首页> 外文会议>International Conference on Energy Smart Systems >About Using Electricity Pricing for Smart Grid Dynamic Management with Renewable Sources
【24h】

About Using Electricity Pricing for Smart Grid Dynamic Management with Renewable Sources

机译:关于使用可再生来源进行智能电网动态管理的电力定价

获取原文

摘要

A new approach to the design subsets (clusters) of “objects” for optimal pricing in local systems of Smart Grid (SG) of the combined type has been proposed. In our case, under term “objects” we understand the day-time (more precisely, twenty-four hours) periods, in which the necessary measurements of informative, from the standpoint of the task, values (the energy generated by the components of the system, its current cost for each type of generator, etc.) were performed. We assume that systems Smart Grid are based on renewable generation sources such as solar radiation and wind energy in combination with such system components as high-power storage batteries and power generators based on autonomous power station. The obtained statistical information formed the basis of constructing models that describe certain optimal in terms of developed criteria of a subset of “objects” using bi-clustering algorithms. The authors of this innovative approach have in mind the further application of the model output (optimal clustering) for the dynamic estimation of the total cost of energy generated by its own components, taking into account the cost of the network involved in the subsequent periods of the day. In research the half-hourly sampling time within one day was used. Simulation on the basis of collected statistical data, the results of which can be applied in processes (algorithms) of electricity pricing for smart grid dynamic management with renewable sources has been performed.
机译:提出了一种新的“物体”的设计子集(集群),用于在组合类型的智能电网(SG)的本地系统中的最佳定价。在我们的情况下,在“对象”术语下,我们了解日期(更准确地说,二十四小时)的时间,其中从任务的角度来看,信息性的必要测量值(由组件所产生的能量)系统,其目前的每种发生器的成本等。我们假设系统智能电网基于可再生的生成来源,例如太阳辐射和风能,与这种系统组件相结合,作为基于自动发电站的大高蓄电池和发电机。所获得的统计信息构成构建模型的基础,这些模型在使用双聚类算法的“物体”子集的开发标准方面的构建模型。这项创新方法的作者能够介绍模型输出(最佳聚类)的进一步应用于其自身组件产生的能源总成本的动态估计,同时考虑到随后的网络的成本那天。在研究中,使用了一天内的半小时采样时间。在收集的统计数据的基础上进行仿真,已经进行了通过可再生来源的智能电网动态管理的电力价格的工艺(算法)中可以应用的结果。

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