Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings

Ane Feijoo-Arostegui; Nerea Goitia-Zabaleta; Aitor Milo; Haizea Gaztanaga; Laura Oca

doi:10.1109/EEM54602.2022.9921155

Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings

Ane Feijoo-Arostegui
, Nerea Goitia-Zabaleta
, Aitor Milo
, Haizea Gaztanaga
, Laura Oca

Basque Research and Technology Alliance (BRTA)

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

2 Citations (Scopus)

Abstract

This work presents a predictive energy management strategy for self-consumption in tertiary buildings. The self-consumption is composed of a photovoltaic generation and a battery. The energy management strategy is composed of a forecast module, high-level strategy and real-time adaptative control. Due to the daily forecast, significant data was available 24 hours in advance, allowing the energy management strategy to take advantage. The high-level strategy defines the battery's operation mode for each hour of the day. The real-time adaptative control corrects the possible errors with instant measurements and generates real-time battery commands and its operation mode. With this approach, a reduction of 16.17 % of the electric bill was obtained by comparing it to a scenario without a battery and its correspondent strategy. The development was integrated and validated in a test bench, obtaining a 60.43 % grid independence increase.

Original language	English
Title of host publication	18th International Conference on the European Energy Market, EEM 2022
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665408967
DOIs	https://doi.org/10.1109/EEM54602.2022.9921155
Publication status	Published - 2022
Event	18th International Conference on the European Energy Market, EEM 2022 - Ljubljana, Slovenia Duration: 13 Sept 2022 → 15 Sept 2022

Publication series

Name	International Conference on the European Energy Market, EEM
Volume	2022-September
ISSN (Print)	2165-4077
ISSN (Electronic)	2165-4093

Conference

Conference	18th International Conference on the European Energy Market, EEM 2022
Country/Territory	Slovenia
City	Ljubljana
Period	13/09/22 → 15/09/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

adaptative control
energy storage system
regression tree.
school
Self-consumption
tertiary building

Access to Document

10.1109/EEM54602.2022.9921155

Cite this

Feijoo-Arostegui, A., Goitia-Zabaleta, N., Milo, A., Gaztanaga, H., & Oca, L. (2022). Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings. In 18th International Conference on the European Energy Market, EEM 2022 (International Conference on the European Energy Market, EEM; Vol. 2022-September). IEEE Computer Society. https://doi.org/10.1109/EEM54602.2022.9921155

@inproceedings{aa54415a090c4d799eab473e7b3a247e,

title = "Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings",

abstract = "This work presents a predictive energy management strategy for self-consumption in tertiary buildings. The self-consumption is composed of a photovoltaic generation and a battery. The energy management strategy is composed of a forecast module, high-level strategy and real-time adaptative control. Due to the daily forecast, significant data was available 24 hours in advance, allowing the energy management strategy to take advantage. The high-level strategy defines the battery's operation mode for each hour of the day. The real-time adaptative control corrects the possible errors with instant measurements and generates real-time battery commands and its operation mode. With this approach, a reduction of 16.17 \% of the electric bill was obtained by comparing it to a scenario without a battery and its correspondent strategy. The development was integrated and validated in a test bench, obtaining a 60.43 \% grid independence increase.",

keywords = "adaptative control, energy storage system, regression tree., school, Self-consumption, tertiary building",

author = "Ane Feijoo-Arostegui and Nerea Goitia-Zabaleta and Aitor Milo and Haizea Gaztanaga and Laura Oca",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 18th International Conference on the European Energy Market, EEM 2022 ; Conference date: 13-09-2022 Through 15-09-2022",

year = "2022",

doi = "10.1109/EEM54602.2022.9921155",

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series = "International Conference on the European Energy Market, EEM",

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Feijoo-Arostegui, A, Goitia-Zabaleta, N, Milo, A, Gaztanaga, H & Oca, L 2022, Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings. in 18th International Conference on the European Energy Market, EEM 2022. International Conference on the European Energy Market, EEM, vol. 2022-September, IEEE Computer Society, 18th International Conference on the European Energy Market, EEM 2022, Ljubljana, Slovenia, 13/09/22. https://doi.org/10.1109/EEM54602.2022.9921155

Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings. / Feijoo-Arostegui, Ane; Goitia-Zabaleta, Nerea; Milo, Aitor et al.
18th International Conference on the European Energy Market, EEM 2022. IEEE Computer Society, 2022. (International Conference on the European Energy Market, EEM; Vol. 2022-September).

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

TY - GEN

T1 - Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings

AU - Feijoo-Arostegui, Ane

AU - Goitia-Zabaleta, Nerea

AU - Milo, Aitor

AU - Gaztanaga, Haizea

AU - Oca, Laura

PY - 2022

Y1 - 2022

N2 - This work presents a predictive energy management strategy for self-consumption in tertiary buildings. The self-consumption is composed of a photovoltaic generation and a battery. The energy management strategy is composed of a forecast module, high-level strategy and real-time adaptative control. Due to the daily forecast, significant data was available 24 hours in advance, allowing the energy management strategy to take advantage. The high-level strategy defines the battery's operation mode for each hour of the day. The real-time adaptative control corrects the possible errors with instant measurements and generates real-time battery commands and its operation mode. With this approach, a reduction of 16.17 % of the electric bill was obtained by comparing it to a scenario without a battery and its correspondent strategy. The development was integrated and validated in a test bench, obtaining a 60.43 % grid independence increase.

AB - This work presents a predictive energy management strategy for self-consumption in tertiary buildings. The self-consumption is composed of a photovoltaic generation and a battery. The energy management strategy is composed of a forecast module, high-level strategy and real-time adaptative control. Due to the daily forecast, significant data was available 24 hours in advance, allowing the energy management strategy to take advantage. The high-level strategy defines the battery's operation mode for each hour of the day. The real-time adaptative control corrects the possible errors with instant measurements and generates real-time battery commands and its operation mode. With this approach, a reduction of 16.17 % of the electric bill was obtained by comparing it to a scenario without a battery and its correspondent strategy. The development was integrated and validated in a test bench, obtaining a 60.43 % grid independence increase.

KW - adaptative control

KW - energy storage system

KW - regression tree.

KW - school

KW - Self-consumption

KW - tertiary building

UR - https://www.scopus.com/pages/publications/85141169537

U2 - 10.1109/EEM54602.2022.9921155

DO - 10.1109/EEM54602.2022.9921155

M3 - Conference contribution

AN - SCOPUS:85141169537

T3 - International Conference on the European Energy Market, EEM

BT - 18th International Conference on the European Energy Market, EEM 2022

PB - IEEE Computer Society

T2 - 18th International Conference on the European Energy Market, EEM 2022

Y2 - 13 September 2022 through 15 September 2022

ER -

Feijoo-Arostegui A, Goitia-Zabaleta N, Milo A, Gaztanaga H, Oca L. Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings. In 18th International Conference on the European Energy Market, EEM 2022. IEEE Computer Society. 2022. (International Conference on the European Energy Market, EEM). doi: 10.1109/EEM54602.2022.9921155

Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this