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optimal placement of Active Members in Truss Adaptive Structures

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Chinese Journal of Mechanical Engineering 2010年第2期23卷 233-241页

作者： ZHANG Lianwen XIA Renwei HUANG Hai School of Mechanical Engineering Tianjin University of Commerce Tianjin 300134 China School of Astronautics Beijing University of Aeronautics ＆ Astronautics Beijing 100083 China

The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.

关键词： truss adaptive structure optimal placement active member multi-objective optimization mixed variables penalty function approach

optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm

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Frontiers in Energy 2021年第1期15卷 240-255页

作者： A.S.O.OGUNJUYIGBE T.R.AYODELE O.D.BAMGBOJE Power Energy Machines and Drives(PEMD)Research Group Department of Electrical and Electronic EngineeringUniversity of IbadanNigeria

Most wind turbines within wind farms are set up to face a pre-determined wind direction.However,wind directions are intermittent in nature,leading to less electricity production capacity.This paper proposes an algorithm to solve the wind farm layout optimization problem considering multi-angular(MA)wind direction with the aim of maximizing the total power generated on wind farms and minimizing the cost of installation.A twostage genetic algorithm(GA)equipped with complementary sampling and uniform crossover is used to evolve a MA layout that will yield optimal output regardless of the wind direction.In the first stage,the optimal wind turbine layouts for 8 different major wind directions were determined while the second stage allows each of the previously determined layouts to compete and inter-breed so as to evolve an optimal MA wind farm layout.The proposed MA wind farm layout is thereafter compared to other layouts whose turbines have focused site specific wind turbine orientation.The results reveal that the proposed wind farm layout improves wind power production capacity with minimum cost of installation compared to the layouts with site specific wind turbine layouts.This paper will find application at the planning stage of wind farm.

关键词： optimal placement wind turbines wind direction genetic algorithm wake effect

optimal placement and Sizing of Renewable Distributed Generation Using Hybrid Metaheuristic Algorithm

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Journal of Modern Power Systems and Clean Energy 2020年第3期8卷 499-510页

作者： Jordan Radosavljević Nebojša Arsić Milos Milovanović Aphrodite Ktena Faculty of Technical Sciences University of Priština in Kosovska MitrovicaKneza Miloša 7Kosovska MitrovicaSerbia National and Kapodistrian University of Athens AthensGreece

The problem of optimal placement and sizing(OPS) of renewable distributed generation(RDG) is followed by numerous technical, economical, geographical, and ecological constraints. In this paper, it is investigated from two viewpoints, namely the simultaneous minimization of total energy loss of a distribution network and the maximization of profit for RDG owner. The stochastic nature of RDG such as the wind turbine and photovoltaic generation is accounted using suitable probabilistic models. To solve this problem, a hybrid metaheuristic algorithm is proposed, which is a combination of the phasor particle swarm optimization and the gravitational search algorithm. The proposed algorithm is tested on an IEEE69-bus system for several cases in two scenarios. The results obtained by the hybrid algorithm shows that it provides high-quality solution for all cases considered and has better performances for solving the OPS problem compared to other metaheuristic population-based techniques.

关键词： Wind turbine photovoltaic generation optimal placement metaheuristic optimization

optimal placement and Sizing of Distributed Generations for Power Losses Minimization Using PSO-Based Deep Learning Techniques

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智能电网与可再生能源(英文) 2023年第9期14卷 169-181页

作者： Bello-Pierre Ngoussandou Nicodem Nisso Dieudonné Kaoga Kidmo Kitmo Department of Renewable Energy National Advanced School of Engineering of Maroua University of Maroua Maroua Cameroon Department of Computer Science and Telecoms National Advanced School of Engineering of Maroua University of Maroua Maroua Cameroon

The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.

关键词： Distributed Generations Deep Learning Techniques Improved Particle Swarm Optimization Power Losses Power Losses Minimization optimal placement

Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement

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Protection and Control of Modern Power Systems 2021年第1期6卷 124-135页

作者： Bhargav Appasani Amitkumar Vidyakant Jha Sunil Kumar Mishra Abu Nasar Ghazali School of Electronic Engineering KIIT UniversityBhubaneswar751024India

Real time monitoring and control of a modern power system has achieved significant development since the incorporation of the phasor measurement unit (PMU). Due to the time-synchronized capabilities, PMU has increased the situational awareness (SA) in a wide area measurement system (WAMS). Operator SA depends on the data pertaining to the real-time health of the grid. This is measured by PMUs and is accessible for data analytics at the data monitoring station referred to as the phasor data concentrator (PDC). Availability of the communication system and communication delay are two of the decisive factors governing the operator SA. This paper presents a pragmatic metric to assess the operator SA and ensure optimal locations for the placement of PMUs, PDC, and the underlying communication infrastructure to increase the efficacy of operator SA. The uses of digital elevation model (DEM) data of the surface topography to determine the optimal locations for the placement of the PMU, and the microwave technology for communicating synchrophasor data is another important contribution carried out in this paper. The practical power grid system of Bihar in India is considered as a case study, and extensive simulation results and analysis are presented for validating the proposed methodology.

关键词： Situational awareness Phasor measurement unit optimal placement Microwave communication

Repulsive firefly algorithm-based optimal switching device placement in power distribution systems

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Global Energy Interconnection 2019年第6期2卷 490-496页

作者： Yuanpeng Tan Hai Chen Wei Liu Mingze Zhang Yinong Li Xincong Li Hanyang Lin Beijing Key Laboratory of Distribution Transformer Energy-Saving Tech. China Electric Power Research InstituteBeijing 102206P.R.China Artificial Intelligence Application Department China Electric Power Research InstituteBeijing 102206P.R.China State Grid Shanghai Municipal Electric Power Company Shanghai 200333P.R.China School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230001P.R.China

To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.

关键词： Power distribution systems Switching device Repulsive firefly algorithm optimal placement Reliability

High-impedance Fault Detection Method Based on Feature Extraction and Synchronous Data Divergence Discrimination in Distribution Networks

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1235-1246页

作者： Yang Liu Yanlei Zhao Lei Wang Chen Fang Bangpeng Xie Laixi Cui School of Electrical and Electronic Technology Shandong University of TechnologyZiboChina State Grid Shanghai Electric Power Research Institute ShanghaiChina State Grid Shanghai Pudong Electric Power Supply Company ShanghaiChina

High-impedance faults(HIFs)in distribution networks may result in fires or electric shocks.However,considerable difficulties exist in HIF detection due to low-resolution measurements and the considerably weaker time-frequency characteristics.This paper presents a novel HIF detection method using synchronized current information.The method consists of two stages.In the first stage,joint key characteristics of the system are extracted with the minimal system prior knowledge to identify the global optimal micro-phase measurement unit(μPMU)placement.In the second stage,the HIF is detected through a multivariate Jensen-Shannon divergence similarity measurement using high-resolution time-synchronized data inμPMUs in a high-noise environment.l2,1 principal component analysis(PCA),i.e.,PCA based on the l2,1 norm,is applied to an extracted system state and fault features derived from different resolution data in both stages.An economic observability index and HIF criteria are employed to evaluate the performance of placement method and to identify HIFs.Simulation results show that the method can reliably detect HIFs with reasonable detection accuracy in noisy environments.

关键词： High-impedance fault micro-phase measurement unit fault detection distribution network optimal placement

A METHOD FOR THE SELECTION OF SENSOR AND ACTUATOR LOCATIONS

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Acta Mechanica Sinica 1998年第4期14卷 353-362页

作者：陈塑寰曹宗杰刘中生谢军 Department of Mechanics Jilin University of TechnologyChangchun 130025China

A new and efficient technique for determining optimal locations of sensors and actuators of intelligent structures is presented. The optimization of sensor and actuator locations is based on the Ist order singular value perturbations of observability and controllability. Using this method the optimal placements of sensors and actuators of the intelligent structurer can be selected. Two numerical examples are given to demonstrate the applications of the method. The impulse responses of structures due to different locations of actuators with the same control law are analyzed in detail.

关键词： sensor actuator optimal placement singular value perturbation

Congestion Management of Power System with Interline Power Flow Controller Using Disparity Line Utilization Factor and Multi-objective Differential Evolution

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CSEE Journal of Power and Energy Systems 2015年第3期1卷 76-85页

作者： Akanksha Mishra G.V.Nagesh Kumar Department of Electrical and Electronics Engineering GITAM Institute of TechnologyGITAM UniversityVisakhapatnamIndia Associate Professor in Department of Electrical and Electronics Engineering GITAM Institute of TechnologyGITAM UniversityVisakhapatnamIndia

The restructuring of the electric power market has led to complex power transmission congestion problems.Additionally,scheduled power flows in the transmission line,as well as spontaneous power exchanges have also risen sharply in recent years.The proper placement of IPFC can improve the transmission line congestion problem to a great extent.This paper proposes a disparity line utilization factor(DLUF)for the optimal placement of IPFC to control the congestion in transmission lines.DLUF determines the difference between the percentages of Mega Volt Ampere utilization of each line connected to the same bus.The IPFC is placed in the lines with maximum DLUF.A multiobjective function consisting of reduction of active power loss,minimization of total voltage deviations,minimization of security margin and minimization of installed IPFC capacity is considered for the optimal tuning of IPFC using differential evolution algorithm.The proposed method is implemented for IEEE-30 bus test system under different loading conditions and the results are presented and analyzed to establish the effectiveness on the reduction of congestion.

关键词： Congestion differential evolution algorithm interline power flow controller line utilization factor optimal placement optimal tuning