Multiyear microgrid data from a research building in Tsukuba, Japan

Microgrids comprising renewable energy technologies are often modelled and optimised from a theoretical point of view. Verification of theoretical systems with data of actually implemented systems in the field rarely occurs in an open manner, especially on the intermediate scale of research building...

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Bibliographic Details
Published inScientific data Vol. 6; no. 1; p. 190020
Main Authors Vink, Karina, Ankyu, Eriko, Koyama, Michihisa
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 19.02.2019
Subjects
Data acquisition
Data collection
Data Descriptor
Electricity
Electricity distribution
Energy
Radiation
Renewable resources
Japan
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Summary:Microgrids comprising renewable energy technologies are often modelled and optimised from a theoretical point of view. Verification of theoretical systems with data of actually implemented systems in the field rarely occurs in an open manner, especially on the intermediate scale of research buildings. To enable modelling of the actual microgrid performance of a research environment, we present a multiyear dataset of a microgrid with solar arrays and a battery. The main energy datasets comprise data per second supplemented by hourly solar irradiation data. These may be combined with data concerning the hourly electricity prices from the main grid and the low-electricity-price periods of national holidays. The level of detail of the data per second in combination with the hourly data in these datasets allows for a comparison to the efficiency and weather-parameter correlation of other renewable energy technologies, as well as forecasting future energy generation and consumption.
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K.V. co-designed the research, collected and prepared the datasets, performed the technical validation, and co-wrote the manuscript. E.A. assisted in gathering datasets for the data per second and preparing the datasets. M.K. co-designed the research and co-wrote the manuscript. All authors discussed the data, data cleaning, and metadata.
ISSN:2052-4463
2052-4463
DOI:10.1038/sdata.2019.20