This paper addresses the problem faced by large electricity consumers to simultaneously determine the optimal day-ahead electricity procurement and the optimal energy-aware production schedule. The inherent uncertainty of the problem, due to the bidding process in the day-ahead market, is dealt with by means of the stochastic programming modeling framework. In particular, a two-stage problem is formulated with the aim of establishing the optimal bidding strategy and the optimal production schedule hedging against price uncertainty. The optimal integrated solution is defined to minimize the overall cost and to control the risk of high cost scenarios due to uncertain price peaks. The stochastic model is solved with a scenario-decomposition approach. Extensive numerical experiments have been carried out to assess the performance of the proposed decision approach. The results collected when considering an industrial relevant case-study show the superiority of the proposed methodology in comparison with a deterministic approach.

本文解决了大型用电者面临的问题，即同时确定最佳的日间提前用电采购和最佳的能源意识生产计划。由于日间市场的招标过程，问题的内在不确定性可以通过随机编程建模框架来解决。特别是，为了建立最优投标策略和针对价格不确定性对冲的最优生产计划，提出了一个两阶段问题。定义了最佳的集成解决方案，以最大程度地降低总体成本并控制由于不确定的价格峰值而导致高成本方案的风险。随机模型通过情景分解方法解决。已经进行了广泛的数值实验，以评估所提出决策方法的性能。在考虑行业相关案例研究时收集的结果表明，与确定性方法相比，该方法具有优越性。