论文标题
使用存储的多型随机峰剃须
Multiperiod Stochastic Peak Shaving Using Storage
论文作者
论文摘要
我们提供了一个在线随机模型的预测控制框架，用于带网格连接的消费者的需求收费管理框架，并带有附着的电源存储。我们认为的消费者必须满足不灵活但随机的电力需求，并且还会收到随机电力流入。优化问题提出了解决随机成本最小化问题，给定的天气预测情景转化为预测需求和流入。我们介绍了一种新型的加权方案，以说明优化范围跨越多个需求充电周期的情况。优化方案在具有建筑物需求和光伏阵列流入数据的设置中进行了测试。仿真研究使我们能够比较各种设计和建模替代方案，最终提出了基于因果偏爱决策规则的政策。
We present an online stochastic model predictive control framework for demand charge management for a grid-connected consumer with attached electrical energy storage. The consumer we consider must satisfy an inflexible but stochastic electricity demand, and also receives a stochastic electricity inflow. The optimization problem formulated solves a stochastic cost minimization problem, with given weather forecast scenarios converted into forecast demand and inflow. We introduce a novel weighting scheme to account for cases where the optimization horizon spans multiple demand charge periods. The optimization scheme is tested in a setting with building demand and photovoltaic array inflow data from a real office building. The simulation study allows us to compare various design and modeling alternatives, ultimately proposing a policy based on causal affine decision rules.
