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评估不同电网拓扑结构和产消者份额下低压能量计量表的技术经济效益。

Assessing the techno-economic benefits of LEMs for different grid topologies and prosumer shares.

作者信息

Doepfert Markus, Candas Soner, Kraus Hermann, Tzscheutschler Peter, Hamacher Thomas

机构信息

Technical University of Munich, TUM School of Engineering and Design, Chair of Renewable and Sustainable Energy Systems, Lichtenbergstr. 4a, 85748 Garching, Germany.

OTH Regensburg University of Applied Sciences, Faculty of Electrical Engineering and Information Technology, Research Center of Power Systems and Energy Storages, Seybothstraße 2, 93053 Regensburg, Germany.

出版信息

iScience. 2025 Apr 23;28(6):112493. doi: 10.1016/j.isci.2025.112493. eCollection 2025 Jun 20.

DOI:10.1016/j.isci.2025.112493
PMID:40612905
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12225898/
Abstract

The shift toward decentralized and renewable energy sources has introduced significant challenges to traditional power systems, necessitating innovative market designs. Local energy markets present a viable solution for integrating distributed energy resources such as photovoltaic systems, electric vehicles, and heat pumps. This study investigates the techno-economic implications of local energy markets compared to conventional market designs, focusing on their impact on average energy prices and operational peak power. Through comprehensive simulations across various grid topologies with varying penetration levels of the distributed energy resources, totaling 400 simulation setups, we demonstrate that local energy markets can enhance economic efficiency and grid stability with 99% of the scenarios boasting lower average energy prices and 80% lower operational peak power levels. The findings suggest that local energy markets can play a role in the future energy system, provided that additional infrastructure, management costs, and bureaucratic complexity are kept to a minimum.

摘要

向分散式和可再生能源的转变给传统电力系统带来了重大挑战,因此需要创新的市场设计。本地能源市场为整合分布式能源资源(如光伏系统、电动汽车和热泵)提供了一个可行的解决方案。本研究调查了与传统市场设计相比,本地能源市场的技术经济影响,重点关注其对平均能源价格和运营峰值功率的影响。通过对各种电网拓扑结构进行全面模拟,分布式能源资源的渗透率各不相同,总共400个模拟设置,我们证明本地能源市场可以提高经济效率和电网稳定性,99%的情景平均能源价格更低,运营峰值功率水平降低80%。研究结果表明,只要将额外的基础设施、管理成本和官僚复杂性降至最低,本地能源市场就可以在未来能源系统中发挥作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/a51d60e04bbe/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/d91fc87ed0d7/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/36960f636a45/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/c26ce37927b9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/366430346e6e/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/3c4d4cd6a5bc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/ceb4da31f105/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/56cb325a7cea/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/fc3eea8274eb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/8224545f941d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/556b8ba6d2f9/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/59b1f2dbc75e/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/a51d60e04bbe/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/d91fc87ed0d7/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/36960f636a45/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/c26ce37927b9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/366430346e6e/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/3c4d4cd6a5bc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/ceb4da31f105/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/56cb325a7cea/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/fc3eea8274eb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/8224545f941d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/556b8ba6d2f9/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/59b1f2dbc75e/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba48/12225898/a51d60e04bbe/gr11.jpg

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本文引用的文献

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2
Dataset on electrical single-family house and heat pump load profiles in Germany.德国电气单户住宅和热泵负荷曲线数据集。
Sci Data. 2022 Feb 15;9(1):56. doi: 10.1038/s41597-022-01156-1.