Optimal Adjustment Strategy for Operating Schedule of Energy System under Uncertainty of Renewable Sources and Demand Changes
Optimal Adjustment Strategy for Operating Schedule of Energy System under Uncertainty of Renewable Sources and Demand Changes
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发表时间：
2016
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通讯作者：
Per Kvols;S. Ikeda;R. Ooka
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作者：
Per Kvols;S. Ikeda;R. Ooka
最近，电池和热能存储（TES）技术对于降低运营成本变得越来越重要。尽管之前有许多研究优化能源系统的运行计划，但它们只考虑了需求和光伏发电的完美预测，这意味着这些预测值在运行时不会改变。此外，一些考虑不确定性的研究提出了复杂的方法来测量或预测每个影响因素的影响，例如具有目标函数的室外温度和太阳辐射。因此，迫切需要一种能够在这种不确定性下对每个组件进行实时控制的实用方法。在本研究中，我们提出了一种新的优化策略来处理不确定性，并将其称为“两次步骤重新计算策略”（TtsR）。结果表明，当发电量和需求量发生不可预测的变化时，TtsR 比“所有时间步重新计算策略”（AtsR）需要更少的计算时间来获得准最优解；同时，TtsR 能够保持计算精度。
Recently, batteries and thermal energy storage (TES) technologies have become increasingly important for reducing operating costs. Although there have been many previous studies to optimise the operating schedule of energy systems, they only considered perfect predictions for demand and photovoltaic (PV) power generation, implying that these predicted values did not change at the operating time. In addition, some studies that considered the uncertainty proposed complex methods to measure or forecast the effect of each contributing factor, such as outdoor temperatures and solar radiation with an objective function. Therefore, a practical method that can specify a real-time control for each component under this uncertainty is strongly needed. In this study, we propose a new optimisation strategy to handle the uncertainty and call it the “two-time steps recalculation strategy” (TtsR). The results show that TtsR requires lower computational time than “all time steps recalculation strategy” (AtsR) to obtain a quasi-optimal solution when there were unpredicted changes in power generation and demand; meanwhile, TtsR was able to maintain computational accuracy.