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A Stream Processing Framework Based on Linked Data for Information Collaborating of Regional Energy Networks | IEEE Journals & Magazine | IEEE Xplore

A Stream Processing Framework Based on Linked Data for Information Collaborating of Regional Energy Networks


Abstract:

Coordinating of energy networks to form a city-level multidimensional integrated energy system becomes a new trend in Energy Internet (EI). The collaborating in the infor...Show More

Abstract:

Coordinating of energy networks to form a city-level multidimensional integrated energy system becomes a new trend in Energy Internet (EI). The collaborating in the information layer is a core issue to achieve smart integration. However, the heterogeneity of multiagent data, the volatility of components, and the real-time analysis requirement in EI bring significant challenges. To solve these problems, in this article we propose a stream processing framework based on linked data for information collaboration among multiple energy networks. The framework provides a universal data representation based on linked data and semantic relation discovery approach to model and semantically fuse heterogeneous data. Semantics-based information transmission contracts and channels are automatically generated to adapt to structural changes in EI. A multimodel-based dynamic adjusting stream processing is implemented using data semantics. A real-world case study is implemented to demonstrate the adaptability, feasibility, and flexibility of the proposed framework.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 17, Issue: 1, January 2021)
Page(s): 179 - 188
Date of Publication: 04 December 2019

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