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short-paper

Innovative power operating center management exploiting big data techniques

Authors:

Michelangelo Ceci,

Nunziato Cassavia,

Roberto Corizzo,

Pietro Dicosta,

Donato Malerba,

Camillo PasturaAuthors Info & Claims

IDEAS '14: Proceedings of the 18th International Database Engineering & Applications Symposium

Pages 326 - 329

https://doi.org/10.1145/2628194.2628231

Published: 07 July 2014 Publication History

Abstract

The problem of accurately predicting the energy production from renewable sources has recently received an increasing attention from both the industrial and the research communities. It presents several challenges, such as facing with the rate data are provided by sensors, the heterogeneity of the data collected, power plants efficiency, as well as uncontrollable factors, such as weather conditions and user consumption profiles. In this paper we describe Vi-POC (Virtual Power Operating Center), a project conceived to assist energy producers and decision makers in the energy market. In this paper we present the Vi-POC project and how we face with challenges posed by the specific application. The solutions we propose have roots both in big data management and in stream data mining.

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Cited By

Mohamed Nazief Haggag Kotb Kholaif MXiao MTang X(2022)Covid-19′s fear-uncertainty effect on renewable energy supply chain management and ecological sustainability performance; the moderate effect of big-data analyticsSustainable Energy Technologies and Assessments10.1016/j.seta.2022.10262253(102622)Online publication date: Oct-2022
https://doi.org/10.1016/j.seta.2022.102622
Dymora PMazurek MSudek B(2021)Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW ServiceEnergies10.3390/en1422771914:22(7719)Online publication date: 18-Nov-2021
https://doi.org/10.3390/en14227719
Jack KAffia NOnu UOkekenwa EEzugwu EUdofa E(2021)Real Time Energy Monitoring and Control Model for Peer-to-Peer Integrated Hybrid Supply System2021 IEEE PES/IAS PowerAfrica10.1109/PowerAfrica52236.2021.9543440(1-5)Online publication date: 23-Aug-2021
https://doi.org/10.1109/PowerAfrica52236.2021.9543440
Show More Cited By

Index Terms

Innovative power operating center management exploiting big data techniques
1. Information systems
2. Software and its engineering

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Information

Published In

cover image ACM Other conferences

IDEAS '14: Proceedings of the 18th International Database Engineering & Applications Symposium

July 2014

411 pages

ISBN:9781450326278

DOI:10.1145/2628194

Editors:
Ana Maria Almeida
ISEP
,
Jorge Bernardino
CISUC-Polytechnic Institute of Coimbra
,
Elsa Ferreira Gomes
ISEP
,
General Chairs:
Bipin C. Desai
Concordia University
,
Jorge Bernardino
CISUC-Polytechnic Institute of Coimbra
,
Program Chairs:
Ana Maria Almeida
ISEP
,
Bipin C. Desai
Concordia University

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

ISEP: Instituto Superior de Engenharia do Porto
BytePress
Concordia University: Concordia University

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2014

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Short-paper

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Ministero dell'Istruzione, dell'Università e della Ricerca

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IDEAS '14

Sponsor:

ISEP
Concordia University

IDEAS '14: 18th International Database Engineering & Applications Symposium

July 7 - 9, 2014

Porto, Portugal

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Overall Acceptance Rate 74 of 210 submissions, 35%

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Citations

Cited By

Mohamed Nazief Haggag Kotb Kholaif MXiao MTang X(2022)Covid-19′s fear-uncertainty effect on renewable energy supply chain management and ecological sustainability performance; the moderate effect of big-data analyticsSustainable Energy Technologies and Assessments10.1016/j.seta.2022.10262253(102622)Online publication date: Oct-2022
https://doi.org/10.1016/j.seta.2022.102622
Dymora PMazurek MSudek B(2021)Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW ServiceEnergies10.3390/en1422771914:22(7719)Online publication date: 18-Nov-2021
https://doi.org/10.3390/en14227719
Jack KAffia NOnu UOkekenwa EEzugwu EUdofa E(2021)Real Time Energy Monitoring and Control Model for Peer-to-Peer Integrated Hybrid Supply System2021 IEEE PES/IAS PowerAfrica10.1109/PowerAfrica52236.2021.9543440(1-5)Online publication date: 23-Aug-2021
https://doi.org/10.1109/PowerAfrica52236.2021.9543440
Kava HSpanaki KPapadopoulos TDespoudi SRodriguez-Espindola OFakhimi M(2021)Data analytics diffusion in the UK renewable energy sector: an innovation perspectiveAnnals of Operations Research10.1007/s10479-021-04263-1333:2-3(717-742)Online publication date: 16-Sep-2021
https://doi.org/10.1007/s10479-021-04263-1
Corizzo RCeci MMalerba D(2019)Big Data Analytics and Predictive Modeling Approaches for the Energy Sector2019 IEEE International Congress on Big Data (BigDataCongress)10.1109/BigDataCongress.2019.00020(55-63)Online publication date: Jul-2019
https://doi.org/10.1109/BigDataCongress.2019.00020
Ceci MCorizzo RFumarola FIanni MMalerba DMaria GMasciari EOliverio MRashkovska ADesai BToyama M(2015)Big Data Techniques For Supporting Accurate Predictions of Energy Production From Renewable SourcesProceedings of the 19th International Database Engineering & Applications Symposium10.1145/2790755.2790762(62-71)Online publication date: 13-Jul-2015
https://dl.acm.org/doi/10.1145/2790755.2790762
Moguel EPreciado JSanchez-Figueroa FPreciado MHernandez J(2015)Multilayer Big Data Architecture for Remote Sensing in Eolic ParksIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing10.1109/JSTARS.2015.24155838:10(4714-4719)Online publication date: Oct-2015
https://doi.org/10.1109/JSTARS.2015.2415583

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