Control of a battery energy storage system connected to a low voltage grid

J.J.C.M. van Dun; Robert de Groot; Johan Morren; Han Slootweg

doi:10.1109/PTC.2015.7232405

Control of a battery energy storage system connected to a low voltage grid

J.J.C.M. van Dun, Robert de Groot, Johan Morren, Han Slootweg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

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Abstract

This paper describes the development of a control algorithm for a battery energy storage system, which is connected to a residential low voltage grid. By predicting future load demand and photovoltaic production within the neighbourhood concerned, flattening of the aggregated neighbourhood electricity demand is pursued. Historical electricity consumption data and weather predictions are incorporated into the prediction algorithm in order to achieve a further improvement of prediction accuracy, and with that a reduction of peak-load.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE PowerTech Conference, June 29 - July 2 2015, Eindhoven, The Netherlands
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.1109/PTC.2015.7232405
Publication status	Published - 29 Jul 2015
Event	2015 IEEE Power Tech - Eindhoven, Netherlands Duration: 29 Jun 2015 → 2 Jul 2015 http://powertech2015-eindhoven.tue.nl/

Conference

Conference	2015 IEEE Power Tech
Country/Territory	Netherlands
City	Eindhoven
Period	29/06/15 → 2/07/15
Internet address	http://powertech2015-eindhoven.tue.nl/

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title = "Control of a battery energy storage system connected to a low voltage grid",

abstract = "This paper describes the development of a control algorithm for a battery energy storage system, which is connected to a residential low voltage grid. By predicting future load demand and photovoltaic production within the neighbourhood concerned, flattening of the aggregated neighbourhood electricity demand is pursued. Historical electricity consumption data and weather predictions are incorporated into the prediction algorithm in order to achieve a further improvement of prediction accuracy, and with that a reduction of peak-load.",

author = "{van Dun}, J.J.C.M. and {de Groot}, Robert and Johan Morren and Han Slootweg",

year = "2015",

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day = "29",

doi = "10.1109/PTC.2015.7232405",

language = "English",

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booktitle = "Proceedings of the 2015 IEEE PowerTech Conference, June 29 - July 2 2015, Eindhoven, The Netherlands",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "2015 IEEE Power Tech ; Conference date: 29-06-2015 Through 02-07-2015",

url = "http://powertech2015-eindhoven.tue.nl/",

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van Dun, JJCM, de Groot, R, Morren, J & Slootweg, H 2015, Control of a battery energy storage system connected to a low voltage grid. in Proceedings of the 2015 IEEE PowerTech Conference, June 29 - July 2 2015, Eindhoven, The Netherlands. Institute of Electrical and Electronics Engineers, Piscataway, pp. 1-6, 2015 IEEE Power Tech, Eindhoven, Netherlands, 29/06/15. https://doi.org/10.1109/PTC.2015.7232405

Control of a battery energy storage system connected to a low voltage grid. / van Dun, J.J.C.M.; de Groot, Robert; Morren, Johan et al.

Proceedings of the 2015 IEEE PowerTech Conference, June 29 - July 2 2015, Eindhoven, The Netherlands. Piscataway : Institute of Electrical and Electronics Engineers, 2015. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Y1 - 2015/7/29

N2 - This paper describes the development of a control algorithm for a battery energy storage system, which is connected to a residential low voltage grid. By predicting future load demand and photovoltaic production within the neighbourhood concerned, flattening of the aggregated neighbourhood electricity demand is pursued. Historical electricity consumption data and weather predictions are incorporated into the prediction algorithm in order to achieve a further improvement of prediction accuracy, and with that a reduction of peak-load.

AB - This paper describes the development of a control algorithm for a battery energy storage system, which is connected to a residential low voltage grid. By predicting future load demand and photovoltaic production within the neighbourhood concerned, flattening of the aggregated neighbourhood electricity demand is pursued. Historical electricity consumption data and weather predictions are incorporated into the prediction algorithm in order to achieve a further improvement of prediction accuracy, and with that a reduction of peak-load.

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BT - Proceedings of the 2015 IEEE PowerTech Conference, June 29 - July 2 2015, Eindhoven, The Netherlands

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CY - Piscataway

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Y2 - 29 June 2015 through 2 July 2015

ER -

Control of a battery energy storage system connected to a low voltage grid

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