A Virtual Battery Model for Packetized Energy Management ∗

A Virtual Battery Model for Packetized Energy Management ∗
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用于分组能源管理的虚拟电池模型*

DOI:
10.1109/cdc42340.2020.9304065
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发表时间:
2020
期刊:
2020 59th IEEE Conference on Decision and Control (CDC)
影响因子:
--
通讯作者:
M. Almassalkhi
M. Almassalkhi
中科院分区:
--
文献类型:
--
作者:
L. A. D. Espinosa;Adil Khurram;M. Almassalkhi

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相似文献

本文的目标是开发一个低阶模型来表示分布式能源资源的协调,基于使互联网工作的概念,被称为分组能源管理(PEM)。低阶模型包括作为状态变量的能量以及动态选择退出约束和内部分组请求反馈,其原则上将模型转变为PEM虚拟电池(PEM-VB)模型。本文重点研究了PEM下电热水器的均匀聚集。结果表明,自底向上的逻辑PEM-VB使系统可观察的主要是由于方便的反馈的数据包请求的数量通过PEM协调器和设备之间建立的通信信道注册该计划。如果没有这些额外的信息,系统就失去了观察系统存储能量状态的能力。计算PEM-VB的最大和最小能量界限的程序开发。此外,PEM-VB被明确地用作扩展卡尔曼滤波观测器制定的基础模型,其目的是估计存储在PEM下基于代理的EWHs的模拟合奏中的能量。PEM-VB的使用表明在预先定位的灵活的资源取决于负荷预测。最后,结论和未来的发展方向。
The goal of this paper is to develop a low-order model to represent the coordination of distributed energy resources based on concepts that make the internet work and is known as packetized energy management (PEM). The low-order model includes energy as a state variable together with dynamic opt-out constraints and internal packet request feedback, which in principle turns the model into a PEM virtual battery (PEM-VB) model. The paper focuses on a homogeneous aggregation of electric water heaters (EWHs) under PEM. It is shown that the bottom-up logic of the PEM-VB makes the system observable mainly due to the convenient feeding back of the number of packet requests through the communication channel established between the PEM coordinator and devices enrolled in the scheme. Without such extra information, the system loses the ability to observe the system’s stored energy state. A procedure for computing the maximum and minimum energy bounds for the PEM-VB is developed. Moreover, the PEM-VB is explicitly used as the underlying model for an extended Kalman filter observer formulation with the purpose of estimating the energy stored in a simulated ensemble of agent-based EWHs under PEM. The use of PEM-VB is demonstrated in pre-positioning of flexible resources depending upon load forecasts. Finally, conclusions and future directions are provided.
DOI: 10.1109/tpwrs.2020.2981436
发表时间: 2020-09-01
影响因子: 6.6
作者:
Espinosa, Luis A. Duffaut;Almassalkhi, Mads
通讯作者: Almassalkhi, Mads