首页> 外文会议>International Conference on Ubiquitous and Future Networks >Pricing-based shared energy storage optimization for residential users with photovoltaic generation system and demand-side load management
【24h】

Pricing-based shared energy storage optimization for residential users with photovoltaic generation system and demand-side load management

机译:光伏发电系统和需求侧负荷管理的基于定价的住宅用户共享储能优化

获取原文

摘要

In this paper, we investigate a problem of optimal capacities of energy storage system for the residential users and an optimal unit price energy storage system for an aggregator. We suppose that the residential users have own photovoltaic generation system and a smart meter which can schedule activation of home appliances and controls. The aggregator participates in energy market to maximize his profit by selling the storage to the residential users. Each user determines his energy consumption schedule and a required amount of storage to minimize his energy cost depending on the unit price of energy storage, price profile of electricity from the main grid and his renewable power generation capacity. We consider electricity bill from main grid and storage bill from the aggregator as users' energy cost. We formulate a problem for the aggregator to decide an optimal unit price of energy storage and a problem for each user to decide energy consumption schedule and a required amount of storage capacity. With numerical investigation, it is shown that the energy storage can reduce the energy load to main grid and shave peak power. As a result, by purchasing energy storage, users can save their energy cost by 43% in average compared to the case without energy storage.
机译:在本文中,我们研究了针对住宅用户的最佳储能系统容量和针对聚集器的最佳单价储能系统的问题。我们假设居民用户拥有自己的光伏发电系统和智能电表,可以安排家用电器和控件的激活。聚合器通过将存储出售给居民用户来参与能源市场,以最大程度地提高其利润。每个用户根据能量存储的单价,主电网的电价和可再生能源发电量来确定自己的能源消耗时间表和所需的存储量,以最大程度地降低其能源成本。我们将主电网的电费和聚合商的存储电费视为用户的能源成本。我们提出了一个问题,让集合商确定一个最佳的储能单价,并为每个用户确定一个能源消耗计划和所需的存储容量。通过数值研究表明,储能可以减少主电网的能量负荷并减少峰值功率。结果,与没有储能的情况相比,通过购买储能,用户平均可节省43%的能源成本。

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