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Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators

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ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH 2017年第2期20卷 411-426页

作者： Teeparthi, Kiran Kumar, D. M. Vinod NIT Warangal Dept Elect Engn Warangal Andhra Pradesh India

In this paper, a new low level with teamwork heterogeneous hybrid particle swarm optimization and artificial physics optimization (HPSO-APO) algorithm is proposed to solve the multi-objective security constrained optimal power flow (MO-SCOPF) problem. Being engaged with the environmental and total production cost concerns, wind energy is highly penetrating to the main grid. The total production cost, active power losses and security index are considered as the objective functions. These are simultaneously optimized using the proposed algorithm for base case and contingency cases. Though PSO algorithm exhibits good convergence characteristic, fails to give near optimal solution. On the other hand, the APO algorithm shows the capability of improving diversity in search space and also to reach a near global optimum point, whereas, APO is prone to premature convergence. The proposed hybrid HPSO-APO algorithm combines both individual algorithm strengths, to get balance between global and local search capability. The APO algorithm is improving diversity in the search space of the PSO algorithm. The hybrid optimization algorithm is employed to alleviate the line overloads by generator rescheduling during contingencies. The standard IEEE 30-bus and Indian 75-bus practical test systems are considered to evaluate the robustness of the proposed method. The simulation results reveal that the proposed HPSO-APO method is more efficient and robust than the standard PSO and APO methods in terms of getting diverse Pareto optimal solutions. Hence, the proposed hybrid method can be used for the large interconnected power system to solve MO-SCOPF problem with integration of wind and thermal generators. (C) 2017 Karabuk University. Publishing services by Elsevier B.V.

关键词： Multi-objective hybrid optimization algorithm Security constrained optimal power flow Pareto optimal solution

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Study of Valuation Function and Search Strategy in Random Game

Study of Valuation Function and Search Strategy in Random Ga...

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第30届中国控制与决策会议

作者： Zhang Xiao-chuan Li Qin Wang Wan-wan Huang Long-chao Sun Yong-jie Peng Li-rong Li Yi School of Computer Science and Engineering Chongqing University of Technology Chongqing Industry Polytechnic College

The balance between attack and defense is one of the key problems of computer game *** EinStein Würfelt Nicht! game injects randomness of the game process with the aid of the dice for choosing,increasing the game fun,but also making valuations *** this reason,this paper selects two valuation factors of distance and probability,and designs the valuation function specially for this *** multi-thread technology,a hybrid optimization algorithm based on Monte Carlo algorithm and Expected Search algorithm is *** the perspective of system balance,the game system of EinStein Wiirfelt Nicht! is reconstructed based on the two aspects of attack and *** experimental results show that the improved game system continued to maintain a strong chess force and won the national championship.

关键词： valuation function hybrid optimization algorithm EinStein Wiirfelt Nicht! game

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Operational research in multi space debris removal using space maneuver vehicle

Operational research in multi space debris removal using spa...

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Chinese Automation Congress

作者： Weilin Wang Xumin Song Meng Shao Space Engineering University Beijing China

This paper investigates the operational research in active debris removal and focuses on the orbit control in multi debris removal. Far-range trajectory is the crucial phase which guides chaser to proximity of target debris in sequence and provides precondition for further rendezvous control. Far-range trajectory can be divided into two modes depending on velocity requirement at the engagement instant. A novel mode, fly-by trajectory, is firstly proposed for far-range trajectory control corresponding to debris capture by compact with whipple material. Compared with general rendezvous and capture mode, there is no requirement on relative velocity in fly-by mode. At last, hybrid optimization algorithm is applied to far-range trajectory optimization based on multi-revolution Lambert algorithm. Simulations are conducted with three scenarios to illustrate effectiveness of proposed concept. This paper summarizes relevant work in this field and presents our new research in far-range orbit control.

关键词： Operational research Orbit control Far-range Fly-by hybrid optimization algorithm

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Jinliang A Novel Method for Mechanical Constitutive Parameters Estimation of Human Left Ventricle

Jinliang A Novel Method for Mechanical Constitutive Paramete...

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5th International Conference on Mechanical, Automotive and Materials Engineering (CMAME)

作者： Li, Yiqiang Cai, Li Huang, Zhiqiang Northwestern Polytech Univ Dept Appl Math Xian Shaanxi Peoples R China

ISBN: (纸本)9781538604328

In this paper, a new framework for estimation of myocardium constitutive parameters is established. A more realistic, cardiac magnetic resonance image based realistic human left ventricular finite element analysis model is introduced for analyzing the deformation of left ventricle during diastole firstly, the material behavior is described by the anisotropic nonlinear Holzapfel-Ogden constitutive model;then a novel hybrid simplex and quantum behavioral particle swarm optimization algorithm which is proposed to estimate the constitutive model parameters of myocardium as the inverse problem of left ventricle deformation. Numerical examples show that finite element analysis results and the estimated parameters are in good agreement with the experimental data reported in literature, which demonstrate that parameter estimation framework is valid. Comparing with current optimization algorithm, the presented hybrid optimal algorithm can estimate the mechanical parameters more efficiently.

关键词： hybrid optimization algorithm Nonlinear constitutive model Material parameter estimation

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Modeling and optimization of a Cooling Tower-Assisted Heat Pump System

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ENERGIES 2017年第5期10卷 733-733页

作者： Wei, Xiaoqing Li, Nianping Peng, Jinqing Cheng, Jianlin Hu, Jinhua Wang, Meng Hunan Univ Coll Civil Engn Changsha 410082 Hunan Peoples R China

To minimize the total energy consumption of a cooling tower-assisted heat pump (CTAHP) system in cooling mode, a model-based control strategy with hybrid optimization algorithm for the system is presented in this paper. An existing experimental device, which mainly contains a closed wet cooling tower with counter flow construction, a condenser water loop and a water-to-water heat pump unit, is selected as the study object. Theoretical and empirical models of the related components and their interactions are developed. The four variables, viz. desired cooling load, ambient wet-bulb temperature, temperature and flow rate of chilled water at the inlet of evaporator, are set to independent variables. The system power consumption can be minimized by optimizing input powers of cooling tower fan, spray water pump, condenser water pump and compressor. The optimal input power of spray water pump is determined experimentally. Implemented on MATLAB, a hybrid optimization algorithm, which combines the Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm with the greedy diffusion search (GDS) algorithm, is incorporated to solve the minimization problem of energy consumption and predict the system's optimal set-points under quasi-steady-state conditions. The integrated simulation tool is validated against experimental data. The results obtained demonstrate the proposed operation strategy is reliable, and can save energy by 20.8% as compared to an uncontrolled system under certain testing conditions.

关键词： cooling tower-assisted heat pump theoretical and empirical models energy saving hybrid optimization algorithm

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A new hybrid algorithm for simultaneous size and semi-rigid connection type optimization of steel frames

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INTERNATIONAL JOURNAL OF STEEL STRUCTURES 2015年第1期15卷 89-102页

作者： Hadidi, Ali Rafiee, Amin Univ Tabriz Dept Civil Engn Tabriz Iran

A hybrid algorithm based on Harmony Search (HS) and Big Bang-Big Crunch (BB-BC) optimization methods is proposed for optimal design of semi-rigid steel frames. The algorithm selects suitable sections for beams and columns and assigns suitable semi-rigid connection types for beam-to-column connections, such that the total member plus connection cost of the frame, is minimized. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the design procedure. The nonlinear moment-rotation behavior of connections and P-Delta effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark steel frames are designed and the results are compared with those of standard BB-BC and of other studies. The comparisons demonstrate that proposed algorithm performs better than standard BB-BC and HS methods in all examples and that the total cost of a frame can be reduced through suitable selection of its beam-to-column connection types.

关键词： Big Bang-Big Crunch Harmony Search hybrid optimization algorithm size optimization steel frames semi-rigid connections

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A hybrid glowworm swarm optimization algorithm to solve constrained multimodal functions optimization

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optimization 2015年第4期64卷 1057-1080页

作者： Zhou, Yongquan Zhou, Guo Zhang, Junli Guangxi Univ Nationalities Coll Informat Sci & Engn Nanning Peoples R China Guangxi Key Lab Hybrid Computat & IC Design Anal Nanning Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China

In this paper, a novel hybrid glowworm swarm optimization (HGSO) algorithm is proposed. The HGSO algorithm embeds predatory behaviour of artificial fish swarm algorithm (AFSA) into glowworm swarm optimization (GSO) algorithm and combines the GSO with differential evolution on the basis of a two-population co-evolution mechanism. In addition, to overcome the premature convergence, the local search strategy based on simulated annealing is applied to make the search of GSO approach the true optimum solution gradually. Finally, several benchmark functions show that HGSO has faster convergence efficiency and higher computational precision, and is more effective for solving constrained multi-modal function optimization problems.

关键词： differential evolution artificial fish swarm glowworm swarm optimization multimodal function optimization hybrid optimization algorithm 68W20 68T20

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hybrid optimization Design of a High-Speed Permanent Magnet Machine Used for EV Traction 9

Hybrid Optimization Design of a High-Speed Permanent Magnet ...

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9th International Conference and Exposition on Electrical and Power Engineering (EPE)

作者： Fodorean, Daniel Idoumghar, Lhassane Tech Univ Cluj Napoca Cluj Napoca Romania Univ Haute Alsace Mulhouse France

ISBN: (纸本)9781509061280

The paper is dealing with the optimum design of a high-speed permanent magnet synchronous machine (HS-PMSM), to be used for the traction of an electric vehicle. A hybrid optimization algorithm, based on particle swarm and simulated annealing approaches is employed for the optimization of the studied machine. The finite element method approach is used to numerically validate the optimum design of the HSPMSM.

关键词： hybrid optimization algorithm high-speed permanent magnet machine EV application

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Coordinated Freeway Ramp Control Based on Genetic Ant Colony algorithm

Coordinated Freeway Ramp Control Based on Genetic Ant Colony...

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Chinese Automation Congress

作者： Xinrong Liang Mu Yan College of Automation South China University of Technology Guangzhou China College of Information Engineering Wuyi University Jiangmen Guangdong China

In this paper, we employ a multilayer decentralized control and an advanced PID control to solve the coordinated ramp control problem. Furthermore, we use a hybrid optimization approach to adjust the PID parameters. This hybrid approach in use is the combination of a genetic algorithm (GA) and an ant colony algorithm (ACA). First, a macroscopic and dynamic freeway traffic flow model called a finite-difference model is built. Second, the control objective of ramp metering is fully set forth. Third, a coordinated control system of multiple ramps based on a genetic ant colony algorithm is designed. This control system is divided into an adaptation layer, a coordination layer, and a direct control layer. In the direct control layer, we employ PID control to determine the ramp metering rates and use a hybrid algorithm of GA and ACA to optimize the PID parameters. Finally, simulation research and result comparison are carried out. Simulation results show that the method of multilayer decentralized control, as well as the hybrid optimization algorithm, has an excellent density tracking performance. This control technology, as well as the optimization process, finds a new way for freeway traffic control.

关键词： Freeway density control Multilayer decentralized control hybrid optimization algorithm Finite-difference model

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Jinliang A Novel Method for Mechanical Constitutive Parameters Estimation of Human Left Ventricle

Jinliang A Novel Method for Mechanical Constitutive Paramete...

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2017 5th International Conference on Mechanical, Automotive and Materials Engineering（CMAME 2017）

作者： YiQiang Li Li Cai Zhiqiang Huang Department of Applied Mathematics Northwestern Polytechnical University

In this paper,a new framework for estimation of myocardium constitutive parameters is established.A more realistic,cardiac magnetic resonance image based realistic human left ventricular finite element analysis model is introduced for analyzing the deformation of left ventricle during diastole firstly,the material behavior is described by the anisotropic nonlinear Holzapfel-Ogden constitutive model;then a novel hybrid simplex and quantum behavioral particle swarm optimization algorithm which is proposed to estimate the constitutive model parameters of myocardium as the inverse problem of left ventricle *** examples show that finite element analysis results and the estimated parameters are in good agreement with the experimental data reported in literature,which demonstrate that parameter estimation framework is *** with current optimization algorithm,the presented hybrid optimal algorithm can estimate the mechanical parameters more efficiently.

关键词： hybrid optimization algorithm Nonlinear constitutive model Material parameter estimation

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