Optimal Aggressive Level-based Offering Method for Hybrid PV Plants

Xiaoge Huang, Ziang Zhang, Zhenhuan Ding, Zhao Liu
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Abstract

Over the past few years, the penetration of solar power plants increased dramatically. Unlike traditional power plants, the uncertainty of Photovoltaic (PV) generation makes the offering process very challenging for PV plant operators. The uncertainty can be addressed by using the worst-case-based robust optimization. However, the solution to this method may be overly conservative. On the other hand, the battery energy storage system (BESS) is commonly used in PV plants, which can be used to reduce the uncertainty of PV generation. In this paper, a day-ahead offering method for the PV plant operator is proposed. As part of the proposed method, the optimal aggressive level of the offering decision is calculated by a data-driven method. Two scenarios that include a PV-only plant and a hybrid PV+BESS plant have been considered in our study. This paper also analyzed the potential advantage of pairing a BESS to a PV plant in the offering process. We found that the BESS can generate more revenue while reducing the risk of paying an under-generation charge under some conditions.
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基于最优进取水平的混合光伏电站供给方法
在过去的几年里,太阳能发电厂的普及率急剧增加。与传统电厂不同,光伏发电的不确定性使得光伏电站运营商在提供产品的过程中非常具有挑战性。这种不确定性可以通过基于最坏情况的鲁棒优化来解决。然而,这种方法的解决方案可能过于保守。另一方面,光伏电站通常采用电池储能系统(BESS),可以降低光伏发电的不确定性。本文提出了一种针对光伏电站运营商的日前报价方法。作为提出的方法的一部分,提供决策的最优侵略性水平是由数据驱动的方法计算。在我们的研究中考虑了两种情况,包括仅光伏电站和混合光伏+BESS电站。本文还分析了在提供过程中将BESS与光伏电站配对的潜在优势。我们发现,在某些条件下,BESS可以产生更多的收入,同时降低支付发电不足费用的风险。
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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