Optimal Sizing for Wind/PV/Battery System Using Fuzzy -Means Clustering with Self-Adapted Cluster Number

IF 0.9 Q4 ENGINEERING, MECHANICAL

International Journal of Rotating Machinery Pub Date : 2017-09-26 DOI:10.1155/2017/5142825

Xin Liu, Hongkun Chen, Bing Huang, Yubo Tao

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引用次数: 10

Abstract

Integrating wind generation, photovoltaic power, and battery storage to form hybrid power systems has been recognized to be promising in renewable energy development. However, considering the system complexity and uncertainty of renewable energies, such as wind and solar types, it is difficult to obtain practical solutions for these systems. In this paper, optimal sizing for a wind/PV/battery system is realized by trade-offs between technical and economic factors. Firstly, the fuzzy -means clustering algorithm was modified with self-adapted parameters to extract useful information from historical data. Furthermore, the Markov model is combined to determine the chronological system states of natural resources and load. Finally, a power balance strategy is introduced to guide the optimization process with the genetic algorithm to establish the optimal configuration with minimized cost while guaranteeing reliability and environmental factors. A case of island hybrid power system is analyzed, and the simulation results are compared with the general FCM method and chronological method to validate the effectiveness of the mentioned method.

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基于自适应聚类数的模糊均值聚类优化风/光伏/电池系统的规模

将风力发电、光伏发电和电池储能相结合，形成混合动力系统已被公认为是可再生能源发展的前景。然而，考虑到可再生能源(如风能和太阳能)系统的复杂性和不确定性，很难获得这些系统的实用解决方案。在本文中，风电/光伏/电池系统的最佳尺寸是通过技术和经济因素之间的权衡来实现的。首先，利用自适应参数对模糊均值聚类算法进行改进，从历史数据中提取有用信息;在此基础上，结合马尔可夫模型确定了自然资源和负荷的时序系统状态。最后，引入功率均衡策略，利用遗传算法指导优化过程，在保证可靠性和环境因素的前提下，建立成本最小的最优构型。以孤岛混合动力系统为例进行了仿真分析，并将仿真结果与一般FCM法和时序法进行了比较，验证了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Rotating Machinery ENGINEERING, MECHANICAL-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

25 weeks

期刊介绍： This comprehensive journal provides the latest information on rotating machines and machine elements. This technology has become essential to many industrial processes, including gas-, steam-, water-, or wind-driven turbines at power generation systems, and in food processing, automobile and airplane engines, heating, refrigeration, air conditioning, and chemical or petroleum refining. In spite of the importance of rotating machinery and the huge financial resources involved in the industry, only a few publications distribute research and development information on the prime movers. This journal is the first source to combine the technology, as it applies to all of these specialties, previously scattered throughout literature.