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首页> 外文期刊>International journal of electrical power and energy systems >Stochastic optimal dispatching strategy of electricity-hydrogen-gas-heat integrated energy system based on improved spectral clustering method
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Stochastic optimal dispatching strategy of electricity-hydrogen-gas-heat integrated energy system based on improved spectral clustering method

机译:基于改进的光谱聚类方法的电力 - 氢气 - 气体 - 热集成能量系统随机最优调度策略

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摘要

The couplings and interactions among the multi-energy resources in the integrated energy system (IES) significantly improve the utilization of renewables and reduce carbon emissions. Hydrogen is considered to be one of the most potential energy carriers due to its excellent characteristics. Therefore, the use of hydrogen has become a hot spot in the energy field. Most researches on power to gas (P2G) technology do not use the potential advantages of hydrogen but only analyze the coupling relationship between electricity and natural gas, so the efficiency is low. Moreover, the uncertainties of renewable energy and load bring challenges to the power system dispatching. To solve these problems, an electricity-hydrogen-gas-heat integrated energy system (EHGHS) stochastic optimal dispatching strategy based on improved spectral clustering method is presented in this paper. First, the structure of EHGHS and the energy conversion unit in the EHGHS is modeled. A two-stage P2G technology is proposed which exploits the hydrogen utilization process and the combined heat and power generation process. Then a scenario reduction method based on improved spectral clustering is presented to describe the uncertain characteristics of renewable energy and load. The curve distance and cosine similarity are developed to represent the similarity between scenarios. Finally, the effectiveness, economics, and sensitivity of the stochastic optimal dispatching model are verified by case studies.
机译:集成能源系统(IE)中多能源资源之间的联轴器和相互作用显着提高了可再生能源的利用率,降低了碳排放。由于其优异的特性,氢被认为是最潜在的能量载体之一。因此,使用氢气已成为能源场中的热点。对天然气(P2G)技术的大多数研究不使用氢气的潜在优势,但仅分析电力和天然气之间的耦合关系,因此效率低。此外,可再生能源和负荷的不确定性为电力系统调度带来了挑战。为了解决这些问题,本文提出了一种基于改进的光谱聚类方法的电力 - 氢气 - 气 - 热集成能量系统(EHGHS)随机最佳调度策略。首先,建模EHGHS和EHGHS中的能量转换单元的结构。提出了一种两级P2G技术,该技术利用氢利用过程和组合的热量和发电过程。然后,提出了一种基于改进的光谱聚类的场景还原方法来描述可再生能量和负载的不确定特征。曲线距离和余弦相似度是开发的,以表示场景之间的相似性。最后,通过案例研究验证了随机最佳调度模型的有效性,经济和灵敏度。

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