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A real-time decision support system for voltage collapse avoidance in power supply networks

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2008年第6期E91D卷 1740-1747页

作者： Chang, Chen-Sung Nan Kai Inst Technol Dept Informat Management Tsao Tun 542 Nan Tou Country Taiwan

This paper presents a real-time decision support system (RDSS) based on artificial intelligence (AI) for voltage collapse avoidance (VCA) in power supply networks. The RDSS scheme employs a fuzzy hyperrectangular composite neural network (FHRCNN) to carry out voltage risk identification (VRI). In the event that a threat to the security of the power supply network is detected, an evolutionary programming (EP)-based algorithm is triggered to determine the operational settings required to restore the power supply network to a secure condition. The effectiveness of the RDSS methodology is demonstrated through its application to the American Electric Power Provider System (AEP, 30-bus system) under various heavy load conditions and contingency scenarios. In general, the numerical results confirm the ability of the RDSS scheme to minimize the risk of voltage collapse in power supply networks. In other words, RDSS provides Power Provider Enterprises (PPEs) with a viable tool for performing on-line voltage risk assessment and power system security enhancement functions.

关键词： real-time decision support system voltage collapse avoidance fuzzy neural network evolutionary programming control decision

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A novel crazy swarm optimized economic load dispatch for various types of cost functions

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2008年第4期30卷 242-253页

作者： Roy, Ranjit Ghoshal, S. P. SV Natl Inst Technol Dept Elect Engn Surat 395007 India Natl Inst Technol Dept Elect Engn Durgapur 713209 W Bengal India

Economic load dispatch (ELD) is the scheduling of generators to minimize the total operating cost depending on equality and inequality constraints. The transmission line loss also is to be kept as minimum as possible. So, the problem is of multi-objective optimization. The authors have studied the comparative effectiveness of GA, Improved fast EP (IFEP) and various particle swarm optimizations (PSO) reported in the literature and a novel particle swarm algorithm namely CRAZYPSO for such multi-objective optimization in two test cases. The first test case deals with some well-known Benchmark functions and then the second case deals with a general power system having 40 thermal generating units with non-monotonically increasing cost functions with valve point loadings and other constraints. The generators are interconnected through lossy transmission lines. The proposed method out performs and provides true global optimal solutions as compared to other existing techniques for economic load dispatch. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： crazypso economic load dispatch evolutionary programming GA HPSO vurmfipso

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Unmanned aerial vehicles cooperative tracking of moving ground target in urban environments

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2008年第5期31卷 1360-1371页

作者： Shaferman, Vitaly Shima, Tal Technion Israel Inst Technol Dept Aerosp Engn IL-32000 Haifa Israel

The problem of autonomous tracking of aground moving target in an urban terrain is studied. In the investigated scenario, the target is tracked from multiple unmanned aerial vehicles using gimballed or body-fixed sensors under the constraints of terrain occlusions and airspace limitations. Information regarding the occlusions may be available a priori from a database or may be provided to the system by the operator based on his understanding of the environment. To ensure flyable trajectories, the unmanned aerial vehicles' dynamic constrains must be taken into account. A methodology is proposed for solving in real time a general class of such problems by casting the tracking task as a cooperative motion planning problem. Because of the computational complexity of the problem, a stochastic search method (genetic algorithm) is proposed for finding in real time monotonically improving solutions. An important attribute of the proposed solution approach is its scalability and, consequently, applicability to large-sized problems. For testing the algorithm, it was implemented in a high-fidelity simulation test bed using a visual database of an actual city., The viability of using the algorithm is shown using a Monte Carlo study. It is envisioned that automating this part of a ground moving target tracking problem will considerably reduce operators' workload and dramatically improve mission performance in such real-life problems.

关键词： UAV Sensors Airspace Motion Planning Genetic Algorithm Search Algorithm evolutionary programming Autopilot Optimal Control Mobile Robots

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Optimization of energy systems based on evolutionary and Social metaphors

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ENERGY 2008年第2期33卷 171-179页

作者： Dimopoulos, George G. Frangopoulos, Christos A. Natl Tech Univ Athens Sch Naval Architecture & Marine Engn Zografos 15773 Greece

Optimization problems that arise in energy systems design often have several features that hinder the use of many optimization techniques. These optimization problems have non-continuous mixed variable definition domains, are heavily constrained, are multimodal (i.e. have many local optima) and, foremost, the functions used to define the engineering optimization problem are often computationally intensive. Three methods are tested here: (a) a Struggle Genetic Algorithm (StrGA), (b) a Particle Swarm Optimization Algorithm (PSOA), and (c) a PSOA with Struggle Selection (PSOStr). The last is a hybrid of the evolutionary StrGA and the socially inspired PSOA. They are tested in four purely mathematical and three energy systems thermoeconomic optimization problems. All of the methods solved successfully all the problems. The PSOStr, however, outperformed the other methods in terms of both solution accuracy and computational Cost (i.e. function evaluations). (C) 2007 Elsevier Ltd. All rights reserved.

关键词： energy systems particle swarm optimization evolutionary programming

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A comparison of memetic algorithms for the spread spectrum radar polyphase codes design problem

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2008年第8期21卷 1233-1238页

作者： Perez-Bellido, Angel M. Salcedo-Sanz, Sancho Ortiz-Garcia, Emilio G. Portilla-Figueras, Jose A. Lopez-Ferreras, Francisco Univ Alcala Dept Signal Theory & Commun Madrid Spain

This paper presents three memetic algorithms to solve the spread spectrum radar polyphase code design problem, based on evolutionary programming, Particle Swarm Optimization and Differential Evolution, respectively. These global search heuristics are hybridized with a gradient-based local search procedure which includes a dynamic step adaptation procedure to perform accurate and efficient local search for better solutions. We have compared the different memetic algorithms proposed in several numerical examples, and we have also demonstrated the performance of our approaches against existing approaches for this problem. (C) 2008 Elsevier Ltd. All rights reserved,

关键词： Polyphase codes Code design evolutionary programming Memetic algorithms

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Decentralized observer-based tracker for analog systems with saturating actuator and state constraints

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2008年第1期55卷 1-22页

作者： Tsai, J. S. H. Lin, J. H. Shieh, L. S. Liu, C. R. Guo, S. M. Natl Cheng Kung Univ Dept Elect Engn Control Syst Lab Tainan 701 Taiwan Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan

A weighted switching strategy and an inner-loop compensator are presented in this paper to design an observer-based tracker for a decentralized closed-loop cascaded system with a saturating actuator and state constraints. The LQR design methodology for the observer-based tracker is proposed to simplify the complexity of the decentralized control. The realizable sample-data controller with a low-gain property and a high design performance is realized through the digital redesign method. For obtaining a better design performance, evolutionary programming is then presented to tune the parameters of the tracker. Some examples are also presented to demonstrate the effectiveness of the proposed methodology. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： digital redesign decentralized control evolutionary programming observer-based tracker input and state saturations

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Security constrained economic load dispatch using improved particle swarm optimization suitable for utility system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2008年第10期30卷 609-613页

作者： Baskar, G. Mohan, M. R. Anna Univ Dept Elect & Elect Engn Madras 6000025 Tamil Nadu India

The objective of this paper is to evolve simple and effective methods for the economic load dispatch (ELD) problem with security constraints in thermal units, which are capable of obtaining economic scheduling for utility system. In the proposed improved particle swarm optimization (IPSO) method, a new velocity strategy equation is formulated suitable for a large scale system and the features of constriction factor approach (CFA) are also incorporated into the proposed approach. The CFA generates higher quality solutions than the conventional PSO approach. The proposed approach takes security constraints such as line flow constraints and bus voltage limits into account. In this paper, two different systems IEEE-14 bus and 66-bus Indian utility system have been considered for investigations and the results clearly show that the proposed IPSO method is very competent in solving ELD problem in comparison with other existing methods. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Security constraints Economic load dispatch evolutionary programming Improved particle swarm optimization

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Optimization of energy systems based on evolutionary and Social metaphors 19

Optimization of energy systems based on Evolutionary and Soc...

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19th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2006)

作者： Dimopoulos, George G. Frangopoulos, Christos A. Natl Tech Univ Athens Sch Naval Architecture & Marine Engn Zografos 15773 Greece

ISBN: (纸本)9608758424

关键词： energy systems particle swarm optimization evolutionary programming

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Unit Commitment under Wind Power and Demand Uncertainties

Unit Commitment under Wind Power and Demand Uncertainties

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Joint International Conference on Power Systems Technology (POWERCON)/IEEE Power India Conference

作者： Pappala, V. S. Erlich, I. Singh, S. N. Univ Duisburg Essen Inst Elect Power Syst D-47057 Duisburg Germany Indian Inst Technol Kanpur 208016 Uttar Pradesh India

ISBN: (纸本)9781424417636

This paper addresses a multistage stochastic model for the optimal operation of wind farm, pumped storage and thermal power plants. The output of the wind farm and the electrical demand are considered as two independent stochastic processes. The evolution of these processes over time is modeled as a scenario tree. Considering all possible realizations of stochastic process, leads to a huge set of scenarios. These scenarios are reduced by a particle swarm optimization based scenario reduction algorithm. The scenario tree modeling transforms the cost model to a stochastic model. The stochastic model can be used to estimate the operation costs of the hybrid system under the influence of the uncertainties. The stochastic model is solved using adaptive particle swarm optimization.

关键词： Economic Model evolutionary programming Multi-stage Scenario tree Particle Swarm Optimization Random Process Stochastic programming

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Synthesis, design and operation optimization of a marine energy system 19

Synthesis, design and operation optimization of a marine ene...

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19th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2006)

作者： Dimopoulos, George G. Kougloufas, Aristotelis V. Frangopoulos, Christos A. Natl Tech Univ Athens Sch Naval Architecture & Marine Engn Zografos 15773 Greece

ISBN: (纸本)9608758424

Recent developments in the global fuel markets imposed the need of increased fuel economy and cost effectiveness of sea-going vessels. Optimization of the ship's total energy system, as a whole, is now a demand of the marine industry sector in order to address the significant increase of installation and operational costs. This study is focused on the synthesis, design and operation optimization of a marine energy system. A realistic example of a cruise liner energy system has been selected. Basic technology options have been identified and a generic energy system model has been constructed. Various configuration options.. types of technologies and existence of components have been incorporated in the generic system. In addition, time varying operational requirements for this cruise liner ship have been considered, resulting in a time dependent operation optimization problem. The complete optimization problem has been solved using a novel algorithm, inspired by evolutionary and social behavior metaphors. A parametric analysis with respect to the fuel price demonstrated changes in the optimum synthesis of the system. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： synthesis optimization marine energy systems evolutionary programming

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