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Self-adaptive differential approach for transient stability constrained optimal power flow

IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第15期10卷 3717-3726页

作者： Chen, Yingying Luo, Fengji Xu, Yan Qiu, Jing Univ Sydney Sch Elect & Informat Engn Sydney NSW Australia Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing Peoples R China Univ Sydney Sch Civil Engn Sydney NSW Australia Univ Newcastle Ctr Intelligent Elect Networks Newcastle NSW Australia

A new transient stability-constrained optimal power flow (TSCOPF) model for power system optimal operations is presented in this study. The proposed model is a non-linear, non-convex, discrete, and non-differentiable optimisation problem, and very difficult to be solved by classic programming algorithms. In this study, an effective optimisation framework is developed to address the TSCOPF problem. The self-adaptive differential evolution (SaDE) algorithm is employed in the framework, which can effectively eliminate the needs for the strategy selection process and at the same time improve the robustness of the DE search process. The benchmark New England 10-generator, 39-bus system is used to verify the efficacy of this algorithm. The simulation result obtained using SaDE is compared with both conventional mathematical method and the recently published heuristic methods for OPF problems. The simulation results reveal that the SaDE optimisation technique outperforms other algorithms in both terms of robustness and solution quality.

关键词： load flow power system transient stability nonlinear programming concave programming evolutionary computation search problems transient stability-constrained optimal power flow model power system optimal operations TSCOPF model nonlinear optimisation problem nonconvex optimisation problem discrete optimisation problem nondifferentiable optimisation problem self-adaptive differential evolution algorithm SaDE algorithm DE search process robustness improvement New England 10-generator 39-bus system

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Collision and obstacle avoidance for agents based on velocity programming in unknown environments under kinematical constraints

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IET CONTROL THEORY AND APPLICATIONS 2023年第9期17卷 1089-1104页

作者： Xiong, Zhigang Luo, Yasong Liu, Zhong Zhang, Jianqiang Liu, Zhikun Naval Univ Engn Coll Weap Engn Wuhan Peoples R China Naval Univ Engn Coll Weap Engn Wuhan 430000 Peoples R China

This paper conducts research on obstacle and collision avoidance under kinematical constraints in unknown environments, while communication and simultaneous localization and mapping (SLAM) are unavailable to agents. Then a strategy based on mixed-integer programming is proposed, in which velocity constraints are established with a modified Barrier function for obstacles that can be completely detected. As for obstacles that cannot be completely detected, a feasible set is built for the velocity programming based on the convex theory, and the contradicted constraints are addressed with the logic metric method. Besides, the actuator saturation is avoided by converting kinematical constraints into the restrictions on the magnitude, the restrictions on the direction, and the negative correlations between the components of the velocity respectively. Given that invalid nominal velocity leads to collisions, a virtual goal is estimated for nominal velocity improvement. In addition, the local extremum brought by empty programming space due to multiple constraints is repaired by fixing the velocity constraints. The feasibility of the proposed strategy is analyzed, and numerical simulations are provided to verify the effectiveness of the proposed strategy.

关键词： collision avoidance concave programming constraint satisfaction problems convex programming dynamic programming integer programming linear programming Lyapunov methods multi-robot systems

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Research on three-phase optimal power flow for distribution networks based on constant Hessian matrix

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第1期12卷 241-246页

作者： Zhao, Fengzhan Zhao, Tingting Ju, Yuntao Ma, Kang Zhou, Xianfei China Agr Univ Coll Informat & Elect Engn Beijing Peoples R China Univ Bath Dept Elect & Elect Engn Bath Avon England State Grid Beijing Elect Power Co Beijing Peoples R China

The optimal power flow (OPF) problem for active distribution networks with distributed generation (DG) and a variety of discretely adjustable devices (e.g. on-load tap-changers, OLTCs) is essentially a non-convex, non-linear, mixed-integer optimisation problem. In this study, the quadratic model of three-phase OLTCs is proposed by adding branch currents as unknown variables, which guarantee a constant Hessian matrix throughout iterations. This study proposes a three-phase OPF model for active distribution networks, considering a three-phase DG model. The OPF model is solved by an interior point method incorporating a quadratic penalty function as opposed to a Gaussian penalty function. Furthermore, a voltage regulator is also incorporated into the OPF model to form an integrated regulation strategy. The methodology is tested and validated on the IEEE 13-bus three-phase unbalanced test system.

关键词： on load tap changers power distribution control power generation control voltage control iterative methods Hessian matrices power distribution economics distributed power generation concave programming nonlinear programming integer programming load flow control three-phase optimal power flow constant Hessian matrix active distribution network distributed generation three-phase OPF model three-phase DG model nonconvex optimisation problem nonlinear optimisation problem mixed-integer optimisation problem three-phase OLTC quadratic model iteration method interior point method quadratic penalty function Gaussian penalty function voltage regulator IEEE 13-bus three-phase unbalanced test system integrated regulation strategy on-load tap-changers

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Non-local weighted fuzzy energy-based active contour model with level set evolution starting with a constant function

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IET IMAGE PROCESSING 2019年第7期13卷 1115-1123页

作者： Lv, Hongli Fu, Shujun Zhang, Caiming Liu, Xuya Shandong Univ Sch Math Jinan 250100 Shandong Peoples R China Shandong Univ Sch Comp Sci & Technol Jinan 250101 Shandong Peoples R China

In the traditional active contour models, global region-based methods fail to segment images with intensity inhomogeneity, and local region-based methods are sensitive to initial contour. In this study, a novel fuzzy energy-based active contour model is proposed to segment medical images, which are always corrupted by intensity inhomogeneity. In order to deal with intensity inhomogeneity, a local energy term is first constructed by substituting a non-local weight for Gaussian kernel widely used in traditional local region-based models. Second, the defined adaptive force can drive the level set function to adaptively increase or decrease according to image intensity information. Therefore, the initial contour can be initialised as a constant function, which eliminates the problem caused by contour initialisation. Moreover, the proposed active contour model is a convex function. Thus, the problem, resulting from optimising a non-convex functional in the traditional active contour models, can be avoided. Experimental results validate the superiorities and effectiveness of the proposed model for image segmentation with comparisons of those yielded by several state-of-the-art techniques.

关键词： fuzzy set theory image segmentation medical image processing concave programming convex programming Gaussian processes constant function contour initialisation convex function nonlocal weighted fuzzy energy-based active contour model level set evolution global region-based methods intensity inhomogeneity local region-based methods initial contour novel fuzzy energy-based active contour model local energy term image intensity information medical image segmentation Gaussian kernel adaptive force nonconvex functional optimization

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Joint beamforming and power allocation for secure communication in cognitive radio networks

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IET COMMUNICATIONS 2016年第10期10卷 1156-1162页

作者： Chen, Tao Yuan, HuaQiang Zhao, TieZhu Zhang, ZuSheng Ao, Xin Dongguan Univ Technol Dept Comp Coll Dongguan Peoples R China

In this study, secure communication in cognitive radio networks is investigated. A cooperative jammer is utilised to transmit artificial noise for interfering with the eavesdropper. The authors' objective is to maximise the available secrecy rate of the secondary user (SU) under the interference power constraint at the primary user and the global transmit power constraint at the transmitters. In that case, beamforming vectors of the SU transmitter and the cooperative jammer, and power allocation between them need to be optimised. However, the optimisation problem is non-convex and hard to solve. In order to tackle it, two suboptimal algorithms are proposed: complete orthogonal projection and partial orthogonal projection. In these algorithms, the original optimisation problems are first decoupled into two sub-problems, which deal with the transmit beamforming vectors and power allocation, respectively. Then, the optimal solution is obtained by iteration alternately. Finally, simulation results verify the effectiveness of the proposed algorithms.

关键词： cognitive radio telecommunication security array signal processing cooperative communication concave programming radiofrequency interference joint beamforming-power allocation scheme secure communication cognitive radio networks cooperative jammer artificial noise eavesdropper available secrecy rate secondary user SU transmitter interference power constraint primary user global transmit power constraint beamforming vector nonconvex optimisation problem suboptimal algorithm complete orthogonal projection partial orthogonal projection transmit beamforming vector iteration

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Energy cooperation in multi-user wireless-powered relay networks

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IET COMMUNICATIONS 2015年第11期9卷 1412-1420页

作者： Yang, Dingcheng Zhou, Xiaoxiao Xiao, Lin Wu, Fahui Nanchang Univ Informat Engn Sch Nanchang 330031 Peoples R China

In this study, energy cooperation schemes are considered in wireless cooperative networks;in these networks multiple pairs of users communicate with each other, assisted by an energy harvesting relay that gathers energy from the received signal by applying a power splitting scheme and forwards the received signal by using the harvested energy. This study is focused on the energy cooperation strategies for the relay to distribute the harvested energy between the multiple user pairs in amplify-and-forward and in decode-and-forward modes. Specifically, optimal solutions without energy cooperation at the relay node are first proposed and then the authors formulate the energy cooperation optimisation problem. This optimisation problem is non-convex. They propose an iterative energy cooperation solution to maximise the system throughput by assigning the proper harvested energy to each user pair for both types of forwarding models. They show that with the proposed method, the update in each iteration consists of a group of convex problems with a continuous parameter. Moreover, they derive the optimal solution to these convex problems in closed-form and it is shown that the solution can converge to a local optimum. Simulation results demonstrate that the proposed algorithm outperforms the traditional non-cooperation method.

关键词： relay networks (telecommunication) cooperative communication energy harvesting telecommunication power supplies amplify and forward communication decode and forward communication concave programming convex programming iterative methods radio networks multiuser wireless-powered relay networks energy cooperation schemes wireless cooperative networks energy harvesting relay power splitting scheme received signal amplify-and-forward modes decode-and-forward modes energy cooperation optimisation problem nonconvex optimisation problem convex problems local optimum iterative energy cooperation solution

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Design of amplify-and-forward relaying schemes for layered relay networks

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IET COMMUNICATIONS 2014年第11期8卷 1910-1918页

作者： Liu, Binyue Cai, Ning Xidian Univ State Key Lab ISN Xian Peoples R China

This paper studies amplify-and-forward (AF) relaying schemes for layered relay networks. The design of the network-wide optimal AF scheme in terms of maximum end-to-end transmission rate is mathematically formulated as a non-convex optimisation problem which is computationally intractable in general. Therefore, the authors restrict it to a localised optimisation problem and develop a second-order cone programming-based approach to efficiently solve it, which yields localised optimal AF schemes for the relays at a specific layer. To improve the performance of a given network-wide AF scheme, a low-complexity alternating algorithm is proposed based on the localised optimisation technique. To reduce the computational complexity, they also derive localised suboptimal schemes in closed form. With relays at one layer applying this scheme and the other relays transmitting with the maximum allowable powers, a simple network-wide AF scheme is derived, which is proved to be asymptotically optimal in the generalised high-SNR regime. Finally, simulations are used to illustrate the validity of the proposed schemes.

关键词： amplify and forward communication relay networks (telecommunication) mathematical analysis concave programming computational complexity amplify-and-forward relaying scheme layered relay network network-wide optimal AF relaying scheme maximum end-to-end transmission rate mathematical formulation nonconvex optimisation problem second-order cone programming-based approach low-complexity alternating algorithm computational complexity localised suboptimal scheme generalised high-SNR regime

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A numerical approach for solving some convex maximization problems

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JOURNAL OF GLOBAL OPTIMIZATION 2006年第1期35卷 85-101页

作者： Enkhbat, R. Barsbold, B. Kamada, Masaru Natl Univ Mongolia Sch Math & Comp Sci Ulaanbaatar Mongolia Ibaraki Univ Dept Comp & Informat Sci Ibaraki Japan

We are concerned with concave programming or the convex maximization problem. In this paper, we propose a method and algorithm for solving the problem which are based on the global optimality conditions first obtained by Strekalovsky (Soviet Mathematical Doklady, 8(1987)). The method continues approaches given in (Journal of global optimization, 8(1996);Journal of Nolinear and convex Analyses 4(1)(2003)). Under certain assumptions a convergence property of the proposed method has been established. Some computational results are reported. Also, it has been shown that the problem of finding the largest eigenvalue can be found by the proposed method.

关键词： algorithm concave programming global maximizer global optimization simple set

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Cuckoo search algorithm for non-convex economic dispatch

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IET GENERATION TRANSMISSION & DISTRIBUTION 2013年第6期7卷 645-654页

作者： Vo, Dieu N. Schegner, Peter Ongsakul, Weerakorn Ho Chi Minh City Univ Technol Dept Power Syst Ho Chi Minh City Vietnam Tech Univ Dresden Inst Elect Power Syst & High Voltage Engn D-01069 Dresden Germany Asian Inst Technol Energy Field Study Sch Environm Resources & Dev Pathum Thani 12120 Thailand

This study proposes a cuckoo search algorithm (CSA) for solving non-convex economic dispatch (ED) considering generator and system characteristics including valve-point effects, multiple fuels, prohibited zones, spinning reserve and power loss. CSA is a new meta-heuristic optimisation method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species. When the host birds discover an alien egg in their nest, they can either throw it away or simply abandon their nest and build a new one elsewhere. The CSA idealised such breeding behaviour in combination with Levy flights behaviour of some birds and fruit flies for applying to various constrained optimisation problems. The effectiveness of the proposed method has been tested on different non-convex ED problems. Test results have indicated that the proposed method can obtain less expensive solutions than many other methods reported in the literature. Accordingly, the proposed CSA is a promising method for solving the practical nonconvex ED problems.

关键词： concave programming constraint handling heuristic programming power generation dispatch power generation economics search problems cuckoo search algorithm nonconvex economic dispatch CSA ED generator dispatch valve-point effect multiple fuel prohibited zone spinning reserve power loss metaheuristic optimisation method obligate brood parasitism cuckoo species host bird alien egg Lévy flight breeding behaviour constrained optimisation problem

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concave regularisation-based non-rigid feature point matching algorithm

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ELECTRONICS LETTERS 2015年第8期51卷 622-623页

作者： Lian, Wei Changzhi Univ Dept Comp Sci Changzhi 046011 Shanxi Peoples R China

A new non-rigid feature point matching algorithm is proposed, where the non-rigid global deformation is preserved by dividing the object into several overlapping local regions and only regularising the deformations of the local regions. A key property of the proposed algorithm is that the objective function is concave. By combining with the total unimodularity of the constraints, the proposed algorithms can be proved to directly yield integer valued solutions. Experimental results demonstrate the better robustness of the method over several state-of-the-art methods.

关键词： concave programming deformation feature extraction image matching concave regularisation-based non-rigid feature point matching algorithm constraint unimodularity integer valued solution non-rigid global deformation regularisation

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