建筑能源供应设计的多准则可调遗憾鲁棒优化
Multicriteria Adjustable Regret Robust Optimization for Building Energy Supply Design
AI总结：
针对建筑能源供应设计中的多准则冲突与价格不确定性，提出结合可调鲁棒优化与多准则优化的方法，同时最小化最坏情况成本遗憾与碳排放，并利用列与约束生成算法及 $\varepsilon$-约束方法求解。
摘要：
优化建筑的能源供应设计是一个具有多个竞争准则的任务，不仅需要考虑货币目标，还应考虑例如环境目标。此外，在决定购买哪些储能和供暖供冷设备（即时决策）时，能源（如电力和天然气）价格的未来发展存在不确定性。这可以在不确定性显现后，通过相应地操作设备（等待观察决策）来加以应对。因此，该问题可以建模为可调鲁棒优化问题。我们将可调鲁棒性与多准则优化相结合，应用于建筑能源供应设计，并使用列与约束生成算法结合 $\varepsilon$-约束方法求解所得问题。在多准则可调鲁棒问题中，我们同时最小化最坏情况成本遗憾和碳排放。我们考虑了未来价格不确定性，并从信息缺口决策理论的角度审视结果，以在抵御价格波动的安全性与过度保守之间找到权衡。我们提出了模型、求解策略，并讨论了案例研究建筑的不同应用场景。
英文摘要：
Optimizing a building's energy supply design is a task with multiple competing criteria, where not only monetary but also, for example, an environmental objective shall be taken into account. Moreover, when deciding which storages and heating and cooling units to purchase (here-and-now-decisions), there is uncertainty about future developments of prices for energy, e.g. electricity and gas. This can be accounted for later by operating the units accordingly (wait-and-see-decisions), once the uncertainty revealed itself. Therefore, the problem can be modeled as an adjustable robust optimization problem. We combine adjustable robustness and multicriteria optimization for the case of building energy supply design and solve the resulting problem using a column and constraint generation algorithm in combination with an $\varepsilon$-constraint approach. In the multicriteria adjustable robust problem, we simultaneously minimize worst-case cost regret and carbon emissions. We take into account future price uncertainties and consider the results in the light of information gap decision theory to find a trade-off between security against price fluctuations and over-conservatism. We present the model, a solution strategy and discuss different application scenarios for a case study building.
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