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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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本文介绍了混合粒子群算法在环境和经济调度方面的应用，并对粒子群算法做了进一步发展，对算法学习有一定帮助。-In this paper, hybrid particle swarm algorithm in the environment and the application of economic dispatch, particle swarm optimization and further development of the learning algorithm must help.
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Two stage optimization algorithm is
proposed and investigated for fast computation of constrained power economic dispatch control problems.-Two stage optimization algorithm is
proposed and investigated for fast computation of constrained power e
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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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遗传-套粒子群算法用于解决经济调度问题。(Genetic set particle swarm optimization algorithm is used to solve the problem of economic dispatch.)
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IEEE 30 BUS SYSTEM Comparisons between stochastic and deterministic Unit
Commitment solutions are provided. The generation of Unit
Commitment solution is guaranteed by DEEPSO, which is a
hybrid DE-EA-PSO algorithm, where DE stands for Differential
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Comparisons between stochastic and deterministic Unit
Commitment solutions are provided. The generation of Unit
Commitment solution is guaranteed by DEEPSO, which is a
hybrid DE-EA-PSO algorithm, where DE stands for Differential
Evolution, EA for
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在微电网中综合考虑经济和环境两个目标，以各微源的运行上下限为约束条件，采用粒子群算法在matlab环境下进行了仿真，最后给出了微网各微源的最优机组组合方式和最佳电能交易计划。(The first establish micro multi-objective energy optimal operation model, taking into account both environmental and economic factors in the model, the operation
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本程序为粒子群算法的源代码可应用于微电网的多目标经济优化调度(This program is the source code of particle swarm optimization algorithm and can be applied to multi-objective economic optimal dispatch of microgrid)
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