On most modern energy markets, electricity is traded in advance and a power producer has to commit to deliver a certain amount of electricity some time before the actual delivery. This is especially difficult for power producers with renewable energy sources that are stochastic (like wind and solar). Thus, short-term electricity storages like batteries are used to increase flexibility. By contrast, long-term storages allow to exploit price fluctuations over time, but have a comparably bad efficiency over short periods of time.

In this paper, we consider the decision problem of a power producer who sells electricity from wind turbines on the continuous intraday market and possesses two storage devices: a battery and a hydrogen based storage system. The problem is solved with a backwards approximate dynamic programming algorithm with optimal computing budget allocation. Numerical results show the algorithm's high solution quality. Furthermore, tests on real-world data demonstrate the value of using both storage types and investigate the effect of the storage parameters on profit.

在大多数现代能源市场上，电力是预先交易的，电力生产商必须承诺在实际交付之前的某个时间交付一定数量的电力。对于具有随机（如风能和太阳能）可再生能源的电力生产商而言，这尤其困难。因此，诸如电池之类的短期蓄电被用于增加灵活性。相比之下，长期存储允许利用随时间变化的价格波动，但在短期内效率相对较低。

在本文中，我们考虑一个发电商的决策问题，该发电商在连续的盘中市场上从风力涡轮机出售电力，并且拥有两个存储设备：电池和基于氢的存储系统。使用具有最佳计算预算分配的后向近似动态规划算法解决了该问题。数值结果表明该算法具有较高的求解质量。此外，对实际数据的测试证明了使用两种存储类型的价值，并研究了存储参数对利润的影响。