Renewable Energy: Forecasting and Risk Management - Paris, France, June 7-9, 2017
Renewable Energy: Forecasting and Risk Management - Paris, France, June 7-9, 2017
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可再生能源：预测和风险管理 - 法国巴黎，2017 年 6 月 7-9 日
DOI：
10.1007/978-3-319-99052-1_11
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Cruise J
中科院分区：
文献类型：
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作者：
Cruise J
我们研究的最优控制的存储，这是用于套利和缓冲对意外事件（冲击），特别是应用到控制的能源系统中的随机和典型的时间异构的环境。我们的哲学是，作为正式的随机动态规划（SDP）的问题之一，但重铸的SDP递归的功能，如果已知的话，将减少相关的优化问题，这是确定性的，除了它必须重新解决的时候，冲击发生。在一个完全有效的商店面临线性购买和销售成本的情况下，这种方法所需的函数可以精确地确定;否则，它们通常可以被估计为良好的近似值。我们提供了最优控制策略的特征。我们还考虑了相关的确定性优化问题，概述了一种方法，它的解决方案，这是计算上易于处理的，并通过识别一个运行的预测地平线，适合在无限长的时间内的系统管理。我们给出了基于英国电价数据的例子。
We study the optimal control of storage which is used for both arbitrage and buffering against unexpected events (shocks), with particular applications to the control of energy systems in a stochastic and typically time-heterogeneous environment. Our philosophy is that of viewing the problem as being formally one of stochastic dynamic programming (SDP), but of recasting the SDP recursion in terms of functions which, if known, would reduce the associated optimisation problem to one which is deterministic, except that it must be re-solved at times when shocks occur. In the case of a perfectly efficient store facing linear buying and selling costs the functions required for this approach may be determined exactly; otherwise they may typically be estimated to good approximation. We provide characterisations of optimal control policies. We consider also the associated deterministic optimisation problem, outlining an approach to its solution which is both computationally tractable and—through the identification of a running forecast horizon—suitable for the management of systems over indefinitely extended periods of time. We give examples based on Great Britain electricity price data.