英文标题：
《Dynamic Energy Management》
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作者：
Nicholas Moehle and Enzo Busseti and Stephen Boyd and Matt Wytock
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最新提交年份：
2019
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英文摘要：
  We present a unified method, based on convex optimization, for managing the power produced and consumed by a network of devices over time. We start with the simple setting of optimizing power flows in a static network, and then proceed to the case of optimizing dynamic power flows, i.e., power flows that change with time over a horizon. We leverage this to develop a real-time control strategy, model predictive control, which at each time step solves a dynamic power flow optimization problem, using forecasts of future quantities such as demands, capacities, or prices, to choose the current power flow values. Finally, we consider a useful extension of model predictive control that explicitly accounts for uncertainty in the forecasts. We mirror our framework with an object-oriented software implementation, an open-source Python library for planning and controlling power flows at any scale. We demonstrate our method with various examples. Appendices give more detail about the package, and describe some basic but very effective methods for constructing forecasts from historical data.
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中文摘要：
我们提出了一种基于凸优化的统一方法，用于管理设备网络随时间产生和消耗的功率。我们从静态网络中优化功率流的简单设置开始，然后继续优化动态功率流，即在一段时间内随时间变化的功率流。我们利用这一点来开发实时控制策略，即模型预测控制，该策略在每个时间步解决动态潮流优化问题，使用对未来数量（如需求、容量或价格）的预测来选择当前的潮流值。最后，我们考虑了模型预测控制的一个有用扩展，该扩展明确说明了预测中的不确定性。我们使用面向对象的软件实现来反映我们的框架，这是一个开源Python库，用于规划和控制任何规模的功率流。我们用各种例子来演示我们的方法。附录提供了有关该软件包的更多详细信息，并描述了从历史数据构建预测的一些基本但非常有效的方法。
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分类信息：

一级分类：Mathematics        数学
二级分类：Optimization and Control        优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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一级分类：Quantitative Finance        数量金融学
二级分类：Portfolio Management        项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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