配电网络分析民主化

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE DataCentric Engineering Pub Date : 2023-01-10 DOI:10.1017/dce.2022.41
M. Neaimeh, M. Deakin, Ryan Jenkinson, Oscar Giles
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引用次数: 1

摘要

摘要电动汽车(EV)和可再生能源技术的普及正在改变电网中电力流动的规模、可变性和方向。为了确保成功过渡到净零能源系统,广泛的利益相关者有必要了解这些不断变化的流量对网络的影响。然而,那些有数据和能力了解电力网络的人,如网络运营商,与那些在能源转型拼图的相邻部分工作的人,例如电力供应商和电动汽车充电基础设施运营商之间存在差距。本文描述了电动汽车网络分析工具(EVENT),该工具旨在帮助能源生态系统中更广泛的利益相关者进行网络分析,这些利益相关者可能没有带宽来策划和集成不同的数据集并进行电网模拟。EVENT分析了低碳技术对电网拥堵的潜在影响,有助于为产品和服务的设计提供信息。为了展示EVENT的潜力,我们使用能源供应商提供的广泛的智能电表数据集来评估电力智能电价对网络的影响。结果表明,网络运营商和能源供应商必须更加紧密地合作,以确保客户支持能源系统的灵活性最大化,同时尊重网络内的安全和安保约束。EVENT的模块化和开源方法实现了新方法和数据的集成,为工具的长期影响提供了经得起未来考验的能力。
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Democratizing electricity distribution network analysis
Abstract The uptake of electric vehicles (EVs) and renewable energy technologies is changing the magnitude, variability, and direction of power flows in electricity networks. To ensure a successful transition to a net zero energy system, it will be necessary for a wide range of stakeholders to understand the impacts of these changing flows on networks. However, there is a gap between those with the data and capabilities to understand electricity networks, such as network operators, and those working on adjacent parts of the energy transition jigsaw, such as electricity suppliers and EV charging infrastructure operators. This paper describes the electric vehicle network analysis tool (EVENT), developed to help make network analysis accessible to a wider range of stakeholders in the energy ecosystem who might not have the bandwidth to curate and integrate disparate datasets and carry out electricity network simulations. EVENT analyses the potential impacts of low-carbon technologies on congestion in electricity networks, helping to inform the design of products and services. To demonstrate EVENT’s potential, we use an extensive smart meter dataset provided by an energy supplier to assess the impacts of electricity smart tariffs on networks. Results suggest both network operators and energy suppliers will have to work much more closely together to ensure that the flexibility of customers to support the energy system can be maximized, while respecting safety and security constraints within networks. EVENT’s modular and open-source approach enables integration of new methods and data, future-proofing the tool for long-term impact.
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
期刊最新文献
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