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Dynamic optimization for the management of stochastic generation and storage

机译:动态优化管理随机生成和存储

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In order to increase the amounts of renewable energy accommodated in the system, new tools that take into account the horizon of the decision taken are necessary. Feature like the availability of new information can be included in a dynamic optimization framework and therefore help mitigate congestion in the system and have positive effects on distribution systems. This study proposes a new algorithm and shows some preliminary results for the use of Energy Storage Systems (ESS) interacting with stochastic sources of generation. The initial motivation came from the study of the adoption of renewables for electricity, and how to better harness the power of sources that are inherently oscillatory in power output. The benefits of ESS in a dynamic optimization go beyond the amount of renewable energy actually dispatched in the system. The current debate and probable adoption of electrified transportation will most likely increase the pressure on local distribution systems. However, the availability of distributed energy will also increase, in the form of energy storage, once the interface between the grid and the power sources in the vehicles is developed in a mass scale.
机译:为了增加系统中容纳的可再生能源的数量,必须考虑到所做出决策的范围的新工具。诸如新信息的可用性之类的功能可以包含在动态优化框架中,因此有助于减轻系统中的拥塞并对配电系统产生积极影响。这项研究提出了一种新算法,并显示了使用储能系统(ESS)与随机发电源进行交互的一些初步结果。最初的动机来自对可再生能源用于电力的研究,以及如何更好地利用功率输出中固有振荡的能源。 ESS在动态优化中的好处超出了系统中实际分配的可再生能源的数量。当前的辩论和可能采用的电气化运输将最有可能增加对当地配电系统的压力。但是,一旦大规模开发了车辆的电网和电源之间的接口,以能量存储的形式分配的能量的可用性也将增加。

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