We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity consumption and renewable power generation. The latter copes with the plausible deviations with respect to the forward schedule by making use of balancing power during the actual operation of the system. Standard industry practice deals with the uncertain net demand in the forward stage by replacing it with a good estimate of its conditional expectation (usually referred to as a point forecast), so as to minimize the need for balancing power in real time. However, it is well known that the cost structure of a power system is highly asymmetric and dependent on its operating point, with the result that minimizing the amount of power imbalances is not necessarily aligned with minimizing operating costs. In this paper, we propose a bilevel program to construct, from the available historical data, a prescription of the net demand that does account for the power system's cost asymmetry. Furthermore, to accommodate the strong dependence of this cost on the power system's operating point, we use clustering to tailor the proposed prescription to the foreseen net-demand regime. By way of an illustrative example and a more realistic case study based on the European power system, we show that our approach leads to substantial cost savings compared to the customary way of doing.

翻译：我们考虑一个包含日前调度和实时再调度的两阶段发电调度问题。日前调度必须在面临包含不可调度电力消耗和可再生能源发电的不确定净负荷下进行，而实时再调度则在实际系统运行中通过利用平衡功率来应对与日前调度计划的可能偏差。行业标准做法是在日前阶段将不确定的净负荷替换为其条件期望的良好估计（通常称为点预测），以最小化实时平衡功率需求。然而，众所周知电力系统的成本结构具有高度不对称性且依赖于运行点，因此最小化功率不平衡量并不一定与最小化运行成本相一致。本文提出一种双层规划方法，利用可用历史数据构建能够考虑电力系统成本不对称性的净负荷预测方案。进一步地，为适应运行成本对电力系统运行点的强依赖性，我们采用聚类方法针对预期净负荷状态对预测方案进行定制。通过一个算例和基于欧洲电力系统的更现实案例研究，我们证明相比常规方法，我们的方法能够显著降低运行成本。