居家光伏-储能系统中的奥卡姆之刀：理论阐释、实践影响与改进方案
摘要
本文对广泛采用的基于规则的控制方法进行理论阐释并探讨可能的改进方案，该方法用于居家太阳能光伏（PV）配合储能系统（BSS）。本文称该方法为“奥卡姆之刀控制”，以其简单性及对14世纪威廉·奥卡姆的致敬。通过自消费最大化应用，证明奥卡姆之刀控制是一类称为在线凸学习的优化方法的特例。因此，首次推导了该控制方法的理论上界。 Furthermore, based on the theoretical insight, an alternative algorithm is devised on the same complexity level that outperforms Occam's. Practical data is used to evaluate the performance of these learning methods as compared to the classical rolling-horizon linear/quadratic programming. Findings support online learning methods for residential applications given their low complexity and small computation, communication, and data footprint. Consequences include improved economics for residential PV-BSS systems and mitigation of distribution systems' operational challenges associated with high PV penetration.
引用
@article{arxiv.2411.18876,
title = {Occam's Razor in Residential PV-Battery Systems: Theoretical Interpretation, Practical Implications, and Possible Improvements},
author = {Mostafa Farrokhabadi},
journal= {arXiv preprint arXiv:2411.18876},
year = {2024}
}