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Chinese Automation Congress (CAC)

作者： Zhen Xie Zhongwei Lin Zhenyu Chen Chuanxi Wang Qingru Cui Gengda Li Weidong Wang Daizhen Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control Computer and Engineering North China Electric Power University Beijing P. R. China Guodian New Energy Technology Research Institute Co. Ltd Beijing P. R. China CHN ENERGY (Shandong) New Energy Co. Ltd. Jinan P. R. China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

With the deepening research on wind farms, wake effects have gradually been paid attention to and used in wind farm optimization. During this development, the engineering wake models are adopted, which could be further improved in modeling accuracy. This paper adopts a control-oriented wake model to improve the modeling accuracy, especially in the near wake region. A double-Gaussian wake model is incorporated with appropriate wake deflection and combination models and a vertical wind profile function. Based on a Large-eddy simulated dataset, the proposed model is adopted and verified. The widely-used Gaussian wake model is also adopted and compared with the proposed model. Results show good agreement between the presented model and LES results, especially in the focused near wake region.

关键词： Wind turbines Computational modeling Wind farms Rotors Electron tubes Wind speed Mathematical model

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Reliability Evaluation of Thermal Power Units Based on AHP and ELECTRE-Ⅲ 29

Reliability Evaluation of Thermal Power Units Based on AHP a...

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第29届中国控制与决策会议

作者： Le Wei Xiaowei Li School of Control and Computer Engineering North China Electric Power University

ISBN: (纸本)9781509046584

The security and stable operation of thermal power units plays a very important role in a power system,so the reliability evaluation of thermal power units has become a critical *** combining the advantages of the Analytic Hierarchy Process(AHP) and the Elimination et Choice Translating Reality(ELECTRE) Ⅲ,a reliability evaluation method for thermal power units based on AHP and ELECTRE-Ⅲ is put forward.A new method of proposed "net" procedure is presented to rank these scheme with valued outranking *** advantages and disadvantages of the scheme are expressed from the harmony index and the discordance index,which constitute valued outranking relation by ELECTRE Ⅲ and weights of criteria are determined by *** method is clear and easily to be accepted by the decision maker with the person's actual decision thinking of human *** the results of the example analysis show that the method is feasible for the reliability evaluation of thermal power units.

关键词： Analytic Hierarchy Process(AHP) Elimination et Choice Translating Reality(ELECTRE) Thermal power unit Reliability evaluation System decision

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Improved Interactive Multiple Models Based on Self-Adaptive Turn Model for Maneuvering Target Tracking

Improved Interactive Multiple Models Based on Self-Adaptive ...

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International Conference on Information Science and Technology (ICIST)

作者： Rong Zhou Kemin Zhou Menghua Wu Jing Teng School of Control and Computer Engineering North China Electric Power University Beijing China

Tracking maneuvering target is a challenging problem and Interactive Multiple Model (IMM) is proved an effective solution for it. In multiple model, the constant turn model (CT) is usually used to describe the target's turning motion. However, fixed or partially adaptive turn angular rate μ is usually adopted in CT which leads to tracking accuracy decrease. In this paper, an improved interactive multiple model set based on self-adaptive CT model is proposed. In self-adaptive CT model, the value of the turn angular rate ω is calculated based on both x and y velocity instead of only one of them or fixed value. To verify the improvement, particle filter, which is proved an effective way to solve non Gaussian nonlinear problem, is used to track maneuvering target. The performance of the proposed multiple model set is verified in two different scenarios and compared to two widely used multiple model sets. Simulation results show that the proposed model set has better performance both in tracking accuracy and computational cost.

关键词： Computational modeling Target tracking Adaptation models Turning Acceleration Particle filters

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Attitude Synchronization for Multiple Quadrotors using Reinforcement Learning

Attitude Synchronization for Multiple Quadrotors using Reinf...

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第三十八届中国控制会议

作者： Hao Liu Wanbing Zhao Frank L.Lewis Zhong-Ping Jiang Hamidreza Modares School of Astronautics Beihang University Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies of Ministry of Education Beihang University the University of Texas at Arlington Research Institute University of Texas at Arlington the Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering New York University the University of Texas at Arlington Research Institute

In this paper, a reinforcement learning based control law is proposed to solve the attitude synchronization problem of the leader-following multi-quadrotor systems. The overall system is composed of a team of quadrotors, modeled with highly nonlinear and coupled dynamics. An optimal control solution is obtained by solving an augmented HamiltonJacobi-Bellman equation. A reinforcement learning approach is used to learn the optimal control law. Simulation results are provided to verify the effectiveness of the proposed controller.

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Multi-Sensor Node Fusion Localization Using Unscented Kalman Filter in Rough Environments

Multi-Sensor Node Fusion Localization Using Unscented Kalman...

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第30届中国控制与决策会议

作者： Yueyang Huang Yuanwei Jing Yuanbo Shi The School of Information and Control Engineering Liaoning Shihua University The School of Computer and Communication Engineering Liaoning Shihua University The School of Information Science and Engineering Northeastern University

Localization information of wireless sensor network is an important application in indoor complicate environment. In line-of-sight（LOS） environment, localization accuracy is very high. However, the measurement may be contaminated by nonline-of-sight（NLOS） propagation, which will result in localization accuracy degrades. To cover come this problem, this paper proposes a modified Kalman filter（MKF） localization method based on Unscented Kalman filter（UKF）. Firstly, test statistic method is employed to identify the NLOS condition. Then we smooth the measurement range using linear Kalman filter（LKF） and mitigate the NLOS effect using MKF. Finally, the method of UKF is used to determine the localization of unknown motion node. The validity of the proposed approach is demonstrated through the numerical simulation and experiment

关键词： nonline-of-sight Unscented Kalman filter mobile location wireless sensor network Multi-Sensor Node fusion

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Distributed bandit online convex optimization with time-varying coupled inequality constraints

arXiv

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arXiv 2019年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Johansson, Karl H. Chai, Tianyou Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the problem of distributed bandit online convex optimization with time-varying coupled inequality constraints. This problem can be defined as a repeated game between a group of learners and an adversary. The learners attempt to minimize a sequence of global loss functions and at the same time satisfy a sequence of coupled constraint functions. The global loss and the coupled constraint functions are the sum of local convex loss and constraint functions, respectively, which are adaptively generated by the adversary. The local loss and constraint functions are revealed in a bandit manner, i.e., only the values of loss and constraint functions at sampled points are revealed to the learners, and the revealed function values are held privately by each learner. We consider two scenarios, one- and two-point bandit feedback, and propose two corresponding distributed bandit online algorithms used by the learners. We show that sublinear expected regret and constraint violation are achieved by these two algorithms, if the accumulated variation of the comparator sequence also grows sublinearly. In particular, we show that O(T θ1 ) expected static regret and O(T 7/4−θ1 ) constraint violation are achieved in the one-point bandit feedback setting, and O(T max{κ,1−κ}) expected static regret and O(T 1−κ/2) constraint violation in the two-point bandit feedback setting, where θ1 ∈ (3/4, 5/6] and κ ∈ (0, 1) are user-defined trade-off parameters. Finally, these theoretical results are illustrated by numerical simulations of a simple power grid example. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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An Electric Load Forecasting Model Based on BP Neural Network and Improved Bat Algorithm Hybridized with Extremal Optimization

An Electric Load Forecasting Model Based on BP Neural Networ...

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Chinese Automation Congress (CAC)

作者： Yi-Yuan Huang Min-Rong Chen Liu-Qing Yang Kang-Di Lu Guo-Qiang Zeng School of Computer Science South China Normal University Guangzhou China Institute of Cyber Systems and Control Zhejiang University Hangzhou China National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology Wenzhou University Wenzhou China

Electric load forecasting is a vital role in obtaining effective management of modern power systems. The accuracy forecasting results will lead to the improvement of the energy efficiency and reduction of production cost. This paper presents a novel electric load forecasting model by using BP neural network and improved bat algorithm with extremal optimization called IBA-EO-BP model. First, to enhance the global search ability and diversity of original bat algorithm (BA), we propose IBA-EO by improving original BA and combining with extremal optimization. Then, considering traditional BP is more likely converge to local optimal values, the IBA-EO is employed to find out the optimal connection weight parameters in BP. Two datasets from energy market operation in Australia are selected as case study. The simulation results demonstrate that the proposed IBA-EO-BP model is much more accurate than the traditional BP forecasting model and persistence model in terms of three widely used performance indices and two statistical tests.

关键词： Load modeling Load forecasting Predictive models Mathematical model Neural networks Optimization Biological system modeling

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Surrogate Thermal Model for Power Electronic Modules using Artificial Neural Network

Surrogate Thermal Model for Power Electronic Modules using A...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Zhigen Xu Yuan Gao Xin Wang Xiaoyu Tao Qingui Xu School of Electronic and Electrical Dongguan Polytechnic Dongguan China Faculty of Engineering Power Electronics Machi nes and Control Group University of Nottingham Nottingham UK Institute for Aerospace Technology University of Nottingham Nottingham UK School of Sciences Wuhan University of Technology Wuhan China School of Computer Sciences Dongguan University of Technology Dongguan China

Virtual prototyping of power electronic modules aims to allow rapid evaluation of potential designs without building and testing physical prototypes. Among the interests in thermal models of the virtual modules, process of compact thermal models needs effective methodology to fast generate small models describing the thermal performance of a potential design. This study chooses the Generalized Minimized Residual (GMRES) Algorithm to process thermal models due to its efficiency. Based on that, a machine learning aided surrogate model is proposed for the prediction of thermal performance since existing approaches take much time to determine the thermal response to a particular input power. This surrogate model is created by training a dedicated artificial neural network (ANN) on simulation data, after that this model can quickly map the module temperature and the power input in time domain. In the training process, cross-validation method is introduced to determine which neuron structure should be selected for the practical data generated by thermal equations. The test group is noted in cross-validation to give the prediction performance of structure candidates. To verify the proposed method, the resulting data of trained surrogate models are compared with the accurate simulation data after the ANN based cross-validation.

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An Improved Firefly Algorithm Hybridized with Extremal optimization for Parameter Identification of Photovoltaic Models

An Improved Firefly Algorithm Hybridized with Extremal optim...

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Chinese Automation Congress (CAC)

作者： Liu-Qing Yang Min-Rong Chen Yi-Yuan Huang Kang-Di Lu Guo-Qiang Zeng School of Computer Science South China Normal University Guangzhou China Institute of Cyber Systems and Control Zhejiang University Hangzhou China National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology Wenzhou University Wenzhou China

Firefly algorithm (FA) has widely used to solve various complex optimization problems. However, FA has significant drawbacks in slow convergence rate and easily trapped into local optimum. To tackle these defects, this paper proposes an improved FA combined with extremal optimization (EO), named IFA-EO, where three strategies are incorporated. First, to balance tradeoff between exploration and exploitation, we adopt a new attraction model for FA operation, which combines the full attraction model and the single attraction model through the probability choice strategy. In single attraction model, inspired by the simulated annealing idea, small probability accepts the worse solution to improve the diversity of the offspring. Second, the adaptive step size is proposed according to the number of iterations. Third, we combine EO algorithm with powerful ability in local-search. IFA-EO is employed to handle three different parameters identification problems of photovoltaic model. For comparisons, we choose three swarm intelligence algorithms to compare with IFA-EO. Simulation results demonstrate the superiority of IFA-EO to other three competitors.

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A Method of Conflict Detection for Cooperative Defense Strategy in Power Industrial control System

A Method of Conflict Detection for Cooperative Defense Strat...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Hongqin Zhu Zi Wang Wei Li Dawei Su Jiawei Sun Muye Li Power Dispatching Control Center State Grid Nanjing Power Supply Company Nanjing P.R. China Nanjing NARI Information & Communication Technology Co. Ltd. NARI Group Co. Ltd./State Grid Electric Power Research Institute Co. Ltd. Nanjing P.R. China School of Computer Science and Engineering Southeast University Nanjing P.R. China Power Dispatching Control Center State Grid Jiangsu Electric Power Co. Ltd. Nanjing P.R. China

With the increasingly rampancy of network attacks and the steady progress of the national smart grid construction, the security protection of the power industrial control system is facing severe challenges. It is an effective means to improve the overall defense capability of the power industrial control system by formulating the security collaborative defense strategy and dynamically configuring the relevant equipment to make them have linkage response. For this purpose, a method of conflict detection for cooperative defense strategy in power industrial control system is proposed in this paper. Based on the formal description of cooperative defense strategy, the type of policy conflicts is analyzed according to the relationship between policy actions and system states. And the policy execution is simulated for detecting conflict by establishing the temporal relationship between policy actions. The experimental results show that this method can reduce the dependence on the system administrator, and can quickly and accurately find the conflicts in the collaborative defense strategy.

关键词： Couplings Industrial control Collaboration Big Data Smart grids Security

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