Abstract This paper proposes a hybrid robust-stochastic optimization model for smart home energy management in day-ahead (DA) and real-time (RT) energy markets which the uncertainties of energy prices and PV generation are investigated in the proposed model. A flexible robust optimization approach (ROA) is employed to create a tractable equivalent of the problem and manages the uncertainty of DA market prices when the PV generation is assumed in the worst-case. The ROA conservatism level can be adjusted by a control parameter and solutions with different levels of conservatism are obtained. Also, the proposed optimization framework considers the RT energy market and takes into account the associated uncertainties using stochastic programming (SP). At this stage, probable scenarios are used to model the uncertain characteristics of PV generation and energy prices. Loads are also considered to be controllable, while the comfort of inhabitants is considered. Results analysis show the advantage of the proposed hybrid method which makes sure decision-maker about the profitability of energy management. In the most conservatism case, the summation of profits of DA and RT markets is about 2.5 $/day.

中文翻译：

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使用混合稳健随机优化的智能家居能源管理

摘要 本文提出了一种用于日前（DA）和实时（RT）能源市场中智能家居能源管理的混合鲁棒-随机优化模型，该模型研究了能源价格和光伏发电的不确定性。采用灵活的稳健优化方法 (ROA) 来创建问题的易处理等价物，并在假设光伏发电处于最坏情况时管理 DA 市场价格的不确定性。ROA 保守性水平可以通过控制参数进行调整，得到不同保守性水平的解。此外，所提出的优化框架考虑了 RT 能源市场，并使用随机规划 (SP) 考虑了相关的不确定性。在这个阶段，可能的情景用于模拟光伏发电和能源价格的不确定特征。负荷也被认为是可控的，同时考虑了居民的舒适度。结果分析显示了所提出的混合方法的优势，可以确保决策者对能源管理的盈利能力。在最保守的情况下，DA 和 RT 市场的利润总和约为 2.5 美元/天。