首页> 外文会议>International Conference on Genetic and Evolutionary Computing >The Annual Power Demand Prediction Approach by Fuzzy-Genetic Algorithm
【24h】

The Annual Power Demand Prediction Approach by Fuzzy-Genetic Algorithm

机译:模糊遗传算法的年功率需求预测方法

获取原文

摘要

This paper focus on two types of the industry class high-voltage consumer, to investigate various kind of electricity fees which includes demand charge, energy charge, power factor charge and penalty charge, and correlation among them according to the monthly electricity fee calculation structure in the past. Using the simulation of Fuzzy theory analysis and the Optimal Learning of Genetic Algorithm method, the optimal contract capacity can be derived by selecting annual peak load as a key parameter. The Industrial Class Consumer can predict the plant operation power consumption to fulfill energy conservation goal.
机译:本文侧重于两种类型的工业级高压消费者,调查各种电力费用,包括需求费用,能源费,功率因数费用和罚金充电,以及根据每月电费计算结构之间的相关性过去。利用模糊理论分析的仿真和遗传算法方法的最佳学习,通过选择年峰值负载作为关键参数,可以得到最佳合同能力。工业类消费者可以预测植物运行功耗以实现节能目标。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号