@inproceedings{367684ce26804373baa60fd674b94ead,
title = "Big data solutions - Data ingestion and stream processing for demand response management",
abstract = "The electricity demand has become more and more active significantly contributing to the sustainable development of the power systems. In this era, the demand response or the electricity consumers' reaction needs to be quick. Thus, the data processing is relevant for many parties such as consumers, suppliers, grid and market operators. Multiple activities such as the consumption monitoring, appliances scheduling, integration of local micro-generation, implementation of the advanced tariff scheme, electric vehicles and storage devices management are various data sources that are continuously generated and requires Big Data technologies. In this paper, we investigate a pipeline solution (data ingestion and stream processing) for demand response management considering the progress of sensors and communication systems that generate a large volume of data.",
keywords = "Demand response, Kafka, Spark Streaming",
author = "Oprea, \{Simona Vasilica\} and Adela Bara and Vlad Diaconita and Dan Preotescu and Tor, \{Osman Bulent\}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 23rd International Conference on System Theory, Control and Computing, ICSTCC 2019 ; Conference date: 09-10-2019 Through 11-10-2019",
year = "2019",
month = oct,
doi = "10.1109/ICSTCC.2019.8885519",
language = "English",
series = "2019 23rd International Conference on System Theory, Control and Computing, ICSTCC 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "697--702",
editor = "Radu-Emil Precup",
booktitle = "2019 23rd International Conference on System Theory, Control and Computing, ICSTCC 2019 - Proceedings",
address = "United States",
}