论文标题
基于事件的EV充电计划在建筑物的微电网中
Event-based EV Charging Scheduling in A Microgrid of Buildings
论文作者
论文摘要
随着电动汽车(EV)的普及,电动汽车充电需求正在成为建筑物中的重要负担。考虑到电动汽车从建筑物到建筑物及其不确定的充电需求的流动性,控制建筑物微电网中的电动汽车充电过程具有极大的实际兴趣,以优化总运行成本,同时确保微电网和主要电网之间的传输安全性。我们在本文中考虑了这个重要的问题,并做出了以下贡献。首先,我们将这个问题作为马尔可夫决策过程,以捕获建筑物微电网中不确定的供应和电动电动机的需求。除了降低建筑物的总运营成本外,该模型还考虑了电力交换限制以确保传输安全性。其次,该模型在基于事件的优化框架下进行了重新制定,以减轻大型国家和行动空间的影响。通过适当定义事件和基于事件的操作,可以通过在微电网控制器中搜索基于随机参数事件的控制策略并在每个构建控制器中实现选择 - 充电规则来优化EV充电过程。第三,提出了一种基于梯度的基于梯度的策略优化方法,该方法通过迭代地找到了基于事件的最佳控制策略,用于每个建筑物中的EV充电需求。考虑了三个建筑物的微电网的数值实验,以分析基于事件的控制策略的结构和性能。
With the popularization of the electric vehicles (EVs), EV charging demand is becoming an important load in the building. Considering the mobility of EVs from building to building and their uncertain charging demand, it is of great practical interest to control the EV charging process in a microgrid of buildings to optimize the total operation cost while ensuring the transmission safety between the microgrid and the main grid. We consider this important problem in this paper and make the following contributions. First, we formulate this problem as a Markov decision process to capture the uncertain supply and EV charging demand in the microgrid of buildings. Besides reducing the total operation cost of buildings, the model also considers the power exchange limitation to ensure transmission safety. Second, this model is reformulated under event-based optimization framework to alleviate the impact of large state and action space. By appropriately defining the event and event-based action, the EV charging process can be optimized by searching a randomized parametric event-based control policy in the microgrid controller and implementing a selecting-to-charging rule in each building controller. Third, a constrained gradient-based policy optimzation method with adjusting mechanism is proposed to iteratively find the optimal event-based control policy for EV charging demand in each building. Numerical experiments considering a microgrid of three buildings are conducted to analyze the structure and the performance of the event-based control policy for EV charging.