A Mean Field control approach for demand side management of large populations of Thermostatically Controlled Loads
A Mean Field control approach for demand side management of large populations of Thermostatically Controlled Loads
复制标题
用于大量恒温控制负载需求侧管理的平均场控制方法
DOI：
10.1109/ecc.2015.7331083
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
J. Lygeros
中科院分区：
文献类型：
--
作者：
Sergio Grammatico;Basilio Gentile;F. Parise;J. Lygeros
本文提出了一种平均场（MF）控制方法的需求侧管理的大人口的灵活的电力负荷，如电冷却/加热设备，称为恒温控制负荷（TCLs）。我们模拟的开关动态的每个单独的TCL作为一个局部优化问题的解决方案，其特征在于由个人的成本函数，舒适性约束，冷却/加热速率和外部温度。我们认为，一个中央公用事业公司广播宏观激励措施，引导整体TCL人口走向一个方便的平衡，以避免电力需求高峰，由于可能同步的TCL占空比。为了找到这样的定价方案，我们提出了一个迭代算法，在每一步，一个简单的无模型的反馈法是用来更新的激励措施，鉴于目前的总需求的TCL人口。这种算法的收敛性是确保任何人口规模，即使在存在异构凸约束。我们通过数值分析说明我们的MF控制方法。
This paper presents a Mean Field (MF) control approach for demand side management of large populations of flexible electric loads, such as electrical cooling/heating appliances, called Thermostatically Controlled Loads (TCLs). We model the switching dynamics of each individual TCL as the solution of a local optimization problem, characterized by individual cost function, comfort constraints, cooling/heating rates and external temperature. We consider that a central utility company broadcasts macroscopic incentives to steer the overall TCL population towards a convenient equilibrium, to avoid power demand peaks due to possible synchronization of the TCL duty cycles. To find such pricing schemes we propose an iterative algorithm where, at every step, a simple model-free feedback law is used to update the incentives, given the current aggregate demand of the TCL population only. The convergence of such algorithm is ensured for any population size, even in the presence of heterogeneous convex constraints. We illustrate our MF control approach via numerical analysis.