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Stochastic optimal dispatching strategy of electricity-hydrogen-gas-heat integrated energy system based on improved spectral clustering method
International Journal of Electrical Power & Energy Systems ( IF 5.0 ) Pub Date : 2021-03-01 , DOI: 10.1016/j.ijepes.2020.106495
Zixin Wang , Junjie Hu , Baozhu Liu

Abstract 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.

中文翻译:

基于改进谱聚类法的电氢气热一体化能源系统随机优化调度策略

摘要 综合能源系统(IES)中多种能源之间的耦合和相互作用显着提高了可再生能源的利用率,减少了碳排放。氢因其优异的特性被认为是最具潜力的能量载体之一。因此,氢的利用成为能源领域的一个热点。电转气(P2G)技术的研究大多没有利用氢的潜在优势,只分析电与天然气的耦合关系,效率低下。此外,可再生能源和负荷的不确定性给电力系统调度带来了挑战。为了解决这些问题,提出了一种基于改进谱聚类方法的电-氢-气-热综合能源系统(EHGHS)随机最优调度策略。首先,对 EHGHS 的结构和 EHGHS 中的能量转换单元进行建模。提出了一种利用氢利用过程和热电联产过程的两阶段P2G技术。然后提出一种基于改进谱聚类的情景约简方法来描述可再生能源和负荷的不确定特性。开发了曲线距离和余弦相似度来表示场景之间的相似度。最后,通过案例研究验证了随机最优调度模型的有效性、经济性和敏感性。对 EHGHS 的结构和 EHGHS 中的能量转换单元进行建模。提出了一种利用氢利用过程和热电联产过程的两阶段P2G技术。然后提出一种基于改进谱聚类的情景约简方法来描述可再生能源和负荷的不确定特性。开发了曲线距离和余弦相似度来表示场景之间的相似度。最后,通过案例研究验证了随机最优调度模型的有效性、经济性和敏感性。对 EHGHS 的结构和 EHGHS 中的能量转换单元进行建模。提出了一种利用氢利用过程和热电联产过程的两阶段P2G技术。然后提出一种基于改进谱聚类的情景约简方法来描述可再生能源和负荷的不确定特性。开发了曲线距离和余弦相似度来表示场景之间的相似度。最后,通过案例研究验证了随机最优调度模型的有效性、经济性和敏感性。然后提出一种基于改进谱聚类的情景约简方法来描述可再生能源和负荷的不确定特性。开发了曲线距离和余弦相似度来表示场景之间的相似度。最后,通过案例研究验证了随机最优调度模型的有效性、经济性和敏感性。然后提出一种基于改进谱聚类的情景约简方法来描述可再生能源和负荷的不确定特性。开发了曲线距离和余弦相似度来表示场景之间的相似度。最后,通过案例研究验证了随机最优调度模型的有效性、经济性和敏感性。
更新日期:2021-03-01
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