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
N1 - Publisher Copyright:
© 2022 IEEE.
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 -
