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[电气工程与系统科学] 恒温控制聚集的随机电池模型 负荷 [推广有奖]

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能者818 在职认证  发表于 2022-3-3 17:10:30 来自手机 |AI写论文

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摘要翻译:
需求侧作为频率储备的潜力为处理间歇性可再生能源造成的不平衡提供了有趣的机会。本文提出了一种新的方法来计算一个代表恒温控制负荷(TCLs)集合的随机电池模型的参数。采用基于滞后的无干扰控制,利用优先级堆栈算法跟踪参考调节信号。利用TCLs提供的状态(开/关)、可用度和到开关边界的相对温度距离等信息,动态计算允许斜坡率参数和电池的充电极限。该方法建立和改进了现有的研究工作,提供了一种直接计算等效电池模型随机参数的机制。通过一个大量住宅TCL跟踪一个缩小的实际调频信号的测试案例,证明了该方法的有效性。
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英文标题:
《Stochastic Battery Model for Aggregation of Thermostatically Controlled
  Loads》
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作者:
Sohail Khan, Mohsin Shahzad, Usman Habib, Wolfgang Gawlik, Peter
  Palensky
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最新提交年份:
2016
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分类信息:

一级分类:Computer Science        计算机科学
二级分类:Systems and Control        系统与控制
分类描述:cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
cs.sy是eess.sy的别名。本部分包括理论和实验研究,涵盖了自动控制系统的各个方面。本节主要介绍利用建模、仿真和优化工具进行控制系统分析和设计的方法。具体研究领域包括非线性、分布式、自适应、随机和鲁棒控制,以及混合和离散事件系统。应用领域包括汽车和航空航天控制系统、网络控制、生物系统、多智能体和协作控制、机器人学、强化学习、传感器网络、信息物理和能源相关系统的控制以及计算系统的控制。
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一级分类:Electrical Engineering and Systems Science        电气工程与系统科学
二级分类:Systems and Control        系统与控制
分类描述:This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
本部分包括理论和实验研究,涵盖了自动控制系统的各个方面。本节主要介绍利用建模、仿真和优化工具进行控制系统分析和设计的方法。具体研究领域包括非线性、分布式、自适应、随机和鲁棒控制,以及混合和离散事件系统。应用领域包括汽车和航空航天控制系统、网络控制、生物系统、多智能体和协作控制、机器人学、强化学习、传感器网络、信息物理和能源相关系统的控制以及计算系统的控制。
--

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英文摘要:
  The potential of demand side as a frequency reserve proposes interesting opportunity in handling imbalances due to intermittent renewable energy sources. This paper proposes a novel approach for computing the parameters of a stochastic battery model representing the aggregation of Thermostatically Controlled Loads (TCLs). A hysteresis based non-disruptive control is used using priority stack algorithm to track the reference regulation signal. The parameters of admissible ramp-rate and the charge limits of the battery are dynamically calculated using the information from TCLs that is the status (on/off), availability and relative temperature distance till the switching boundary. The approach builds on and improves on the existing research work by providing a straight-forward mechanism for calculation of stochastic parameters of equivalent battery model. The effectiveness of proposed approach is demonstrated by a test case having a large number of residential TCLs tracking a scaled down real frequency regulation signal.
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PDF链接:
https://arxiv.org/pdf/1601.07783
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关键词:Optimization Experimental Availability Cooperative distributed 模型 方法 作为 信号 battery

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