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Battery Operating Regimes: Effect of Temporal Resolution on Peak Shaving by Battery Energy Storage System

机译:电池运行状态:时间分辨率对电池储能系统调峰的影响

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摘要

Battery Energy Storage Systems (BESS) are often used for demand charge reduction through monthly peak shaving. The effect of two temporal resolutions, 15-min and 1-hour, on peak shaving is compared across a battery ratings space defined by power capacity and energy capacity of the battery. Based on the 15-min load of a particular day, a critical power and critical energy can be defined, yielding a critical point in the power- energy space. A linear program of the system optimizes the peak of the net load and the associated demand charge assuming perfect forecasts. Based on the difference of demand charge (DODC) across the two load profiles at high and low temporal resolution for a real building, the battery rating space is divided into three different regions: optimal region, power-constrained region, and energy-constrained region, which can be identified by the critical power (CP) and critical energy (CE) derived from the load profile. As the conclusion shows, the DODC in the power-constrained and energy-constrained regions is explained by the averaging operation and the load sequence at high resolution. In the power-constrained region of the battery rating space, the difference between the original 15 min peak and the 1 hour average peak persists in the optimized net load until the battery power capacity is sufficiently large. In the energy-constrained region, averaging may change the peak period duration, which depends on the sub-hourly sequence of the original load data. Through artificial load data and reordering of real load data, we demonstrate that the sequence effect causes energy-constrained batteries to underestimate peak shaving and demand charge reduction.
机译:电池储能系统 (BESS) 通常用于通过每月调峰来减少需求费用。在由电池的功率容量和能量容量定义的电池额定空间内比较两种时间分辨率(15 分钟和 1 小时)对调峰的影响。根据特定一天的 15 分钟负载,可以定义临界功率和临界能量,从而在电力能量空间中产生临界点。系统的线性程序优化了净负荷的峰值和相关的需求费用,假设预测完美。根据真实建筑物在高时间和低时间分辨率下两种负载曲线的需求电荷 (DODC) 差异,电池额定空间分为三个不同的区域:最佳区域、功率受限区域和能源受限区域,这可以通过从负载曲线得出的关键功率 (CP) 和关键能量 (CE) 来识别。正如结论所示,功率受限和能量受限区域中的 DODC 由高分辨率的平均运算和载荷序列来解释。在电池额定空间的功率受限区域中,原始 15 分钟峰值和 1 小时平均峰值之间的差异在优化的净负载中持续存在,直到电池功率容量足够大。在能量受限的区域中,平均可能会更改高峰期持续时间,这取决于原始负载数据的次小时顺序。通过人工负载数据和对实际负载数据的重新排序,我们证明了序列效应会导致能量受限的电池低估调峰和需求电荷减少。

著录项

  • 作者

    Liu, Shiyi.;

  • 作者单位

    University of California, San Diego.;

    University of California, San Diego.;

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;University of California, San Diego.;University of California, San Diego.;
  • 学科 Mechanical engineering.;Batteries.;Energy consumption.;Electrical engineering.;Scheduling.
  • 学位
  • 年度 2021
  • 页码 45
  • 总页数 45
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mechanical engineering.; Batteries.; Energy consumption.; Electrical engineering.; Scheduling.;

    机译:机械工程。;电池。;能源消耗。;电气工程。;调度。;

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