sles_db.sql (41.16 kB)
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Data Management and Processing for Demonstrator Projects

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posted on 19.03.2021, 16:13 by Kunpeng WangKunpeng Wang

Smart local energy systems require the communication, automation and engagement of individual systems, each producing substantial quantities of data. Data analytics and digital communication technologies need to be used to explore and investigate hypothetical and real-time operating scenarios for future smart local energy systems.

To conduct experimental data analysis of the way energy is generated, stored, shared and consumed, the Newcastle team created the SLES database to store data from our partners and results of our case studies. A novel, generic and scalable smart energy platform for optimised design and the real-time efficient control of power generation and delivery for local energy systems through IoT services for data analytics was proposed.

The structure of each table of the SLES database is shown in the attached sql file (sles_db.sql). The design and functionality of the smart energy platform is presented in the paper submitted to IREC2021 - 12th International Renewable Engineering Conference (https://irec2021.meu.edu.jo/). The title of the paper is "An integration platform for optimised design and real-time control of smart local energy systems".

Funding

Smarthubs SLES

Innovate UK

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History

UoA

Engineering