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Dynamic optimization for the management of stochastic generation and storage

机译:随机生成管理管理的动态优化

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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:为了增加适用于系统中可再生能源的数量,考虑所采取的决策的地平线的新工具是必要的。功能类似于新信息的可用性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分发系统进行积极影响。本研究提出了一种新的算法,并显示了使用能量存储系统(ESS)与随机生成源的互动的一些初步结果。初始动机来自研究电力可再生能源的研究,以及如何更好地利用电力输出中固有振荡的源的力量。 ESS在动态优化中的好处超出了系统中实际派出的可再生能源量。目前的辩论和可能采用电气化运输将最有可能增加局部分配系统的压力。然而,一旦车辆中的电网和电源之间的界面以质量尺度显影,分布能量的可用性也将以能量存储形式增加。

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