面向大数据驱动能源应用的BD4NRG参考架构

Katharina A. Wehrmeister, E. Bothos, Vangelis Marinakis, B. Magoutas, Alexander Pastor, Leonardo Carreras, A. Monti
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引用次数: 3

摘要

能源系统和相关服务的日益数字化为能源利益相关者带来了巨大的机会,他们可以利用大数据和人工智能技术来改进决策,并应对日益复杂和相互关联的能源系统所带来的挑战。IDSA、GAIA-X或FIWARE等大数据参考架构领域的倡议提供了共享、管理和处理大数据的通用框架。通过它们之间的对齐和缺失方面的集成,一个可互操作和安全的能源框架就出现了。本文提出的参考体系结构将朝着这一目标迈进,并将在欧洲能源部门的一组具体用例中进行实例化。在结构上受到sgram和BRIDGE参考体系结构的启发,它将具体的分析过程和数据源组件置于上下文中,将数据治理、安全性和价值创造等重要问题考虑在内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The BD4NRG Reference Architecture for Big Data Driven Energy Applications
The rising digitisation of the energy system and related services is unveiling an enormous opportunity for energy stakeholders to leverage on Big Data & AI technologies for improved decision making and coping with challenges emerging from an increasingly complex and interconnected energy system. Initiatives in the field of Big Data Reference Architectures, like IDSA, GAIA-X or FIWARE provide generic frameworks to share, manage and process Big Data. Through alignment among them and integration of missing aspects, an interoperable and secure framework for the energy comes into view. The Reference Architecture presented in this paper moves towards this goal and will be instantiated in a set of concrete use cases within the European Energy Sector. Structurally inspired by SGAM and the BRIDGE Reference Architecture, it puts concrete analytics processes and data source components into context, taking important issues of Data Governance, Security, and Value Creation into account.
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