Integrating Renewable Energy Technologies into Distributed Energy Systems Maintaining System Flexibility

A. Perera, P. Wickramasinghe, J. Scartezzini, V. Nik
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引用次数: 6

Abstract

Flexibility of the energy system plays a vital role when integrating non-dispatchable renewable energy technologies. However, flexibility of the energy system has been often discussed only focusing on the operation of the energy system. This study extends the flexibility concept considering both design and operation of the energy system. In order to achieve this, pseudo chronological scenarios used for stochastic optimization is used to define system flexibility. Multiple criterions are considered when evaluating the flexibility of the system and fuzzy logic is used to consider the ambiguity in the assessment process when localizing into a specific application. Subsequently, multi objective optimization is conducted to design a multi-energy hub considering net present value (NPV), system flexibility and renewable energy generation. GPU-accelerated computing is introduced to speed up the computing when evaluating the objective functions for number of scenarios. Results of the study show that poor system flexibility can leads to poor utilization of renewable energy generated. More importantly, penetration levels of non-dispatchable renewable energy technologies notably reduce by 20–30% when considering the flexibility of the energy system which guarantees robust operation.
将可再生能源技术集成到分布式能源系统中,保持系统的灵活性
在整合不可调度的可再生能源技术时,能源系统的灵活性起着至关重要的作用。然而,人们对能源系统灵活性的讨论往往只关注于能源系统的运行。本研究从能源系统的设计和运行两方面扩展了柔性概念。为了实现这一点,使用用于随机优化的伪时间场景来定义系统灵活性。在评估系统的灵活性时考虑了多个标准,并在定位到特定应用时使用模糊逻辑来考虑评估过程中的模糊性。随后,考虑净现值(NPV)、系统灵活性和可再生能源发电,进行多目标优化设计。引入gpu加速计算,加快了对多个场景下目标函数的计算速度。研究结果表明,系统灵活性差会导致产生的可再生能源利用率差。更重要的是,考虑到保证稳健运行的能源系统的灵活性,不可调度可再生能源技术的渗透水平显著降低了20-30%。
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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