...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Energy >Cost optimal sizing of smart buildings' energy system components considering changing end-consumer electricity markets
【24h】

Cost optimal sizing of smart buildings' energy system components considering changing end-consumer electricity markets

机译：考虑到最终消费者电力市场的变化，智能建筑能源系统组件的成本优化选型

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Managing the electricity system becomes increasingly challenging, calling for modifications of the current electricity market. High fluctuations in power generation could make the introduction of dynamic end-consumer electricity pricing reasonable. Furthermore, the prediction of end-consumers' power consumption would get easier when charging the maximum power capacity, instead of the consumed energy. Thus, this paper discusses the capability of smart buildings to cope with such market models and evaluates how the design of the electrical and thermal energy system of a modern German building is affected. Therefore, cost optimal sizing of the main supply system components is carried out based on a hybrid MILP and a heuristic optimization algorithm. The results indicate that local photovoltaic generation is beneficial in almost all market conditions, while except for the capacity market, batteries are only economical if prices decrease by more than 60%. The identified electricity price dynamics are too low to incentivize investments into load shifting capable supply or storage systems. Nevertheless, if an installed heat pump and the associated thermal storage have smart home capabilities, they support the maximization of PV self-consumption and reduce electricity cost. (C) 2017 Elsevier Ltd. All rights reserved.
机译：电力系统的管理变得越来越具有挑战性，要求改变当前的电力市场。发电量的高波动可能使引入动态最终消费者电价合理。此外，当充电最大功率而不是消耗能量时，对最终用户功耗的预测将变得更加容易。因此，本文讨论了智能建筑应对此类市场模型的能力，并评估了如何影响现代德国建筑的电气和热能系统的设计。因此，基于混合式MILP和启发式优化算法，可以对主要供应系统组件进行成本优化选型。结果表明，在几乎所有市场条件下，本地光伏发电都是有益的，而除了容量市场外，只有价格下降60％以上，电池才是经济的。所确定的电价动态过低，无法激励投资于具有负载转移能力的供应或存储系统。但是，如果已安装的热泵和相关的蓄热装置具有智能家居功能，则它们将支持最大的PV自耗并降低电力成本。 （C）2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Energy》 |2017年第15期|715-728|共14页
  • 作者

    Wolisz Henryk; Schuetz Thomas; Blanke Tobias; Hagenkamp Markus; Kohrn Markus; Wesseling Mark; Mueller Dirk;

  • 作者单位

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

    Rhein Westfal TH Aachen, EON Energy Res Ctr, Inst Energy Efficient Bldg & Indoor Climate, D-52074 Aachen, Germany;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Electricity market; Cost optimization; Dynamic electricity pricing; Capacity market; Smart grid; Demand side management;

    机译：电力市场;成本优化;动态电价;容量市场;智能电网;需求侧管理;

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