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Adaptive predictive control of a small capacity SMES unit for improved frequency control of a wind-diesel power system

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IET RENEWABLE POWER GENERATION 2017年第14期11卷 1832-1840页

作者： Zargar, Mubashar Yaqoob Mufti, Mairaj Ud-Din Lone, Shameem Ahmad Natl Inst Technol Dept Elect Engn Srinagar 190006 Jammu & Kashmir India

Energy storage is becoming increasingly important for isolated power systems having overall low inertia. Among many energy storage devices, superconducting magnetic energy storage (SMES) is most suited for improved frequency control in isolated power systems, due to its outstanding advantages. However, a small rating SMES device has operational constraints, therefore a suitable control strategy is required for its profitable and constrained operation. An adaptive controller which encapsulates on-line identification with model predictive control is proposed in this paper. A recursive least-squares algorithm is used to identify a reduced-order model of wind-diesel power system on-line. Based on the identified model and a simple discrete time model of SMES unit, an adaptive generalized predictive control scheme (AGPC) considering constraints on SMES current level and converter rating is formulated. The scheme yields a control signal which on one hand keeps the system frequency deviations to minimum and on the other hand forces the SMES device to operate within and near its operational constraints, for profitable operation. Simulation studies are performed to illustrate the potency of the proposed strategy in achieving all the control objectives.

关键词： adaptive control predictive control wind power plants diesel-electric power stations power generation control superconducting magnet energy storage power system identification least squares approximations discrete time systems power convertors small capacity SMES unit improved frequency control wind-diesel power system isolated power system superconducting magnetic energy storage device SMES device encapsulate online identification recursive least-square algorithm reduced-order model discrete time model adaptive generalised predictive control scheme AGPC scheme converter rating S-function code MATLAB

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Multichannel optimal control algorithm for adaptive optics system

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OPTIK 2016年第18期127卷 7210-7217页

作者： Yan, Zhao-jun Yang, Peng-qian Chinese Acad Sci Shanghai Astron Observ Astron Op Instrument Grp Shanghai 200030 Peoples R China Chinese Acad Sci Joint Lab High Power Laser Phys Shanghai Inst Opt & Fine Mech Shanghai 201800 Peoples R China

In this paper we propose a multichannel optimal control algorithm (MOCA) which can be applied to practical real-time closed-loop adaptive optics system (AOS). The MOCA, doesn't like the traditional ones, considers both the effect of atmospheric turbulence and of the time delay. The control parameters are optimized timely through iterative calculations in order to let the system working at the best controlling state. Here we study, by the means of numerical simulations, the multichannel optimal control method with recursive least square (RLS) algorithm, considering a 61-element AOS as an example. Analyses were made on convergence, control performance and bandwidth of this algorithm. Compared with the classical optimal proportional-integral control algorithm, simulation results show that the residual error caused by the atmospheric turbulence and servo lag in the system are reduced more effectively by using MOCA which has good adaptability and could improve the close-loop bandwidth of the AOS. (C) 2016 Elsevier GmbH. All rights reserved.

关键词： Adaptive optics Multichannel optimal control algorithm Optimal proportional-integral control algorithm recursive least-square algorithm

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Real-time estimation of AC-grid short circuit capacity for HVDC control application

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第4期11卷 838-846页

作者： Babazadeh, Davood Muthukrishnan, Arvind Mitra, Pinaki Larsson, Tomas Nordstrom, Lars KTH Royal Inst Technol Sch Elect Engn Dept Elect Power & Energy Syst Stockholm Sweden ABB HVDC Ludvika Sweden

Being able to estimate the AC grid strength using short circuit capacity (SCC) from the perspective of a connected high-voltage direct current (HVDC) station allows adjustment of converter control parameters or to select the converter's operational control mode. The SCC can be calculated by estimation of the grid's impedance and its equivalent voltage. This study presents the operational and practical challenges in real-time implementation of the grid estimation algorithms especially for HVDC applications. This study shows that the recursive least-square algorithm can be very efficiently used for the real-time estimation of SCC. This technique forms a regression problem using algebraic complex equations with an objective to minimise the error between estimated and measured parameters. The algorithm has been reformulated and simplified to make it non-complex without the use of matrices, in order to facilitate further implementation on an industrial real-time controller. The performance of the real-time implementation has been evaluated using a hardware-in-the-loop platform. A sensitivity analysis has been also carried out to study the impact of different parameters and operational conditions on the performance of the estimation algorithm. Finally, the actual application of real-time SCC estimation for the HVDC systems has been demonstrated.

关键词： HVDC power transmission HVDC power convertors power transmission control estimation theory least squares approximations algebra regression analysis sensitivity analysis power grids AC-grid short circuit capacity HVDC control application AC grid strength SCC estimation high-voltage direct current station HVDC station converter control parameters converter operational control mode grid impedance equivalent voltage grid estimation algorithms recursive least-square algorithm regression problem algebraic complex equations industrial real-time controller sensitivity analysis HVDC systems

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Incremental recursive least-squares Identification for the Systems under Poor Observation Condition 31

Incremental Recursive Least-squares Identification for the S...

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31st Chinese Control And Decision Conference (CCDC)

作者： Zhou, Han Ma, Guangpeng Yan, Guangming Sun, Xiaojun Heilongjiang Univ Elect Engn Inst Harbin 150080 Peoples R China

ISBN: (纸本)9781728101057

For the autoregressive (AR) signal under poor observation condition, a kind of incremental recursive least-square (IRLS) algorithm is presented based on the incremental observation equation. Applying the convergence of RLS algorithm, it can be easily proved that the obtained estimates of model parameters and noise variance converge to the corresponding true values with probability one, i.e. they are strongly consistent. A simulation example shows its effectiveness.

关键词： Autoregressive (AR) Signal Incremental AR Model Parameter Estimation recursive least-square algorithm Strong Consistence

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An Embedded Structure of Model Reference Adaptive System

An Embedded Structure of Model Reference Adaptive System

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10th International Conference on Control, Automation, Robotics and Vision

作者： Yang, Qiwen Xue, Yuncan Yang, Simon X. Li, Qiuye Li, Rong Meng, Max Q. -H Hohai Univ Coll Comp & Informat Engn Changzhou Peoples R China Univ Guelph Sch Engn Guelph ON N1G 2W1 Canada Chinese Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

ISBN: (纸本)9781424422869

The traditional model reference adaptive system (MRAS) is of parallel configuration. By representing the reference model as an equivalent closed-loop subsystem, these two subsystems can share a controller virtually. An embedded structure of MRAS is thereby presented. In this paper, two approaches are developed for designing the adaptive laws. The adaptive law based on Lyapunov stability theory is designed for low-order systems. The adaptive law based on the recursive least-square (RLS) algorithm is suitable for both low- and high-order systems. The RLS-based adaptive law provides a quick convergence rate for the controller adaption. MRAS with RLS-based adaptation law performs better in trajectory tracking and model following. Simulation results show the effectiveness of the proposed method.

关键词： Model reference adaptive system Lyapunov function recursive least-square algorithm PI controller

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Finite-time identification of the Thevenin equivalent parameters in power grids

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 116卷 105534-000页

作者： Arancibia, Arnaldo Soriano-Rangel, Carlos A. Mancilla-David, Fernando Ortega, Romeo Strunz, Kai Tech Univ Berlin Fac Elect Engn & Comp Sci 4 Inst Sustainable Elect Networks & Sources Energy Einsteinufer 11 EMH-1 D-10587 Berlin Germany Univ Colorado Dept Elect Engn 1200 Larimer St Denver CO 80204 USA Cent Supelec CNRS LSS F-91192 Gif Sur Yvette France

This paper presents a novel algorithm for online identification of the Thevenin equivalent parameters in ac three-phase power grids of inductive nature. One unique property of the algorithm is to ensure convergence of the estimated parameters within finite time, provided that a weak excitation condition-necessary for identifying offline parameters-is verified. After a finite time, the algorithm reduces to a standard recursive least-squares algorithm to track possible changes in the parameters. Moreover, the algorithm requires neither circuit excitation nor active manipulation of the circuit. The proposed algorithm is evaluated via computer simulation and experimental prototyping for a case study consisting of a three-phase inverter connected to a mains power source via an inductive circuit. Results show that the proposed method is able to successfully identify the Thevenin equivalent parameters.

关键词： Thevenin equivalent Parameter estimation Online estimator recursive least-square algorithm

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Adaptive predictive error filter-based maximum power point tracking algorithm for a photovoltaic system

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JOURNAL OF ENGINEERING-JOE 2016年第4期2016卷 54-61页

作者： Subudhi, Bidyadhar Pradhan, Raseswari Natl Inst Technol Dept Elect Engn Rourkela India Veer Surendra Sai Univ Technol Dept Elect Engn Sambalpur 769008 India

This study presents a new adaptive predictive error filter-based maximum power point tracker (MPPT) for a photovoltaic (PV) system. This MPPT is developed using the concept of an adaptive predictive filter (APEF) that consists of a one-tap finite impulse response. The filter step-size of the APEF is adapted using a recursive least-square (RLS) algorithm with an adaptive forgetting factor. The specialty of this MPPT is that it performs MPP tracking operation in a single step. It performs two functions: namely, MPP estimation adjusting operating point of a boost converter at MPP and then filtering of the PV voltage fluctuation after MPPT action. Thus, the proposed MPPT is compact and efficient with less computational complexities than existing MPPTs such as perturb and observe (P&O) and incremental conductance. The filter part of the proposed RLS-APEF-MPPT is a discrete PID-controller, where PD-part is tuned using pole-placement strategy and integral-term is fixed. The performances of the proposed RLS-APEF-MPPT were verified using experimentation on a prototype PV system. Its performances were compared with that of P&O, adaptive-P&O-MPPTs. From the observed results, it is confirmed that the proposed MPPT exhibits superior performance.

关键词： photovoltaic power systems adaptive filters predictive control adaptive control maximum power point trackers FIR filters recursive estimation least squares approximations computational complexity three-term control pole-placement strategy discrete PID-controller RLS-APEF-MPPT algorithm less computational complexities PV voltage fluctuation filtering boost converter MPP estimation adjusting operating point adaptive forgetting factor recursive least-square algorithm one-tap finite impulse response prototype PV system maximum power point tracking algorithm photovoltaic system APEF-based maximum power point tracker adaptive predictive error filter-based MPPT

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