文件名称:electricity_market

  • 所属分类:
  • 能源行业(电力石油煤炭)
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 13.29mb
  • 下载次数:
  • 2次
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  • N**
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该文件是优秀论文并带有相应的源码。在Matlab软件平台上,对所提出的基于遗传算法的电力系统电力市场分段竞价交易算法进行了阶梯型报价曲线、线性报价曲线这两种常用报价曲线情况下的算例验证,计算结果显示算法的寻优效果因报价曲线性质的不同而略有区别,但两种情况均可得到优化的购电费用。实验结果证明了该算法应用于分段竞价模型的有效性和可行性,且不受报价曲线形式的限制。-The document is an excellent paper with a corresponding source code. In the Matlab software platform for the proposed genetic algorithm-based power systems market segment auction algorithms offer ladder-type curve, the two commonly used linear bidding curve bidding curve example in case of validation, the results show algorithm optimization results for the different nature of bidding curve slightly different, but both cases can be optimized for power purchase costs. Experimental results show that the algorithm is applied to sub-effectiveness and feasibility of bidding model, and is not limited form of bidding curve.
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下载文件列表

基于遗传算法的电力市场分段竞价交易决策研究.doc

uniformXover.m

Untitled.m

data\all_lab.mat

....\bestself.mat

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....\bestself_Tr.mat

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....\self1.mat

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....\SELF_Tr938.mat

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....\SGA-Tr.mat

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....\Tr-bestshortgen-nich-self.mat

....\Y_Nich_Tr.mat

....line\Nichlab.mat

........\NiSelab.mat

........\NNichlab.mat

........\NNSGAlab.mat

........\NSGAlab.mat

........\Selflab.mat

........\SGAlab.mat

accountE.m

accountEsec.m

adjswapMutation.m

arithbalXover.m

arithbalXover.asv

arithXover.m

b2f.m

bal.m

balance.m

balmodify.m

binaryExample.m

binaryMutation.m

boundaryMutation.m

boundmodify.m

boundmodify.asv

bpop对应的order.txt

C.txt

calcbits.m

Contents.m

coranaEval.m

coranaFeval.m

coranaMin.m

CP.txt

creatpop.m

crowding.m

cyclicXover.m

delta.m

Distance.m

dists.m

EER.m

enhancederXover.m

erXover.m

f2b.m

fitness.m

fitnessE.m

fitnessline.m

fitnessPen.m

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