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检索条件"主题词=Optimization Algorithms"

共 4019 条记录，以下是4001-4010 订阅

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A NOVEL HYBRID ALGORITHM FOR RECONFIGURATION PROBLEM OF THE DISTRIBUTION NETWORKS

A NOVEL HYBRID ALGORITHM FOR RECONFIGURATION PROBLEM OF THE ...

引用

International Conference and Exhibition on Electricity Distribution

作者： Salman NASROLLAHI Amir SARDARABADI Younes KHOSHIAN Alireza GHARIB Mashhad Electric Energy Distribution Co.

ISBN: (纸本)9781629931333

One method of storing electrical energy in distribution networks is network reconfiguration. Reconfiguration in power systems can change the network topology and power flow with use of switches that can be closed and open. The main objective of the reconfiguration of distribution networks is reducing power losses and avoid network from overload. Reconfiguration is numerical optimization. Changes between open and close mode of switches should be done in such a way that the radial configuration remains radial. This study proposes a new optimization algorithm to solve the reconfiguration problem based on hybrid of particle swarm and Nelder-Mid (NM) optimization algorithms which is called PSO-NM. Simulation results on real network indicate that this new hybrid algorithm is more efficient and faster in comparsion with genetic algorithm.

关键词： Power grids Reconfiguration Particle swarm optimization optimization algorithms HYBRID Switches Network topology electrical energy Power flow Network power systems

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Exploiting Day-Ahead Electricity Price for Maximized Profit of Photovoltaic Systems

Exploiting Day-Ahead Electricity Price for Maximized Profit ...

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International Conference on Smart Grid Technology, Economics and Policies

作者： Abdalkarim Awad Peter Bazan Reinhard German Computer Networks and Communication Systems University of Erlangen

ISBN: (纸本)9781467359313

This paper proposes a methodology for optimal power management in a house with photovoltaic cells and battery storage. The proposed method exploits the day-ahead electricity market to enhance the profit of a household. An hourly-discretized optimization algorithm is proposed to identify the optimum daily operational strategy to be followed by the photovoltaic system, provided that a forecast for solar-power and load is available. This model is suitable to be applied in the real time operation of a typical house. The proposed strategy maximizes the individual revenue without shifting power demand. We explored the proposed algorithm with and without feed-in tariff. The results show that a typical house can save about 300 /year when app lying optimized power management.

关键词： Photovoltaic systems REAL TIME OPERATION Secondary batteries Solar collectors Domestic architecture Photovoltaic cells optimization algorithms Electricity LOAD Prices Power demand

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UWB VIVALDI ANTENNA BASED ON A SPLINE GEOMETRY WITH FREQUENCY BAND-NOTCH

UWB VIVALDI ANTENNA BASED ON A SPLINE GEOMETRY WITH FREQUENC...

引用

2008 IEEE Antennas and Propagation Society International Symposium (APSURSI 2008), vol.6

作者： Matthias John Max J. Ammann Patrick McEvoy Centre for Telecommunications Value-Chain Research School of Electronic & Communications Engineering Dublin Institute of Technology Dublin Ireland

A printed UWB Vivaldi antenna is presented in this paper. Its geometry is based on a novel spline shape and optimised by an efficient global optimisation algorithm. A U-shaped slot is introduced into the geometry to n... 详细信息

ISBN: (纸本)9781424420414

关键词： geometry Frequency bands splines (mathematics) Ultra wideband technologies wireless local area network (WLAN) optimization algorithms ANTENNA Vivaldi antennas

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Application of Imperialist Competitive Algorithm to Design an Optimal Controller for LFC Problem

Application of Imperialist Competitive Algorithm to Design a...

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Annual Conference on IEEE Industrial Electronics Society

作者： Elyas Rakhshani Alvaro Luna Kumars Rouzbehi Pedro Rodriguez Technical University of Catalonia Department of Electrical Engineering Research Center on Renewable Electrical Energy Systems (SEER Center)

ISBN: (纸本)9781467324199

A novel optimization algorithm is presented to improve the design of optimal controllers for load frequency control problem. This algorithm is applied for two area LFC system with using an output feedback controller. In the practical power system, access to some of the state variables in LFC system is limited and measuring is also impossible. So an optimal output feedback controller with a practical viewpoint is proposed. The optimal control law is determined by minimizing a performance index under the output feedback conditions leading to a coupled matrix equation. In order to solve these equations traditional methods may be used. But for more accuracy and better design for this controller, ICA algorithm is applied to find the global optimal gain matrix of the controller. Simulation results of ICA are compared with the conventional design. Comparison shows the success of ICA for design of optimal controller.

关键词： optimal controllers competitive algorithms Full mold process Independent component analysis islet cell antibody performance indicators load frequency control control law feedback controller Output feedback State variable information matrix Controllers optimization algorithms

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Optimizing Data Access Latencies in Cloud Systems by Intelligent Virtual Machine Placement

Optimizing Data Access Latencies in Cloud Systems by Intelli...

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IEEE INFOCOM Conference

作者： Mansoor Alicherry T. V. Lakshman Bell Labs India Alcatel-Lucent Bangalore India Bell Labs Alcatel-Lucent New Jersey USA

ISBN: (纸本)9781467359443

Many cloud applications are data intensive requiring the processing of large data sets and the MapReduce/Hadoop architecture has become the de facto processing framework for these applications. Large data sets are stored in data nodes in the cloud which are typically SAN or NAS devices. Cloud applications process these data sets using a large number of application virtual machines (VMs), with the total completion time being an important performance metric. There are many factors that affect the total completion time of the processing task such as the load on the individual servers, the task scheduling mechanism, communication and data access bottlenecks, etc. One dominating factor that affects completion times for data intensive applications is the access latencies from processing nodes to data nodes. Ideally, one would like to keep all data access local to minimize access latency but this is often not possible due to the size of the data sets, capacity constraints in processing nodes which constrain VMs from being placed in their ideal location and so on. When it is not possible to keep all data access local, one would like to optimize the placement of VMs so that the impact of data access latencies on completion times is minimized. We address this problem of optimized VM placement - given the location of the data sets, we need to determine the locations for placing the VMs so as to minimize data access latencies while satisfying system constraints. We present optimal algorithms for determining the VM locations satisfying various constraints and with objectives that capture natural tradeoffs between minimizing latencies and incurring bandwidth costs. We also consider the problem of incorporating inter-VM latency constraints. In this case, the associated location problem is NP-hard with no effective approximation within a factor of 2 - ∈ for any ∈ > 0. We discuss an effective heuristic for this case and evaluate by simulation the impact of the various tradeoffs in t

关键词： Completion time Access to Information information retrieval Latency Dataset virtual machines Representation of data placement tradeoffs optimization algorithms

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Green Scheduling to minimize Base station Transmit power and UE circuit power consumption

Green Scheduling to minimize Base station Transmit power and...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Rohit Gupta Emilio Calvanese Strinati CEA LETI MINATEC

ISBN: (纸本)9781457713460

Packet scheduling algorithms are viewed as one of the key mechanisms for increasing the diversity order, robustness and effectiveness of a wireless multi-user communication systems. Traditional packet scheduling algorithms are designed to save energy at the Base-station (BS) in downlink by exploiting tradeoffs between spectral efficiency, delay and energy while at the same time meeting the QoS requirements of the system. However, these algorithms ignore the User-Equipment (UE) circuit power consumption to receive and process downlink traffic. In this paper, we show that the optimization of only BS transmit power consumption in downlink can lead to significant drain of UE battery power. Hence, we propose sub-optimal algorithms that exploit Discontinuous Transmission (DTX) at the base-station to tradeoff delay with energy consumption to improve Energy Efficiency (EE) of the UE circuit power and BS transmit power, while at the same time meeting the application QoS requirements in terms of throughput and service delay. The proposed algorithm is also shown to achieve good performance in saving transmit power at the base-station and also the UE circuit power consumption over traditional scheduling algorithms.

关键词： BASE STATION UNITED ELECTRIC Scheduling algorithms Transmitter power Power consumption Energy sources optimization algorithms Downlink Bahamas

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Cognitive Decision Making Process Supervising the Radio Dynamic Reconfiguration

Cognitive Decision Making Process Supervising the Radio Dyna...

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3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008)

作者： Nicolas Colson Apostolos Kountouris Armelle Wautier Lionel Husson Orange Laboratories France Telecom Research and Development Center Meylan France Department of Telecommunications SUPELEC Gif-sur-Yvette France

ISBN: (纸本)9781424423019

Cognitive radio is a technological concept pushing for the introduction of intelligent radio operation going beyond system adaptation and reconfiguration on the basis of simple criteria and rules. Insofar, a rather limited amount of work has been published on the cognitive mechanisms that should be embedded into the communicating equipments to achieve such an intelligent behavior. Towards filling this gap, this paper presents an innovative optimization algorithm driving the decision making process supervising the cognitive radio reconfiguration. This cognitive algorithm, called RALFE for "Reason And Learn From Experience", presents interesting features since it allows to perform autonomous decision making with regard to multiple, possibly conflicting, operational objectives in the face of an uncertain environment. The proposed approach is illustrated for a case of cognitive waveform design.

关键词： decision making process Reconfiguration Cognitive radio dynamic reconfiguration Radio RADIO OPERATION optimization algorithms

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A Review Paper on the Elimination of Harmonics in Multilevel Inverters using Bioinspired algorithms

A Review Paper on the Elimination of Harmonics in Multilevel...

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International Conference on Circuits, Power and Computing Technologies

作者： Teena Jacob L. Padma Suresh Dept. of EEE Noorul Islam University Kanyakumari District Tamil Nadu

ISBN: (纸本)9781509012787

Multilevel inverters are highly capable of achieving higher quality output voltage waveforms and higher power ratings with the help of their multilevel structure. They have been of great interest in the field of power industry and are best suited for reactive power compensation. Multilevel voltage source inverters are capable of operating at high voltagewith less electromagnetic interference and results in higher efficiency. The harmonic elimination in a multilevel voltage source inverter is of atmost importance and different types of modulation strategies can be applied to the inverters to eliminate these harmonics. Among these modulation techniques, Selective harmonic elimination PWM is asignificant switching strategy that can be applied to the output voltage waveform of multilevel inverters for lower order harmonic elimination. This paper gives a review on the various optimization algorithms that is been used for the SHEPWM technique. Performance comparisons of these optimization algorithms in SHEPWM are discussed.

关键词： Multilevel voltage source inverter Selective Harmonic Elimination Pulse Width Modulation (SHEPWM) optimization algorithms

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EFFICIENT FORECAST SYSTEM FOR DISTRIBUTED GENERATORS WITH UNCERTAINTIES IN THE PRIMARY ENERGY SOURCE 22nd

EFFICIENT FORECAST SYSTEM FOR DISTRIBUTED GENERATORS WITH UN...

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International Conference and Exhibition on Electricity Distribution

作者： Augusto C. RUEDA-MEDINA Antonio PADILHA-FELTRIN J. R. S. MANTOVANI UNESP Ilha Solteira

ISBN: (纸本)9781629931333

A high degree of variability reduces the available capability of Distributed Generators (DGs) based on renewable energy sources because their power output is uncertain. To determine the true available capability of this kind of DG, this uncertainty must be reduced so that these DGs can be regarded as a reliable alternative. In this work, an efficient forecast system for DGs with uncertainties in the primary energy source is proposed. The power generation uncertainty of these DGs is reduced by running a multi-objective optimization algorithm in multiple probabilistic scenarios combining the Monte Carlo method and the Markov models.

关键词： Uncertainty Renewable energy optimization algorithms Energy sources Monte Carlo technique Power output dynamos renewable energy sources

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AN IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZER FOR AIR TRAFFIC FLOW NETWORK REROUTING PROBLEM

AN IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZER FOR AIR...

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IEEE/AIAA Digital Avionics Systems Conference

作者： Miao Zhang Kai-quan Cai Yan-bo Zhu School of Electronic and Information Engineering Beihang University Aviation Data Communication Corporation

ISBN: (纸本)9781467316996

With the increasing incidence of malfunctions of air transportation system due to severe weather, the Air Traffic Flow Network Rerouting (ATFNR) is playing an important role in improving the global efficiency of air traffic. This paper adopts a multi-objective optimization model to solve the ATFNR problem to make a tradeoff between the total delay costs and the airlines fairness. Meanwhile, a specially-designed algorithm based on multi-objective comprehensive learning particle swarm optimizer (MOCLPSO) under the cooperative co-evolution framework is presented to handle this large scale, multi-objective real-world optimization problem. The empirical studies show that the presented methodology is effective and outperforms an existing approach to ATFNR problem as well as two well-known Multi-Objective optimization algorithms.

关键词： air traffic optimization algorithms malfunctions Airlines tradeoffs Network

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