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改进粒子群算法及其在电力系统经济负荷分配中的应用改进粒子群算法及其在电力系统经济负荷分配中的应用-Improved Particle Swarm Optimization and its power system economic load dispatch of improved particle swarm optimization and economic dispatch in power system application
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利用粒子位置和速度的改变更新，在熟悉多目标粒子群算法的基础上利用测试函数对该算法进行仿真，并对仿真结果进行优化。-The particle position and velocity changes update in the familiar multi-objective particle swarm optimization based on the use of test functions to simulate the algorithm, and the optimization
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the source code for particle swarm optimization algorithm is given in this file. the source code is for economic dispatch problem which is a power system problem.
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基于改进粒子群算法的多目标最优潮流计算
基于改进粒子群算法的多目标最优潮流计算-Particle Swarm Optimization Based on Improved Multi-objective Optimal Power Flow
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matlabb标准粒子群优化算法。
电力系统的分析和计算中，需要不同网络结构和参数。在应
用这些参数之前，收集和整理工作会花费大量的时间和精力。-matlabb standard particle swarm optimization. Power system analysis and calculation, require different network structures and parameters. Before applying these parameters,
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用粒子群算法进行无功优化，比较实用，希望对大家有帮助，14节点的，-Particle swarm algorithm with reactive power optimization, more practical, we want to help, 14 nodes,
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The economic load dispatch plays an important role in the operation of power system,
and several models by using different techniques have been used to solve these problems.
Several traditional approaches, like lambda-iteration and gradient metho
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采用基于量子粒子群算法来计算电力系统无功优化-Based on the quantum particle swarm algorithm to compute reactive power optimization
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蚁群算法应该到货物搬送问题中，同时也可应用于电力系统调度优化中-Ant colony algorithm to the cargo bay should be problems, can also be applied in power system scheduling optimization
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使用粒子群优化算法对电力系统最有潮流进行优化，比较不错的程序-Using particle swarm optimization algorithm for power system to optimize the power flow, relatively good program
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基于双适应度的粒子群算法，采用matlab编程，收敛效果好，可用于求解最优潮流等电力系统优化问题！-Based on the fitness of the two-particle swarm optimization using matlab programming, convergence effect, and can be used to solve power system optimization such as optimal power flow problem!
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采用粒子群算法PSO优化BP神经网络，进行风电功率预测，含实际数据和案例-Particle swarm optimization PSO BP neural network for wind power prediction, including the actual data and case
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标准14节点的无功优化，粒子群算法和多智能体粒子群算法的实现，需要放到matpowe里。-ieee14 nodes system reactive optimized to achieve PSO and Multi-Agent particle swarm algorithm, need to put matpower environment.
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这是一篇关于利用改进的粒子群优化算法来构造多层人工神经网络的文章，可用于预测风力和天气。-This is an article on the use of improved particle swarm optimization algorithm to construct a multilayer artificial neural network of the article, can be used to predict the wind and weather.
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Improved Particle Swarm Optimization Based
Load Frequency Control In
A Single Area Power System
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reactive power problem
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A combination of genetic algorithm and particle swarm optimization for optimal
DG location and sizing in distribution systems
Distributed generation (DG) sources are becoming more prominent in distribution systems due to the
incremental dema
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升压电路（boost）、最大功率跟踪（MPPT），粒子群算法（pso）(Booster circuit (boost), maximum power tracking (MPPT), particle swarm optimization (pso))
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Maximum Power Point Tracking for PV System
under Partial Shading Condition via Particle
Swarm Optimization
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optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm
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