Unfortunately, noise statistics are usually unknown and have to be determined fromoutput measurements. Current expectation maximization (EM) based algorithms for estimating noise covariances for nonlinearsystems assume the number of additive process and output noise signals are the same as the number of states and outputs,respectively. However, in some applications, the number of additive process noises could be less than the number of states. Inthis paper, a more general nonlinear system is considered by allowing the number of process and output noises to be smaller orequal to the number of states and outputs, respectively. In order to estimate noise covariances, a semi-definite programmingsolver is applied, since an analytical solution is no longer easy to obtain. The expectation step in current EM algorithms relyon state estimates from the extended Kalman filter (EKF) or smoother. However, the instability and divergence problems ofthe EKF could cause the EM algorithm to converge to a local optimum that is far away from true values. We use movinghorizon estimation instead of the EKF/smoother so that the accuracy of the covariance estimation in nonlinear systems canbe significantly improved.

  • CONFERENCE PAPER
    Green RJ, Strbac,

    Storage in the energy market

    , IEEE Power and Energy Society General Meeting 2015
  • CONFERENCE PAPER
    Huyghues-Beaufond N, Jakeman A, Tindemans S, Strbac Get al.,

    Challenges in model and data merging for the implementation of a distribution network contingency analysis tool

    , CIRED 2017, Publisher: IET

    The electricity network in the South East of England has become more challenging to manage both for the transmission and distribution network operators due to increased distributed generation (DG) connection and increased power flows on transmission interconnectors to and from continental Europe. UK Power Networks (UKPN), the distribution network operator (DNO), has trial led for the first time online contingency analysis on adistribution network in Great Britain. The Kent Active System Management (KASM) project aims to demonstrate the benefitsof using a Contingency Analysis System (CAS) forboth, operational and planning time frames.This paper describes challenges and the recommended approach toovercomedata exchange and data quality challenges whendevelopinga real-time power flow modelfrom existing datasets. It provides a real world example of dealing with data exchange and also highlightstheneed forTSO(Transmission System Operator)/DNO coordination

  • CONFERENCE PAPER
    Huyghues-Beaufond N, Jakeman A, Tindemans S, Strbac Get al.,

    Enhancing distribution network visibility using contingency analysis tools

    , International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017), Publisher: IET

    The East Kentareain the South East of Englandis the goodexample of howthe uptake of distributed generation is changing the way electricitynetworks operate. This paper identifies the technical and operational challenges facing transmission and distribution networks in the East Kent area. It introducesthe Kent Active System Management (KASM)project, which develops anonline contingency analysis solution designed toassist UK Power Networks(UKPN)inmaximising asset utilisation while maintaining the network security.

  • CONFERENCE PAPER
    Jamieson M, Strbac G, Tindemans S, Bell Ket al.,

    A simulation framework to analyse weather-induced faults

    , RTDN 2017: International Conference on Resilience of Transmission and Distribution Networks, Publisher: IET

    A framework for simulating weather-induced dependent faults across networks is proposed and demonstrated on a truncated GB network representative of the Scottish and Northern English network. Different weather scenarios are simulated on the testnetworkconsidering location and wind-speed intensity, analysed using Monte-Carlo simulation.The sensitivity of the network toco-occurrence of faults is simulated by changing the sensitivity of network assets to windspeed via an exponential function. Greater sensitivity to wind speed inducesa significantincrease in outages, as reflected by risk metrics, specifically Expected Energy Not Served and Expected Maximum Load Shed.

  • CONFERENCE PAPER
    Judge PD, Chaffey G, Clemow P, Merlin MMC, Green TCet al.,

    Hardware testing of the alternate arm converter operating in its extended overlap mode

    , International High Voltage Direct Current 2015 Conference (HVDC2015)
  • CONFERENCE PAPER
    Khusainov B, Kerrigan EC, Suardi A, Constantinides GAet al.,

    Nonlinear predictive control on a heterogeneous computing platform

    , IFAC World Congress 2017, Publisher: IFAC

    Nonlinear Model Predictive Control (NMPC) is an advanced control technique that often relieson computationally demanding optimization and integration algorithms. This paper proposesand investigates a heterogeneous hardware implementation of an NMPC controller based onan interior point algorithm. The proposed implementation provides flexibility of splitting theworkload between a general-purpose CPU with a fixed architecture and a field-programmablegate array (FPGA) to trade off contradicting design objectives, namely performance andcomputational resource usage. A new way of exploiting the structure of the Karush-Kuhn-Tucker(KKT) matrix yields significant memory savings, which is crucial for reconfigurable hardware.For the considered case study, a 10x memory savings compared to existing approaches anda 10x speedup over a software implementation are reported. The proposed implementationcan be tested from Matlab using a new release of the Protoip software tool, which isanother contribution of the paper. Protoip abstracts many low-level details of heterogeneoushardware programming and allows quick prototyping and processor-in-the-loop verification ofheterogeneous hardware implementations.

  • CONFERENCE PAPER
    Kuenzel S, Kunjumuhammed LP, Pal BC, Erlich Iet al.,

    Wind Power Plants Inertial Response Capability Considering Wake Effect

    , 11th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, Lisbon
  • CONFERENCE PAPER
    Li PENG, Boem F, Pin G, Parisini Tet al.,

    Distributed fault detection and isolation for interconnected systems: a non-asymptotic kernel-based approach

    , 20th IFAC World Congress, Publisher: IFAC

    In this paper, a novel framework is proposed for deadbeat distributed Fault Detectionand Isolation (FDI) of large-scale continuous-time LTI dynamic systems. The monitoredsystem is composed of several subsystems which are linearly interconnected with unknownparameterization. Each subsystem is monitored by a local diagnoser based on the measuredlocal output, local inputs and the interconnection variables from the neighboring subsystems.The local FDI decision is based on two non-asymptotic state-parameter estimators using Volterraintegral operators which eliminate the effect of the unknown initial conditions so that theestimates converge to the true value in a deadbeat manner and therefore the fault diagnosiscan be achieved in finite time. Moreover, the unknown interconnection parameters and theunknown fault parameters are simultaneously estimated. Numerical examples are included toshow the effectiveness of the proposed FDI architecture.

  • CONFERENCE PAPER
    Martinez Sanz IM, Chaudhuri B, Majumder R,

    HVDC connection to large nuclear power plants: a case study on Moorside in Great Britain

    , 2017 IEEE Power and Energy Society General Meeting, Publisher: IEEE

    Use of HVDC links for direct connection of a largenuclear power station to the existing power grid is unprecedented.Control of such HVDC connection for stable and secure operationof the nuclear power station is challenging and untested. Forthe Moorside nuclear power station planned close to the LakeDistrict in Great Britain, there is tremendous pressure to useHVDC cables for the southern connection route (which wouldpass through the picturesque landscape) to avoid the visualimpact of overhead lines. This paper shows that it is feasibleto connect a large nuclear power station, such as Moorside,through a VSC-HVDC cable route alongside a northern ACroute where there are no objections to overhead transmission.Use of a proposed control of the VSC-HVDC is shown to achieveautomatic and rapid redirection of power on to the VSC-HVDClink following sudden outage of the AC route. Moreover, if thegenerators at Moorside were to shut down accidentally, the samecontrol strategy for VSC-HVDC can back feed the power stationauxiliaries which is essential for nuclear safety. Thus, a mix ofAC and HVDC connection routes achieves similar (if not better)transient responses as compared to using both AC routes whichin this case faces serious opposition.

  • CONFERENCE PAPER
    Moreira R, Strbac G, Papadopoulos P, Laguna Aet al.,

    Business Case in Support for Reactive Power Services from Distributed Energy Storage

    , CIRED 2017
  • CONFERENCE PAPER
    Mylvaganam T, Astolfi A,

    Zero finding via feedback stabilisation

    , IFAC 2017 World Congress, Publisher: Elsevier, ISSN: 1474-6670

    Two iterative algorithms for solving systems of linear and nonlinear equations areproposed. For linear problems the algorithm is based on a control theoretic approach and it isguaranteed to yield a converging sequence for any initial condition provided a solution exists.Systems of nonlinear equations are then considered and a generalised algorithm, again takinginspiration from control theory, is proposed. Local convergence is guaranteed in the nonlinearsetting. Both the linear and the nonlinear algorithms are demonstrated on a series of numericalexamples.

  • CONFERENCE PAPER
    Padoan A, Astolfi,

    Model reduction by moment matching at isolated singularitiesfor linear systems: a geometric approach

    , 56th IEEE Conference on Decision and Control, Publisher: IEEE
  • CONFERENCE PAPER
    Padoan A, Astolfi A,

    Model reduction by moment matching for ZIP systems

    , 53rd IEEE Conference on Decision and Control, Pages: 3631-3636, ISSN: 0191-2216
  • CONFERENCE PAPER
    Padoan A, Astolfi A,

    Moments of random variables: a system-theoretic interpretation

    , American Control Conference 2017, Publisher: IEEE

    Moments of continuous random variables with aprobability density function which can be represented as theimpulse response of a linear time-invariant system are studied.Under some assumptions, the moments of the random variableare characterised in terms of the solution of a Sylvester equationand of the steady-state output response of an interconnectedsystem. This allows to interpret well-known notions and resultsof probability theory and statistics in the language of systemtheory, including the notion of moment generating function, thesum of independent random variables and the notion of mixturedistribution.

  • CONFERENCE PAPER
    Padoan A, Astolfi A,

    Model reduction by moment matching at isolated singularities for linear systems: a complex analytic approach

    , 20th IFAC 2017 World Congress, Publisher: Elsevier

    The model reduction problem by moment matching for continuous-time, single-input, single-output, linear, time-invariant systems is studied at isolated singularities (inparticular, at poles). The notion of moment at a pole of the transfer function is defined.Exploiting this notion a one-to-one correspondence between moments at a pole of the transferfunction and the “limit solution” of a family of Sylvester equations is established. Finally, afamily of reduced order models is defined. A simple example illustrates the theory.

  • CONFERENCE PAPER
    Padoan A, Astolfi A,

    Eigenvalues and Poles of a Nonlinear System: a Geometric Approach

    , 56th IEEE Conference on Decision and Control, Publisher: IEEE
  • CONFERENCE PAPER
    Papadaskalopoulos, Ye Y, strbac,

    Exploring the Role of Demand Shifting in Oligopolistic Electricity Markets

    , 2017 IEEE Power & Energy Society General Meeting (GM)
  • CONFERENCE PAPER
    Pudjianto D, Strbac G, Boyer D,

    Virtual power plant: managing synergies and conflicts between TSO and DSO control objectives

    , CIRED 24th International Conference on Electricity Distribution, Publisher: IET

    In this paper, the implementationof Virtual Power Plantas a means to coordinate the use of distributed resources for different control objectives by TSO and DSO is described. In order to illustrate the concept, a range of illustrative studies demonstrating the application of VPP concept on a real11 kV system in Brixton will be presented, using data from the Low Carbon London project. The studies demonstrate thechanges in theoperating characteristics of the VPP area over a range of system operating conditions.

  • CONFERENCE PAPER
    Puthenpurayil Kunjumuhammed L, Pal BC,

    Selection of feedback signals for controlling dynamics in future power transmission networks

    , IEEE Power & Energy Society General Meeting, 2015

    This paper deals with the selection of feedback signal(s) that retain the modal behavior of power system electromechanical dynamics under varying operating circumstances. The approach seeks signals that have relatively large magnitude of residue, less variation of the magnitude and phase angle, sufficient gap between the critical pole-zeros, and least sensitive to other modes. The methodology is tested in a 16-machine interconnected power system model with multiple wind farms.

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