使用FlexOffers建模和管理能源灵活性

T. Pedersen, Laurynas Siksnys, B. Neupane
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引用次数: 21

摘要

最近分布式可再生能源和智能物联网设备的普及为能源灵活性的使用提供了令人兴奋的新可能性,开启了所谓的自下而上或蜂窝能源系统的新时代。为了充分利用灵活性的潜力,必须以一种能够有效管理、操纵和在市场上交易的方式对灵活性进行建模和表示。在本文中,我们提供了FlexOffer概念的全面概述,该概念提供了一种有效的方法来建模和管理能源需求和供应灵活性,这些灵活性来自广泛的灵活资源及其总量。首先,我们定义了基本概念,并提出了FlexOffer生命周期的不同阶段。然后,我们讨论了更高级的内部FlexOffer约束,以及FlexOffer生成、聚合、分解和定价的算法,这些算法可以显著降低能源管理和交易的复杂性,并提高整体效率。最后,我们提出了一个通用的分散系统架构,用于现有和新市场的交易灵活性(FlexOffers)。我们的实验结果表明:(1)FlexOffers的提取准确率高达98%,(2)聚合和分解可以扩展到1000K FlexOffers甚至更多,(3)灵活性可以在NordPool弹性订单市场进行交易,同时提供高达89.9%(最优)的能源成本降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Managing Energy Flexibility Using FlexOffers
The recent spread of distributed renewable energy sources and smart IoT devices offer exciting new possibilities for the use of energy flexibility, opening a new era of the so-called bottom-up or cellular energy systems. In order to harness the full potential of flexibility, flexibility has to be modeled and represented in a manner that can be efficiently managed, manipulated, and traded on a market. In this paper, we provide a comprehensive overview of the FlexOffer concept, which offers an effective way of modeling and managing energy demand and supply flexibilities from a wide range of flexible resources and their aggregates. First, we define the basic concept and present the different phases of the FlexOffer life-cycle. Then, we discuss more advanced internal FlexOffer constraints as well as algorithms for FlexOffer generation, aggregation, disaggregation, and pricing that can significantly reduce energy management and trading complexities and increase overall efficiency. Finally, we present a general decentralized system architecture for trading flexibility (FlexOffers) in existing and new markets. Our experimental results show that (1) FlexOffers can be extracted with up to 98% accuracy, (2) aggregation and disaggregation can scale to 1000K FlexOffers and more, and (3) flexibility can be traded in the NordPool flexi order market while providing up to 89.9% (of optimal) reduction in the energy cost.
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