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The maximum power demand forecasting with fuzzy theory

机译:用模糊理论预测最大电力需求

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摘要

The study aims at seeking the interrelationship and origin of the basic electricity, mobile electricity, power adjustment charges, additional super-charges, and line subsidy payments of the high-pressure two-stage electricity users (Far East University), according to the average of monthly temperature and tariff structure calendar year. Using fuzzy theory to analyze and simulate the peak electricity quantity of kilowatt of entire year, then using genetic algorithm to this system for making the best learning. Assist users to find the optimal contracted capacity with this way to achieve the goal of saving electricity cost.
机译:该研究旨在根据平均水平来寻找高压两级用电用户(远东大学)的基本用电,移动用电,电力调整费,附加附加费和线路补贴的相互关系和来源。每月的温度和关税结构的详细信息。利用模糊理论对全年的峰值用电量进行分析和仿真,然后采用遗传算法对该系统进行最佳学习。通过这种方式协助用户找到最佳的合同容量,以达到节省电费的目的。

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