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Journal articlePuthenpurayil Kunjumuhammed L, Pal BC, Gupta R, et al., 2017,
Stability analysis of a PMSG based large offshore wind farm connected to a VSC-HVDC
, IEEE Transactions on Energy Conversion, Vol: 32, Pages: 1166-1176, ISSN: 1558-0059This paper presents modal analysis of a large offshore wind farm using PMSG type wind turbines connected to a VSC-HVDC. Multiple resonant frequencies are observed in the ac grid of offshore wind farms. Their control is crucial for the uninterrupted operation of the wind farm system. The characteristics of oscillatory modes are presented using modal analysis and participation factor analysis. Sensitivity of critical modes to wind turbine design parameters and their impact on closed loop stability of the system are discussed. A comparison between a full wind farm model and an aggregated model is presented to show differences in the characteristics of critical modes observed in the models, and implication of using the models for stability studies. It is concluded that robust control design is important for reliable operation of the system.
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Conference paperScarciotti G, 2017,
Discontinuous phasor model of an inductive power transfer system
, IEEE Wireless Power Transfer Conference (WPTC 2017), Publisher: IEEE, ISSN: 2474-0225Recently, a new discontinuous phasor transform has been introduced. The discontinuous phasor can represent the steady-state quantities of electrical circuits powered by discontinuous sources (e.g. square waves) without approximations. In this paper we provide a discontinuous phasor model of a two-coil inductive power transfer system. We validate this model studying the relation between the maximum power dissipated by the load and the frequency of the square wave. The simulations show that the new model correctly describes the steady-state behavior of the circuit for any quality factor and for any frequency.
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Conference paperHuyghues-Beaufond N, Jakeman A, Tindemans S, et al., 2017,
Enhancing distribution network visibility using contingency analysis tools
, International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017), Publisher: IETThe East Kent area in the South East of England is the good example of how the uptake of distributed generation is changing the way electricity networks operate. This paper identifies the technical and operational challenges facing transmission and distribution networks in the East Kent area. It introduces the Kent Active System Management (KASM) project, which develops an online contingency analysis solution designed to assist UK Power Networks (UKPN) in maximising asset utilisation while maintaining the network security.
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Conference paperJamieson M, Strbac G, Tindemans S, et al., 2017,
A simulation framework to analyse weather-induced faults
, RTDN 2017: International Conference on Resilience of Transmission and Distribution Networks, Publisher: IETA 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 test network considering location and wind-speed intensity, analysed using Monte-Carlo simulation. The sensitivity of the network to co-occurrence of faults is simulated by changing the sensitivity of network assets to wind speed via an exponential function. Greater sensitivity to wind speed induces a significant increase in outages, as reflected by risk metrics, specifically Expected Energy Not Served and Expected Maximum Load Shed.
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Journal articleAmeli H, Strbac, Qadrdan, 2017,
Value of gas network infrastructure flexibility in supporting cost effective operation of power systems
, Applied Energy, Vol: 202, Pages: 571-580, ISSN: 1872-9118The electricity system balancing is becoming increasingly challenging due to the integration of Renewable Energy Sources (RES). At the same time, the dependency of electricity network on gas supply system is expected to increase, as a result of employing flexible gas generators to support the electricity system balancing. Therefore the capability of the gas supply system to deliver gas to generators under a range of supply and demand scenarios is of a great importance. As potential solutions to improve security of gas and electricity supply, this paper investigates benefits of employing flexible multi-directional compressor stations as well as adopting a fully integrated approach to operate gas and electricity networks. A set of case studies for a GB gas and electricity networks in 2030 have been defined to quantify the value of an integrated operation paradigm versus sequential operation of gas and electricity networks. The results indicate there are significant overall system benefits (up to 65% in extreme cases) to be gained from integrated optimization of gas and electricity systems, emphasizing the important role of gas network infrastructure flexibility in efficiently accommodating the expected expansion of intermittent RES in future power systems.
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Journal articleMoreira A, strbac G, Moreno R, et al., 2017,
A Five-Level MILP Model for Flexible Transmission Network Planning under Uncertainty: A Min-Max Regret Approach
, IEEE Transactions on Power Systems, Vol: 33, Pages: 486-501, ISSN: 0885-8950The benefits of new transmission investment significantly depend on deployment patterns of renewable electricity generation that are characterized by severe uncertainty. In this context, this paper presents a novel methodology to solve the transmission expansion planning (TEP) problem under generation expansion uncertainty in a min-max regret fashion, when considering flexible network options and n 1 security criterion. To do so, we propose a five-level mixed integer linear programming (MILP) based model that comprises: (i) the optimal network investment plan (including phase shifters), (ii) the realization of generation expansion, (iii) the co-optimization of energy and reserves given transmission and generation expansions, (iv) the realization of system outages, and (v) the decision on optimal post-contingency corrective control. In order to solve the fivelevel model, we present a cutting plane algorithm that ultimately identifies the optimal min-max regret flexible transmission plan in a finite number of steps. The numerical studies carried out demonstrate: (a) the significant benefits associated with flexible network investment options to hedge transmission expansion plans against generation expansion uncertainty and system outages, (b) strategic planning-under-uncertainty uncovers the full benefit of flexible options which may remain undetected under deterministic, perfect information, methods and (c) the computational scalability of the proposed approach.
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Journal articleTeng F, Mu Y, Jia H, et al., 2017,
Challenges on primary frequency control and potential solution from EVs in the future GB electricity system
, Applied Energy, Vol: 194, Pages: 353-362, ISSN: 0306-2619System inertia reduction, driven by the integration of renewables, imposes significant challenges on the primary frequency control. Electrification of road transport not only reduces carbon emission by shifting from fossil fuel consumption to cleaner electricity consumption, but also potentially provide flexibility to facilitate the integration of renewables, such as supporting primary frequency control. In this context, this paper develops a techno-economic evaluation framework to quantify the challenges on primary frequency control and assess the benefits of EVs in providing primary frequency response. A simplified GB power system dynamic model is used to analyze the impact of declining system inertia on the primary frequency control and the technical potential of primary frequency response provision from EVs. Furthermore, an advanced stochastic system scheduling tool with explicitly modeling of inertia reduction effect is applied to assess the cost and emission driven by primary frequency control as well as the benefits of EVs in providing primary frequency response under two representative GB 2030 system scenarios. This paper also identifies the synergy between PFR provision from EVs and “smart charging” strategy as well as the impact of synthetic inertia from wind turbines.
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Journal articleMa S, Geng H, Lu L, et al., 2017,
Grid-synchronization stability improvement of large scale wind farm during severe grid fault
, IEEE Transactions on Power Systems, Vol: 33, Pages: 216-226, ISSN: 1558-0679Loss of synchronization between wind farm and power grid during severe grid faults would cause wind farm tripping. In this paper, the mechanism of grid-synchronization is uncovered, described as motion of an autonomous nonlinear differential equation with specific initial states. The revealed mechanism indicates that even though steady state working point exists, improper initial states and poor system dynamic properties could lead to synchronization instability. In order to keep wind farm synchronous with the power grid during severe grid faults, special requirements on system dynamic properties are stated. Moreover, to satisfy all the requirements, a current injecting method is proposed. By adjusting active and reactive output currents of the wind farm, the proposed method could ensure system synchronization stability during severe grid faults. Implementation of the proposed method on PMSG and DFIG based wind farm is illustrated. Simulation results validate the analysis and the control method.
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Journal articleEvangelou SA, Rehman-Shaikh MA, 2017,
Hybrid electric vehicle fuel minimization by DC-DC converter dual-phase-shift control
, Control Engineering Practice, Vol: 64, Pages: 44-60, ISSN: 1873-6939The paper introduces an advanced DC-link variable voltage control methodology that improves significantly the fuel economy of series Hybrid Electric Vehicles (HEVs). The DC-link connects a rectifier, a Dual Active Bridge (DAB) DC-DC converter and an inverter, interfacing respectively the two sources and the load in a series HEV powertrain. The introduced Dual Phase Shift (DPS) proportional voltage conversion ratio control scheme is realized by manipulating the phase shifts of the gating signals in the DAB converter, to regulate the amount of DAB converter power flow in and out of the DC-link. Dynamic converter efficiency models are utilized to account for switching, conduction, copper and core losses. The control methodology is proposed on the basis of improving the individual efficiency of the DAB converter but with its parameters tuned to minimize the powertrain fuel consumption. Since DPS control has one additional degree of freedom as compared to Single Phase Shift (SPS) voltage control schemes, a Lagrange Multiplier optimization method is applied to minimize the leakage inductance peak current, the main cause for switching and conduction losses. The DPS control scheme is tested in simulations with a full HEV model and two associated conventional supervisory control algorithms, together with a tuned SPS proportional voltage conversion ratio control scheme, against a conventional PI control in which the DC-link voltage follows a constant reference. Nonlinear coupling difficulties associated with the integration of varying DC-link voltage in the powertrain are also exposed and addressed.
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Journal articleRoche M, Shabbir W, Evangelou SA, 2017,
Voltage control for enhanced power electronic efficiency in series hybrid electric vehicles
, IEEE Transactions on Vehicular Technology, Vol: 66, Pages: 3645-3658, ISSN: 0018-9545The paper presents a dc-link voltage control scheme by which the power losses associated with the power electronic converters of a series hybrid electric vehicle (HEV) powertrain are reduced substantially. A dc-link commonly connects the three powertrain branches associated with series HEVs, presently interfaced by a three-phase rectifier, a three-phase inverter, and a dual-active bridge (DAB) dc-dc converter. Dynamic efficiency models of the converters are developed, and a methodology is proposed by which the dc-link voltage is varied with respect to its default value, based on the ratio between the battery and dc-link voltages. The voltage control scheme introduced varies the phase shift between the gating signals of the two DAB converter bridges, proportionally to the ratio of converter input voltage to output voltage referred to the transformer primary. This level of instantaneous control forces the converter to operate in boost mode when the battery charges and buck mode when the battery discharges, allowing the converter to persistently avoid hard switching losses over its entire operating range. The control scheme is tested in simulations with a full HEV model by comparing its performance with constant voltage and unity voltage conversion ratio PI control schemes. The scheme proves most effective for vehicles with high hybridization factor driving in an urban environment.
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Journal articleTrovato V, Martinez Sanz I, Chaudhuri B, et al., 2017,
Advanced control of thermostatic loads for rapid frequency response in Great Britain
, IEEE Transactions on Power Systems, Vol: 32, Pages: 2106-2117, ISSN: 0885-8950In the Great Britain power system, reduced system inertia (particularly during low demand conditions) and larger possible infeed loss would make grid frequency regulation extremely challenging in future. Traditional primary frequency response could be insufficient to limit the frequency variation within acceptable range. This paper shows that thermostatically controlled loads (TCLs) (domestic refrigerators) can be controlled without real-time communication and in a nondisruptive way to collectively enhance the network frequency response. The aggregated power consumption of TCLs, distributed across the system, could be controlled as a `linear' function of the locally measured frequency and its rate of change. Alternatively, their aggregated consumption could be made to follow a `pre-set' power profile depending on the estimated infeed loss. A novel technique for accurate estimation of infeed loss and consequent postfault TCL power reduction is also proposed. The effectiveness of the two TCL control strategies is compared for primary and secondary frequency response through a case study on a 36 busbar reduced equivalent of the Great Britain power system. The effect of spatial variation of transient frequencies and the time delays in frequency measurement and filtering are considered to show how the TCLs can realistically provide rapid frequency response.
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Journal articleKonstantelos I, Moreno R, Strbac G, 2017,
Coordination and uncertainty in strategic network investment: Case on the North Seas Grid
, ENERGY ECONOMICS, Vol: 64, Pages: 131-148, ISSN: 0140-9883The notion of developing a transnational offshore grid in the North Sea has attracted considerable attention in the past years due to its potential for substantial capital savings and increased scope for cross-border trade, sparking a European-wide policy debate on incentivizing integrated transmission solutions. However, one important aspect that has so far received limited attention is that benefits will largely depend on the eventual deployment pattern of electricity infrastructure which is currently characterized by severe locational, sizing and timing uncertainty. Given the lack of coordination between generation and network developments across Europe, there is a real risk for over-investment or a premature lock-in to options that exhibit limited adaptability. In the near future, important choices that have to be made concerning the network topology and amount of investment. In this paper we identify the optimal, in terms of reduced cost, network investment (including topology) in the North Seas countries under four deployment scenarios and five distinct policy choices differing in the level of offshore coordination and international market integration. By drawing comparisons between the study results, we quantify the net benefit of enabling different types of coordination under each scenario. Furthermore, we showcase a novel min–max regret optimization model and identify minimum regret first-stage commitments which could be deployed in the near future in order to enhance strategic optionality, increase adaptability to different future conditions and hence reduce any potential sub-optimality of the initial network design. In view of the above, we put forward specific policy recommendations regarding the adoption of a flexible anticipatory expansion framework for the identification of attractive investment opportunities under uncertainty.
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Journal articleScarciotti G, Astolfi A, 2017,
Data-driven model reduction by moment matching for linear and nonlinear systems
, Automatica, Vol: 79, Pages: 340-351, ISSN: 0005-1098Theory and methods to obtain reduced order models by moment matching from input/output data are presented. Algorithms for the estimation of the moments of linear and nonlinear systems are proposed. The estimates are exploited to construct families of reduced order models. These models asymptotically match the moments of the unknown system to be reduced. Conditions to enforce additional properties, e.g. matching with prescribed eigenvalues, upon the reduced order model are provided and discussed. The computational complexity of the algorithms is analyzed and their use is illustrated by two examples: we compute converging reduced order models for a linear system describing the model of a building and we provide, exploiting an approximation of the moment, a nonlinear planar reduced order model for a nonlinear DC-to-DC converter.
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Journal articlePrieto-Araujo E, Junyent-Ferre A, Clariana-Colet G, et al., 2017,
Control of Modular Multilevel Converters Under Singular Unbalanced Voltage Conditions With Equal Positive and Negative Sequence Components
, IEEE Transactions on Power Systems, Vol: 32, Pages: 2131-2141, ISSN: 0885-8950 -
Journal articleJiang J, Astolfi A, 2017,
Shared-control for a rear-wheel drive car: dynamic environments and disturbance rejection
, IEEE Transactions on Human-Machine Systems, Vol: 47, Pages: 723-734, ISSN: 2168-2291This paper studies the shared-control problem for the kinematic model of a group of rear-wheel drive cars in a (possibly) dynamic (i.e., time-varying) environment. The design of the shared-controller is based on measurements of distances to obstacles, angle differences, and the human input. The shared-controller is used to guarantee the safety of the car when the driver behaves “dangerously.” Formal properties of the closed-loop system with the shared-controller are presented through a Lyapunov-like analysis. In addition, we consider uncertainties in the dynamics and prove that the shared-controller is able to help the driver drive the car safely even in the presence of disturbances. Finally, the effectiveness of the controller is verified by two case studies: traffic at a junction and at a roundabout.
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Conference paperAngeli D, Athanasopoulos N, Jungers RM, et al., 2017,
Path-complete graphs and common Lyapunov functions
, HSCC '17, Publisher: ACM, Pages: 81-90A Path-Complete Lyapunov Function is an algebraic criterion composed of a finite number of functions, called pieces, and a directed, labeled graph defining Lyapunov inequalities between these pieces. It provides a stability certificate for discrete-time arbitrary switching systems. In this paper, we prove that the satisfiability of such a criterion implies the existence of a Common Lyapunov Function, expressed as the composition of minima and maxima of the pieces of the Path-Complete Lyapunov function. the converse however is not true even for discrete-time linear systems: we present such a system where a max-of-2 quadratics Lyapunov function exists while no corresponding Path-Complete Lyapunov function with 2 quadratic pieces exists. In light of this, we investigate when it is possible to decide if a Path- Complete Lyapunov function is less conservative than another. By analyzing the combinatorial and algebraic structure of the graph and the pieces respectively, we provide simple tools to decide when the existence of such a Lyapunov function implies that of another.
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Journal articleAnagnostou G, Pal BC, 2017,
Derivative-free Kalman filtering based approaches to dynamic state estimation for power systems with unknown inputs
, IEEE Transactions on Power Systems, Vol: 33, Pages: 116-130, ISSN: 1558-0679This paper proposes a decentralized derivative-freedynamic state estimation method in the context of a power systemwith unknown inputs, to address cases when system linearisationis cumbersome or impossible. The suggested algorithm tacklessituations when several inputs, such as the excitation voltage,are characterized by uncertainty in terms of their status. Thetechnique engages one generation unit only and its associatedmeasurements, and it remains totally independent of other systemwide measurements and parameters, facilitating in this way theapplicability of this process on a decentralized basis. The robust-ness of the method is validated against different contingencies.The impact of parameter errors, process and measurement noiseon the unknown input estimation performance is discussed. Thisunderstanding is further supported through detailed studies in arealistic power system model.
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Journal articleNanchian S, Majumdar A, Pal BC, 2017,
Ordinal optimization technique for three phase distribution network state estimation including discrete variables
, IEEE Transactions on Sustainable Energy, Vol: 8, Pages: 1528-1535, ISSN: 1949-3037This paper has discussed transformer tap position estimation with continuous and discrete variables in the context of three phase distribution state estimation (SE). Ordinal optimization (OO) technique has been applied to estimate the transformer tap position for the first time in unbalanced three phase distribution network model. The results on 129 bus system model have demonstrated that OO method can generate a reliable estimate for transformer exact tap position with discrete variables in distribution system state estimation (DSSE) and also in short period of time. In this paper the node voltages and power losses are calculated for 129 bus network. It is also demonstrated that OO is much faster than other accurate methods such HPSO. The losses obtained with OO are much accurate. In view of this OO performs better than WLS as it provides higher accuracy of the loss calculation. In a distribution network where about 5-6% of electricity generated is lost, accurate estimation of this loss has significant technical and commercial value. The authors believe the technique proposed will help realize those benefits.
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Conference paperMoreira R, Ollagnier L, Papadaskalopoulos D, et al., 2017,
Optimal Multi-Service Business Models for Electric Vehicles
, PowerTech 2017 -
Conference paperFong G, Moreira R, Strbac G, 2017,
Economic analysis of energy storage business models
, 12th IEEE Power and Energy Society PowerTech Conference 2017, Publisher: IEEEThe increasingpenetration of renewable energy systems andtheelectrification of heat and transport sectors inthe UKhave created business opportunities for flexible technologies, such as battery energy storage (BES). However,BESinvestments arestill not well understood due to a wide range and debatable technology costs that may undermine itsbusiness case. In this context, aneconomic analysis will be established to assess the economic viability ofcurrent BESbusiness models, particularly associated with multiple service portfolios. Our model quantifies the net present values (NPVs) and payback periods of BES investments considering various business models and state-of-the-art BES technologies. We determine thecommercial viability associated with different BES technologies and business models. The developed model comparesdifferent technology costs, business models(i.e. portfolio ofservicesprovided)and BES lifetimes to perform a comprehensive economic analysis on the business case for investing in BES. Several case studies under current GBmarket arrangements demonstrate that BES investment associated with multi-service business modelsoffers the best financial benefits to storage investors and achieve payback periods within 10 years’ lifetime.
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Journal articleScarciotti G, 2017,
Steady-state matching and model reduction for systems of differential-algebraic equations
, IEEE Transactions on Automatic Control, Vol: 62, Pages: 5372-5379, ISSN: 1558-2523The problem of model reduction for nonlinear differential-algebraic systems is addressed using the notions of moment and of steady-state response. These notions are formally introduced for this class of systems and families of nonlinear differential-algebraic reduced order models achieving moment matching with additional properties are presented. Stronger results for the special class of linear singular systems are provided. Two simple examples illustrate the proposed technique.
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Conference paperMoreira R, Strbac G, Papadopoulos P, et al., 2017,
Business Case in Support for Reactive Power Services from Distributed Energy Storage
, CIRED 2017 -
Book chapterScarciotti G, Astolfi A, 2017,
A Review on Model Reduction by Moment Matching for Nonlinear Systems
, Feedback Stabilization of Controlled Dynamical Systems, Editors: Petit, Publisher: Springer International Publishing, Pages: 29-52 -
Conference paperAldhaher S, Mitcheson PD, Arteaga JM, et al., 2017,
Light-Weight Wireless Power Transfer for Mid-Air Charging of Drones
, 11th European Conference on Antennas and Propagation (EUCAP), Publisher: IEEE, Pages: 336-340, ISSN: 2164-3342 -
Journal articleCai 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: 2169-3536Efficient 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.
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Journal articleCai 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: 1558-0679This 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.
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Journal articleZhang X, Xiang X, Green TC, et al., 2017,
Operation and performance of resonant modular multilevel converter with flexible step ratio
, IEEE Transactions on Industrial Electronics and Control Instrumentation, Vol: 64, Pages: 6276-6286, ISSN: 0018-9421Resonant modular multilevel converters (RMMCs)have been proposed for high voltage dc-dc applications. Using dif-ferent modulation strategies, RMMC operates in different modesand achieves flexible step ratio. To provide a comprehensive studyof RMMCs, this paper presents the modulation method achievinga wide range of step ratio with the ability of inherent-balancing.The conditions for guaranteeing the inherent-balancing abilityare provided. The operation principle and performance of theRMMC are presented in this paper, which have been exploredin a case study. The experimental results are obtained from abench-scale setup, which have verified the theoretical analysis.
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Journal articleGe M, Kerrigan EC, 2017,
Noise covariance identification for nonlinear systems using expectation maximization and moving horizon estimation
, Automatica, Vol: 77, Pages: 336-343, ISSN: 0005-1098In order to estimate states from a noise-driven state space system, the state estimator requires a priori knowledge of both process and output noise covariances. Unfortunately, noise statistics are usually unknown and have to be determined from output measurements. Current expectation maximization (EM) based algorithms for estimating noise covariances for nonlinear systems 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. In this paper, a more general nonlinear system is considered by allowing the number of process and output noises to be smaller or equal to the number of states and outputs, respectively. In order to estimate noise covariances, a semi-definite programming solver is applied, since an analytical solution is no longer easy to obtain. The expectation step in current EM algorithms rely on state estimates from the extended Kalman filter (EKF) or smoother. However, the instability and divergence problems of the EKF could cause the EM algorithm to converge to a local optimum that is far away from true values. We use moving horizon estimation instead of the EKF/smoother so that the accuracy of the covariance estimation in nonlinear systems can be significantly improved.
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Journal articlePIpelzadeh Y, Moreno R, Chaudhuri B, et al., 2017,
Corrective control with transient assistive measures: value assessment for Great Britain transmission system
, IEEE Transactions on Power Systems, Vol: 32, Pages: 1638-1650, ISSN: 0885-8950In this paper, the efficacy and value of using corrective control supported by transient assistive measures (TAM) is quantified in terms of the cost savings due to less constrained operation of the system. The example TAM is a rapid modulation of the power order of the high-voltage direct current (HVDC) links in the system so as to improve transient stability during corrective control. A sequential approach is used for the offline value assessment: a security constrained economic dispatch (SCED) module (master problem) determines the optimal generation dispatch, HVDC settings, and the corrective control actions to be used post-fault (generation and demand curtailed) so as to minimize the operational costs while ensuring static security. The transient stability module (slave problem) assesses the dynamic stability for the operating condition set by the SCED and, if needed, applies appropriate TAM to maintain the system transiently stable. If this is not possible, the master module uses a tighter set of security constraints to update the dispatch and other settings until the system can be stabilized. A case-study on the Great Britain system is used to demonstrate that corrective control actions supported by TAM facilitate significantly higher pre-fault power transfers whilst maintaining N-2 security.
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Conference paperLi PENG, Boem F, Pin G, et al., 2017,
Distributed fault detection and isolation for interconnected systems: a non-asymptotic kernel-based approach
, 20th IFAC World Congress, Publisher: IFACIn 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.
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