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Energy Efficiency of Distributed Antenna Systems With Wireless Power Transfer

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2019年第1期37卷 89-99页

作者： Huang, Yuwen Liu, Yuan Li, Geoffrey Ye South China Univ Technol Sch Elect & Informat Engn Guangzhou 510641 Guangdong Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

In this paper, we study energy-efficient resource allocation in distributed antenna system with wireless power transfer, where time-division multiple access is adopted for downlink multiuser information transmission. In particular, when a user is scheduled to receive information, other users harvest energy at the same time using the same radio-frequency signal. We consider two types of energy efficiency (EE) metrics: user-centric EE (UC-EE) and network-centric EE (NC-EE). Our goal is to maximize the UC-EE and NC-EE, respectively, by optimizing the transmission time and power subject to the energy harvesting requirements of the users. For both UC-EE and NC-EE maximization problems, we transform the nonconvex problems into equivalently tractable problems by using suitable mathematical tools and then develop iterative algorithms to find the globally optimal solutions. Simulation results demonstrate the superiority of the proposed methods compared with the benchmark schemes.

关键词： Distributed antenna systems (DAS) energy efficiency (EE) wireless power transfer nonlinear programming

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Multi-objective optimisation of a permanent magnet flux-switching motor by combined parameter sensitivities analysis with non-linear varying-network magnetic circuit method

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IET ELECTRIC POWER APPLICATIONS 2019年第1期13卷 24-30页

作者： Zhu, Xiaoyong Jian, Yanhong Xiang, Zixuan Fan, Deyang Yang, Minjian Jiangsu Univ Sch Elect & Informat Engn Zhenjiang Peoples R China Jiangsu Univ Jiangsu Key Lab Drive & Intelligent Control Elect Zhenjiang Peoples R China

In this study, a new sensitivity analysis based on non-linear varying-network magnetic circuit (VNMC) method is proposed for an outer-rotor I-shaped permanent magnet flux-switching motor. By integrating concept of sensitivity analysis into the non-linear VNMC method, the whole design efficiency can be improved effectively by using the comprehensive sensitivity method and sequential non-linear programming algorithm. In the optimisation process, two design objectives are selected, including machine output torque and torque ripple. Based on the sensitivity analysis, the parameters possessing the significant influence on the design objectives can be selected purposely, thus the overall amount of calculation is obviously reduced. After the determination of the sensitive parameters, the rest of optimisation can be realised efficiently by the non-linear VNMC method. Finally, a prototype motor is manufactured and tested. Both theoretical analysis and experimental results confirm the effectiveness of the proposed method.

关键词： magnetic circuits magnetic flux nonlinear programming permanent magnet motors rotors sensitivity analysis torque

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Direct Solution of Multi-Objective Optimal Control Problems Applied to Spaceplane Mission Design

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2019年第1期42卷 30-46页

作者： Ricciardi, Lorenzo A. Maddock, Christie Alisa Vasile, Massimiliano Univ Strathclyde Aerosp Ctr Excellence Mech & Aerosp Engn 75 Montrose St Glasgow G1 1XJ Lanark Scotland

This paper presents a novel approach to the solution of multiphase multi-objective optimal control problems. The proposed solution strategy is based on the transcription of the optimal control problem with Finite Elements in Time and the solution of the resulting multi-objective nonlinear programming (MONLP) problem with a memetic strategy that extends the Multi Agent Collaborative Search algorithm. The MONLP problem is reformulated as two nonlinear programming problems: a bilevel and a single-level problem. The bilevel formulation is used to globally explore the search space and generate a well spread set of nondominated decision vectors, whereas the single-level formulation is used to locally converge to Pareto efficient solutions. Within the bilevel formulation, the outer level selects trial decision vectors that satisfy an improvement condition based on Chebyshev weighted norm, whereas the inner level restores the feasibility of the trial vectors generated by the outer level. The single-level refinement implements a Pascoletti-Serafini scalarization of the MONLP problem to optimize the objectives while satisfying the constraints. The approach is applied to the solution of three test cases of increasing complexity: an atmospheric reentry problem, an ascent and abort trajectory scenario, and a three-objective system and trajectory optimization problem for spaceplanes.

关键词： Trajectory Optimization Spaceplane nonlinear programming Ascent Abort Search Algorithm Propellant Flight Path Angle Aerodynamic Efficiency Aerodynamic Coefficients Wing Loading

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Data gathering maximisation for wireless sensor networks with a mobile sink

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2019年第4期32卷 224-235页

作者： Han, Zongyuan Shi, Tianyun Lv, Xiaojun Jia, Xinchun Wang, Zhongying Zhou, Dong China Acad Railway Sci Inst Comp Technol Beijing 100081 Peoples R China Shanxi Univ Sch Math Sci Taiyuan 030006 Peoples R China

Recent studies have demonstrated that the significant benefit can be achieved by using mobile sinks for data gathering in wireless sensor networks (WSNs). However, most of them employed a typical scheme that the mobile collector pauses at the anchor points on its moving tour for a period time to collect the data from nearby sensors. In this paper, the data gathering process is divided into two stages named parking communication (PC) and moving communication (MC). We focus on maximising the total amount of data gathering by the mobile sink, and formulate the problem as two different optimisation models under several constraints for these two different communication stages. Accordingly, dual decomposition and simplex methods are dexterously exploited to derive the optimal communication time and flow rates allocation schemes. Computational results demonstrate the efficiency of the proposed algorithms.

关键词： wireless sensor network WSN mobile data gathering dual decomposition nonlinear programming

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Application of improved invasive weed optimization technique for optimally setting directional overcurrent relays in power systems

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APPLIED SOFT COMPUTING 2019年 79卷 1-13页

作者： Srinivas, S. T. P. Swarup, Shanti K. Indian Inst Technol Madras Dept Elect Engn Chennai 600036 Tamil Nadu India

This paper aims to study the application of a heuristic optimization technique namely, Invasive Weed Optimization (IWO) technique for optimal protection coordination in power systems. The optimal relay coordination problem is formulated as a nonlinear constrained optimization, which is solved using Improved IWO (IIWO). The proposed IIWO algorithm modifies the standard deviation expression of the weed population. The simulation results show that IIWO has faster and better convergence compared with standard IWO. To further improve the computational efficiency, a hybrid IIWO method is also proposed which is obtained by defining sequential quadratic programming (SQP) as a subroutine in IIWO for searching local solutions, thus eliminate weaker weeds in the colonization process. The proposed techniques are tested on both the 9-bus test system and IEEE- 30 bus systems and the performance is compared. Relay coordination algorithm is developed in MATLAB, and the results are found to be effective and reliable. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Directional overcurrent relays Heuristic programming Invasive weed optimization nonlinear programming Optimal relay coordination

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Using a spectral scaling structured BFGS method for constrained nonlinear least squares

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OPTIMIZATION METHODS & SOFTWARE 2019年第4期34卷 693-706页

作者： Bidabadi, N. Yazd Univ Fac Math Sci Yazd Iran

In this paper, we use a spectral scaled structured BFGS formula for approximating projected Hessian matrices in an exact penalty approach for solving constrained nonlinear least-squares problems. We show this spectral scaling formula has a good self-correcting property. The reported numerical results show that the use of the spectral scaling structured BFGS method outperforms the standard structured BFGS method.

关键词： nonlinear programming constrained nonlinear least squares exact penalty methods spectral scaling structured BFGS method

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Partition-based optimization model for generative anatomy modeling language (POM-GAML)

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BMC BIOINFORMATICS 2019年第2期20卷 99-114页

作者： Demirel, Doga Cetinsaya, Berk Halic, Tansel Kockara, Sinan Ahmadi, Shahryar Univ Arkansas Dept Comp Sci Little Rock AR 72204 USA Univ Cent Arkansas Dept Comp Sci Conway AR 72035 USA Univ Arkansas Med Sci Dept Orthoped Surg Little Rock AR 72205 USA

BackgroundThis paper presents a novel approach for Generative Anatomy Modeling Language (GAML). This approach automatically detects the geometric partitions in 3D anatomy that in turn speeds up integrated non-linear optimization model in GAML for 3D anatomy modeling with constraints (e.g. joints). This integrated non-linear optimization model requires the exponential execution time. However, our approach effectively computes the solution for non-linear optimization model and reduces computation time from exponential to linear time. This is achieved by grouping the 3D geometric constraints into *** community detection algorithms (k-means clustering, Clauset Newman Moore, and Density-Based Spatial Clustering of Applications with Noise) were used to find communities and partition the non-linear optimization problem into sub-problems. GAML was used to create a case study for 3D shoulder model to benchmark our approach with up to 5000 *** results show that the computation time was reduced from exponential time to linear time and the error rate between the partitioned and non-partitioned approach decreases with the increasing number of constraints. For the largest constraint set (5000 constraints), speed up was over 2689-fold whereas error was computed as low as 2.2%.ConclusionThis study presents a novel approach to group anatomical constraints in 3D human shoulder model using community detection algorithms. A case study for 3D modeling for shoulder models developed for arthroscopic rotator cuff simulation was presented. Our results significantly reduced the computation time in conjunction with a decrease in error using constrained optimization by linear approximation, non-linear optimization solver.

关键词： Modeling language for human anatomy Arthroscopic rotator cuff Virtual human anatomy nonlinear programming Partition-based optimization

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Optimal allocation of distributed generation for planning master-slave controlled microgrids

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第16期13卷 3704-3712页

作者： Pasha, Aisha M. Zeineldin, Hatem H. El-Saadany, Ehab F. Alkaabi, Sultan S. Khalifa Univ Dept Elect & Comp Engn Abu Dhabi U Arab Emirates Cairo Univ Fac Engn Dept Elect Power & Machines Giza 12316 Egypt Univ Waterloo ECE Dept Waterloo ON Canada Al Ain Distribut Co Abu Dhabi Water & Elect Author Al Ain U Arab Emirates

This study proposes a novel problem formulation for a planning distributed generation (DG) allocation for microgrids, using the master-slave approach. In the previous planning studies, all DGs have the same operating mode (e.g. operate at unity power factor). For master-slave controlled microgrid, DGs have two possible operating modes: master (non-unity power factor operation) and slave (unity power factor operation). For planning a master-slave controlled microgrid, in addition to DG siting, the optimal DG operating mode is determined by including a new set of constraints in the planning problem. Thus, the proposed formulation is capable of determining the optimal location of the master and slave DGs with the main objective of minimizing the microgrid's energy losses. The proposed model is formulated as a mixed-integer non-linear programming problem;incorporated into an optimal power flow framework and tested on the IEEE 38-bus systems considering a variable load profile. In addition to this, sensitivity analysis is carried for case studies with different load types and reactive power injection by the slave DGs in the system (e.g. operate at fixed non-unity power factor). The proposed approach can serve as an efficient tool for utility operators for planning microgrids.

关键词： power generation control power factor power generation reliability nonlinear programming integer programming power distribution control optimisation power distribution reliability distributed power generation sensitivity analysis linear programming load flow planning problem slave DGs mixed-integer nonlinear programming problem optimal power flow framework fixed nonunity power factor utility operators planning microgrids optimal allocation planning master-slave controlled microgrids novel problem formulation planning distributed generation master-slave approach optimisation problem previous planning studies master-slave controlled microgrid possible operating modes nonunity power factor operation unity power factor operation optimal DG operating mode

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Insights into conditioning of landfill sludge by FeCl3 and lime

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WATER RESEARCH 2019年 160卷 167-177页

作者： Wu, Wei Zhou, Zhen Yang, Jiazhe Chen, Guang Yao, Jie Tu, Chengqin Zhao, Xiaodan Qiu, Zhan Wu, Zhichao Shanghai Univ Elect Power Coll Environm & Chem Engn Shanghai 200090 Peoples R China Shanghai Chengtou Wastewater Treatment Co Ltd Shanghai 201203 Peoples R China Shanghai Inst Pollut Control & Ecol Secur Shanghai 200092 Peoples R China Tongji Univ Coll Environm Sci & Engn State Key Lab Pollut Control & Resource Reuse Shanghai 200092 Peoples R China

In this study, landfill sludge (LS) was excavated from a 10 year old full-scale sludge landfill and used to investigate effects of dosage on sludge dewaterability, rheological properties and extracellular polymeric substances (EPS) variations by FeCl3-lime conditioning. LS had lower content of organic matters (0.28) and smaller particle size than excess sludge (ES), and greatly lower viscosity and high flowability. The suitable concentration of LS for conditioning (107.2-118.6 g/L) was much higher than that of ES (34 g/L) by rheological analysis. Both FeCl3 and lime improved dewaterability of LS and caused decline of slime and loosely bound EPS (LB-EPS). FeCl3 destroyed proteins in slime and LB-EPS owing to coagulation and acidification effects, weakened internal structure strength, and thus improved dewaterability. Lime addition caused alkaline hydrolysis of polysaccharides in slime and LB-EPS, reduced viscosity and flowability, and improved flowability and dewaterability for LS. The optimal dosage for dewatering using 57.6 mg lime/g dried solids (DS) and 53.6 mg FeCl3/g DS was obtained by using an integrative response surface methodology (RSM) coupled nonlinear programming approach under water content constraint of 55%. The integrative optimization achieved 26.0% cost saving in comparison to RSM optimized condition. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Landfill Sludge conditioning Rheology Response surface methodology nonlinear programming Lime FeCl3

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A predicting model for properties of steel using the industrial big data based on machine learning

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COMPUTATIONAL MATERIALS SCIENCE 2019年 160卷 95-104页

作者： Guo, Shun Yu, Jinxin Liu, Xingjun Wang, Cuiping Jiang, Qingshan Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518000 Guangdong Peoples R China Xiamen Univ Coll Mat Xiamen 361000 Fujian Peoples R China Xiamen Univ Fujian Prov Key Lab Mat Genome Xiamen 361000 Fujian Peoples R China Harbin Inst Technol State Key Lab Adv Welding & Joining Harbin 150001 Heilongjiang Peoples R China Harbin Inst Technol Shenzhen Inst Mat Genome & Big Data Shenzhen 518000 Guangdong Peoples R China

Extracting the valuable information about the connections between the overall properties and the related factors from the industrial big data of materials is of significant interest to the materials engineering. At present, most data-driven approaches focus on building a relation model for a single property of the materials, where it may ignore the restrictive boundaries of other properties. In this paper, we propose a machine-learning-based method using nonlinear programming for multiple properties of the materials, and solve the problem by using the Interior Point Algorithm. The key idea is to take the mapping functions corresponding to the properties of the materials as the constraints of the nonlinear programming problem, thus it is capable of processing the restrictions of these properties. Moreover, with our method, the possible boundaries of these properties under certain conditions can be calculated. Experiments results on steel production data demonstrate the rationality and reliability of the proposed method.

关键词： Big data Machine learning Regression Steel properties nonlinear programming

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