A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model
A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model
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DOI：
10.1016/j.energy.2021.120343
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发表时间：
2021-08
期刊：
影响因子：
9
通讯作者：
R. Yokoyama;Hiroki Kamada;Y. Shinano;T. Wakui
中科院分区：
文献类型：
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作者：
R. Yokoyama;Hiroki Kamada;Y. Shinano;T. Wakui
在设计能源供应系统时，设计人员应提高性能标准对能源需求不确定性的鲁棒性。本文基于混合整数线性模型，提出了一种基于分层混合整数线性规划（MILP）方法的能量供应系统鲁棒优化设计方法，以最大化能量需求不确定性下的能量供应系统鲁棒性。将不确定能量需求用区间表示，基于极小极大后悔准则的性能准则评价鲁棒性，考虑整数设计变量、不确定能量需求、整数和连续运行变量之间的关系，将鲁棒优化设计问题转化为3层min-max-minMILP问题.该问题通过在外部重复评估性能准则的最大遗憾的最小值的上界和下界，并在内部重复评估最大遗憾的上界和下界来解决。不同类型的优化问题的解决，应用层次MILP方法开发的普通优化设计问题，没有和修改。在一个案例研究中，所提出的方法被应用到热电联产系统的鲁棒优化设计。通过研究，确定了其正确性和有效性，并阐明了所得稳健设计的一些特点。
In designing energy supply systems, designers should heighten the robustness in performance criteria against the uncertainty in energy demands. In this paper, a robust optimal design method using a hierarchical mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy supply systems under uncertain energy demands based on a mixed-integer linear model. A robust optimal design problem is formulated as a three-level min-max-min MILP one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering relationships among integer design variables, uncertain energy demands, and integer and continuous operation variables. This problem is solved by evaluating upper and lower bounds for the minimum of the maximum regret of the performance criterion repeatedly outside, and evaluating lower and upper bounds for the maximum regret repeatedly inside. Different types of optimization problems are solved by applying a hierarchical MILP method developed for ordinary optimal design problems without and with its modifications. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system. Through the study, its validity and effectiveness are ascertained, and some features of the obtained robust designs are clarified.