Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems
Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems
复制标题
能源存储和供应系统长期运营规划的收缩和后退方法
DOI：
10.1016/j.energy.2021.122066
复制
发表时间：
2022
期刊：
影响因子：
9
通讯作者：
Ryohei Yokoyama
中科院分区：
文献类型：
--
作者：
Tetsuya Wakui;Kazuki Akai;Ryohei Yokoyama
为了有效地解决储能和供电系统的长期运行规划问题，提出了一种基于收缩地平线和后退地平线的近最优求解方法。首先通过求解一个简化问题来计算原问题的下界，该简化问题减少了二元变量的数量并简化了相关约束。然后，将简化后的问题结果作为存储能量的终端条件，求解了规划视界长度缩小的短期运行规划问题。在该问题中，考虑了原始的二元变量和约束条件。短期作业计划采用地平线后退法进行更新，其中初始和终止条件分别由以前的短期作业计划结果和简化的问题结果提供。将所有更新视界的解连接起来得到的解作为原问题的近最优解。将该方法应用于解决一个储能和供电系统的长期运行规划问题，该系统包括一个光伏单元和一个带水电解槽的金属氢化物罐。结果表明，该方法能在较短的计算时间内得到较好的解。
To efficiently solve long-term operational planning problems of energy storage and supply systems, a near-optimal solution method based on the shrinking and receding horizon approaches was developed. A lower bound of the original problem is first calculated by solving a simplified problem, in which the number of binary variables is reduced and the related constraints are simplified. Then, a short-term operational planning problem, with a shrunken planning horizon length, is solved by providing the simplified problem results as the terminal condition for stored energy. Within this problem, the original binary variables and constraints are considered. The short-term operational planning is updated using a receding horizon approach, in which the initial and terminal conditions are provided by the previous short-term operational planning results and simplified problem results, respectively. The solution, obtained by connecting the solutions in all the updating horizons, is regarded as a near-optimal solution of the original problem. The developed method was applied to solve a long-term operational planning problem for an energy storage and supply system, which includes a photovoltaic unit and a metal hydride tank with a water electrolyzer. The results showed that the developed method could find a better solution in a shorter computation time than the conventional methods.
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