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Coordinated Dispatch Optimization between the Main Grid and Virtual Power Plants Based on multi-parametric quadratic programming

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ENERGIES 2023年第15期16卷 5593页

作者： Yang, Guixing Xu, Mingze Wang, Weiqing Lei, Shunbo Xinjiang Univ Urumqi 830000 Peoples R China Chinese Univ Hong Kong Shenzhen Shenzhen 518000 Peoples R China

Virtual power plants (VPPs) are a critical technology for distribution systems that can integrate various renewable energy resourcescontrollable loads and energy storage systems into one specific power plant through a distributed energy management system. This paper proposes a coordinated dispatch optimization model between the main grid and VPPs aiming to minimize both the power generation cost and total system active loss. When the time of the equivalent dispatching model is not divisible due to the existence of a time coupling constraint inside the VPPs, this model can obtain the global optimal solution through iteration between the main grid and the VPPs. By employing multi-parametric quadratic programming to obtain accurate critical domains and optimal cost functions, the convergence speed and stability are significantly improved. Additionally, a reactive power and voltage optimization technique leveraging the generalized Benders decomposition is presented for the coordination of the main grid and the VPPs. Moreover, the impact of distributed energy resource (DER) clusters on the main grid was studied, from which we proved that the proposed approach can expeditiously abate energy production expenditure and system active dissipation whilst enhancing the system equilibrium.

关键词： virtual power plants coordinated dispatch multi-parametric quadratic programming generalized Benders' decomposition

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Explicit MPC Solution Using Hasse Diagrams: Construction, Storage and Retrieval 27th

Explicit MPC Solution Using Hasse Diagrams: Construction, St...

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27th International Conference on Difference Equations and Applications (ICDEA)

作者： Mihai, Stefan S. Stoican, Florin Ciubotaru, Bogdan D. Natl Univ Sci & Technol Politehn Bucharest Dept Automat Control & Syst Engn 313 Splaiul IndependenteiSect 6 Bucharest 060042 Romania

ISBN: (纸本)9783031510519;9783031510496;9783031510489

This chapter provides new methods for the construction, storage and retrieval of the explicit MPC solution in the case with quadratic cost and linear constraints. By exploiting the geometric interpretation of the MPC problem, we: (i) construct the explicit solution (i.e., enumerate the critical regions and associated affine laws) in an efficient manner;(ii) store it as a partially ordered set;and (iii) provide a modified graph traversal algorithm for efficient point location (i.e., identifying the currently active critical region and its associated control law).

关键词： Explicit MPC Hasse diagram Point location problem multi-parametric quadratic programming

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Coordinated Optimal Power Flow for Integrated Active Distribution Network and Virtual Power Plants Using Decentralized Algorithm

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第4期36卷 3541-3551页

作者： Wu, Chenyu Gu, Wei Zhou, Suyang Chen, Xiaogang Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China State Grid Zhejiang Elect Power Co Hangzhou 310007 Peoples R China

With the wide application of distributed energy technology in active distribution networks (ADNs), virtual power plants (VPPs) are introduced as a promising integration and management technology. To coordinate their operation schedule and ensure confidentiality, we establish a coordinated optimal power flow (OPF) model and propose an efficient decentralized algorithm based on multi-parametric quadratic programming and Benders decomposition. In feasible sub-problems, the quadratic exchanging functions are built, which greatly accelerates the convergence process. In infeasible sub-problems, feasible cut sets can be calculated based on benders decomposition. Besides, an effective relaxation method is developed to address the degeneracy problem. To eliminate redundant feasible cut sets, a predetermined feasible region is constructed according to the characteristics of each VPP. The effectiveness of the proposed method is demonstrated via numerical tests using two cases of different scales. The results show that the proposed method converges much faster than some prevailing methods. Furthermore, the coordinated OPF has a better fuel economy than the conventional OPF scheme.

关键词： Generators Load flow Manganese Economics Reactive power Convergence Security Active distribution network coordinated optimal power flow multi-parametric quadratic programming virtual power plant

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Design of Line-of-Sight Guidance Law and a Constrained Optimal Controller for an Autonomous Underwater Vehicle

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2021年第1期68卷 416-420页

作者： Rout, Raja Subudhi, Bidyadhar Manipal Univ Jaipur Dept Mechatron Engn Jaipur 303007 Rajasthan India Indian Inst Technol Goa Sch Elect Sci Ponda 403401 Goa India

A line-of-sight (LOS) guidance law with an explicit model predictive control (MPC) is proposed for an underactuated autonomous underwater vehicle (AUV). The derived LOS law is based on quaternion angles thus avoids the problem of singularity inherited in Euler angles. The proposed guidance and control scheme is computationally inexpensive and generates a robust optimal control signal for AUV dynamics. In view of the practical implementation, the constraints on control planes and parametric uncertainties are taken into consideration while designing the proposed control law. The effectiveness of the proposed controller is verified by both simulation and experimentation using a prototype AUV developed in the laboratory. Subsequently, multiple experiments were conducted to ascertain the applicability of the proposed algorithm in a practical scenario.

关键词： Vehicle dynamics Kinematics Power system dynamics Dynamics Mathematical model Quaternions Circuits and systems Autonomous underwater vehicle actuator constraints multi-parametric quadratic programming model predictive controller

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A Softly Switching multiple Model Predictive Control for Aero-engines 6th

A Softly Switching Multiple Model Predictive Control for Aer...

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6th IFAC Conference on Engine Powertrain Control, Simulation and Modeling (E-COSM)

作者： Hao, Guang-Chao Zhang, Yong-Liang Wen, Si-Xin Du, Xian Yang, Bin Sun, Xi-Ming Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Beijing Power Machinery Inst Beijing 100074 CO Peoples R China Dalian Univ Technol Minist Educ Key Lab Intelligent Control & Optimizat Ind Equip Dalian 116024 CO Peoples R China

This paper presents a multiple model predictive control (MPC) with a softly switching for aero-engines. Firstly, the different local working regions of the nonlinear aeroengines model are linearized. Then, a model predictive controller is designed for each linear model. The traditional hard switching methods for multiple model predictive controllers may result in bad transient behavior. Therefore, a softly switching mechanism is studied in this paper, which adopts the convex combination of the MPC objective functions before and after switching to ensure the smooth transition of aero-engines when switching in adjacent regions. The multi-parametric quadratic programming (MP-QP) algorithm is then used to solve the suboptimal solution of the problem, which reduces the amount of calculation and obtains an explicit solution. Finally, the reported simulation results of the turbofan engine verify the effectiveness of the suggested algorithm. Copyright (C) 2021 The Authors.

关键词： Aero-engines control multiple model predictive control Softly switching multi-parametric quadratic programming

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A Softly Switching multiple Model Predictive Control for Aero-engines ⁎

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IFAC-PapersOnLine 2021年第10期54卷 477-482页

作者： Guang-Chao Hao Yong-Liang Zhang Si-Xin Wen Xian Du Bin Yang Xi-Ming Sun School of Control Science and Engineering Dalian University of Technology Dalian CO 116024 China Beijing Power Machinery Institute Beijing CO 100074 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian CO 116024 China

This paper presents a multiple model predictive control (MPC) with a softly switching for aero-engines. Firstly, the different local working regions of the nonlinear aeroengines model are linearized. Then, a model predictive controller is designed for each linear model. The traditional hard switching methods for multiple model predictive controllers may result in bad transient behavior. Therefore, a softly switching mechanism is studied in this paper, which adopts the convex combination of the MPC objective functions before and after switching to ensure the smooth transition of aero-engines when switching in adjacent regions. The multi-parametric quadratic programming (MP-QP) algorithm is then used to solve the sub-optimal solution of the problem, which reduces the amount of calculation and obtains an explicit solution. Finally, the reported simulation results of the turbofan engine verify the effectiveness of the suggested algorithm.

关键词： Aero-engines control multiple model predictive control Softly switching multi-parametric quadratic programming

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Verification of Explicit Model Predictive Control through Double-lane-change Maneuver 27

Verification of Explicit Model Predictive Control through Do...

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27th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Lee, Junho Chang, Hyuk-Jun Kookmin Univ Dept Secured Smart Elect Vehicle Seoul South Korea Kookmin Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781538637050

In this paper, we analyze and verify explicit model predictive control (MPC) through the automated double-lane-change (DLC) maneuver by employing MATLAB/Simulink and CarSim. MPC has become a useful optimization method because it can anticipate future events of a system and fulfill constraints on states and inputs. However, the formidable computational complexities of online optimization are considered as a major drawback. Therefore, explicit MPC has been proposed and demonstrated to reduce the computational burden by treating the state vector as a parameter vector. This technique is referred to as multi-parametric quadratic programming (mp-QP). A DLC test of CarSim has been conducted to prove the efficacy of the proposed controller in an autonomous driving situation. In addition, a DLC test conducted using a driver model in CarSim, which is designed based on a MPC scheme, is presented for comparison with the proposed controller. The range of the prediction horizon is varied to explain the relation between the prediction horizon and the performance of the proposed controller;also, a variation of vehicle speed is implemented to prove the robustness of the proposed controller. The main contribution of this paper is to demonstrate the reduction of the computational loads of explicit MPC so that the MPC-based scheme can be designed using not only a 32-bit microcontrollers but also 16-bit, 8 bit- microcontrollers, or a field programmable gate array (FPGA), featuring relatively lower development costs and longer battery consistence.

关键词： Model predictive control explicit model predictive control multi-parametric quadratic programming double lane change constrained optimization

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Linear Machine: A Novel Approach to Point Location Problem

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IFAC Proceedings Volumes 2013年第32期46卷 445-450页

作者： Astha Airan Sharad Bhartiya Mani Bhushan Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai India

In recent literature, explicit model predictive control (e-MPC) has been proposed to facilitate implementation of the popular model predictive control (MPC) approach to fast dynamical systems. e-MPC is based on multi-parametric programming. The key idea in e-MPC is to replace the online optimization problem in MPC by a point location problem. After locating the current point, the control law is simply computed as an appropriate linear function of the states. A variety of approaches have been proposed in literature for the point location problem. In this work, we present a novel approach based on linear machines for solving this problem. Linear machines are widely used in multi-category pattern classification literature for developing linear classifiers given representative data from various classes. The idea in linear machines is to associate a linear discriminant function with each class. A given point is then assigned to the class with the largest discriminant function value. In this work, we develop an approach for identifying such discriminant functions from the hyperplanes characterizing the given regions as in multi-parametric programming. Apart from being an elegant solution to the point location problem as required in e-MPC, the proposed approach also links two apparently diverse fields namely e-MPC and multi-category pattern classification. To illustrate the utility of the approach, it is implemented on a hypothetical example as well as on a quadruple tank benchmark system taken from literature.

关键词： explicit model predictive control linear machine classifier multi-parametric quadratic programming

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A comparison of the computational efficiency of multi-parametric predictive control using generalised function parameterisations

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IFAC Proceedings Volumes 2012年第15期45卷 451-456页

作者： B. Khan J.A. Rossiter Automatic Control and Systems Eng. University of Sheffield UK

This paper considers the computational efficiency of using generalised function parameterisations for multi-parametric quadratic programming (mp-QP) solutions to MPC. Earlier work demonstrated the potential of Laguerre parameterisations for improving computational efficiency in that the parametric solutions either required fewer regions and/or gave larger volumes. This paper considers the potential of extending this concept to more general function parameterisations. Specifically the aim is to consider to what extent different function parameterisations affect the parametric solution complexity and feasible volumes. Extensive simulation results which suggest there are indeed benefits from using more general parameterisations than Laguerre.

关键词： Predictive control multi-parametric quadratic programming Feasibility Generalised function parametrisations

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Explicit Model Predictive Control of Networked Control Systems with Packet Dropout

Explicit Model Predictive Control of Networked Control Syste...

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24th Chinese Control and Decision Conference (CCDC)

作者： Zhang Ju Qin Ting Zhang Haihua Zhejiang Univ Technol Coll Informat Engn Hangzhou 310032 Zhejiang Peoples R China

ISBN: (纸本)9781457720727

In order to estimate the packet dropout in Networked Control Systems (NCS), this paper presents an explicit model predictive control. We firstly transform the model for networked control systems with data packet dropout into piecewise affine form. Then we solve a constrained optimal control problem with PWA model. By using the method of explicit predictive control, which is based on multi-parametric quadratic programming method, we get a state feedback control law which is explicit to the states. Based on this control law, we show that the control law is piece-wise linear and continuous for the finite horizon problem. Thus, the on-line control computation reduces to the simple evaluation of a piecewise affine model. Since the algorithm does not require repeated line optimization, it improves the on-line calculation speed of the controller, making the system better real-time. The algorithm deals with the data packet dropout well. Simulation results show the effectiveness of the method.

关键词： network control system explicit model predictive control multi-parametric quadratic programming piecewise affine model

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