A Mycorrhizal Model for Transactive Solar Energy Markets with Battery Storage

A Mycorrhizal Model for Transactive Solar Energy Markets with Battery Storage
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DOI:
10.3390/en16104081
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发表时间:
2023-05
期刊:
影响因子:
3.2
通讯作者:
Z. Gould;V. Mohanty;Georg Reichard;Walid Saad;Tripp Shealy;Susan G. Day
Z. Gould;V. Mohanty;Georg Reichard;Walid Saad;Tripp Shealy;Susan G. Day
中科院分区:
工程技术4区
文献类型:
--
作者:
Z. Gould;V. Mohanty;Georg Reichard;Walid Saad;Tripp Shealy;Susan G. Day

文献摘要

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可以用生态系统(例如菌根网络)来模拟用于本地交互能源交易的分布式市场结构,这些生态系统已经进化为促进森林生态系统中的植物间碳交换。然而,这些生态系统的复杂性使人们很难理解采用这些模型可能对分布式能源系统产生的影响以及相关性能参数的大小。因此,我们简化并实施了先前开发的菌根能源市场模型蓝图,以隔离菌根干预的影响,允许建筑物在竞争的本地分散市场上重新分配部分能源资产。结果表明,与固定的零售上网电价市场结构相比,菌根干预对市场和建筑绩效指标的影响很小--与固定的零售上网电价市场结构相比,增加了市场自我消费,降低了市场自给自足,减少了所有季节性(冬季、秋季、夏季)和类型(住宅、混合用途)情况下的建筑周储蓄。工作最后讨论了通过强化学习进一步扩大拟议的菌根市场框架的机会,以及考虑到新兴的聚合分布式能源(DER)进入批发能源市场的限制和政策建议。
Distributed market structures for local, transactive energy trading can be modeled with ecological systems, such as mycorrhizal networks, which have evolved to facilitate interplant carbon exchange in forest ecosystems. However, the complexity of these ecological systems can make it challenging to understand the effect that adopting these models could have on distributed energy systems and the magnitude of associated performance parameters. We therefore simplified and implemented a previously developed blueprint for mycorrhizal energy market models to isolate the effect of the mycorrhizal intervention in allowing buildings to redistribute portions of energy assets on competing local, decentralized marketplaces. Results indicate that the applied mycorrhizal intervention only minimally affects market and building performance indicators—increasing market self-consumption, decreasing market self-sufficiency, and decreasing building weekly savings across all seasonal (winter, fall, summer) and typological (residential, mixed-use) cases when compared to a fixed, retail feed-in-tariff market structure. The work concludes with a discussion of opportunities for further expansion of the proposed mycorrhizal market framework through reinforcement learning as well as limitations and policy recommendations considering emerging aggregated distributed energy resource (DER) access to wholesale energy markets.