TY - CHAP
T1 - Smart community load matching using stochastic demand modeling and historical production data
AU - Palacios-Garcia, Emilio J.
AU - Moreno-Munoz, Antonio
AU - Santiago, Isabel
AU - Moreno-Garcia, Isabel M.
AU - Milanes-Montero, Maria I.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/29
Y1 - 2016/8/29
N2 - The current upward trend of the residential energy demand and the high penetration of new renewable resources have changed the conception of the electrical grid. The centralized distribution scheme is currently moving forward to a distributed layout where the paradigm of Smart Energy Communities has emerged, meaning a set of households that share a Microgrid, have tied renewable production and can be either connected or disconnected from the main grid. In this context, due to the reduced dispatchability of the renewable generation, the planning of the installed PV power as well as the storage capacity is the cornerstone in order to achieve a high degree of both self-generation and self-consumption. However, the lack of detailed hourly or sub-hourly data makes it difficult. Therefore, this paper aims to present a high-resolution simulation method for evaluating the PV power and storage capacity requirements for a Smart Community based on a stochastic demand model and real PV production data, so the interplay between consumption and generation can be better understood.
AB - The current upward trend of the residential energy demand and the high penetration of new renewable resources have changed the conception of the electrical grid. The centralized distribution scheme is currently moving forward to a distributed layout where the paradigm of Smart Energy Communities has emerged, meaning a set of households that share a Microgrid, have tied renewable production and can be either connected or disconnected from the main grid. In this context, due to the reduced dispatchability of the renewable generation, the planning of the installed PV power as well as the storage capacity is the cornerstone in order to achieve a high degree of both self-generation and self-consumption. However, the lack of detailed hourly or sub-hourly data makes it difficult. Therefore, this paper aims to present a high-resolution simulation method for evaluating the PV power and storage capacity requirements for a Smart Community based on a stochastic demand model and real PV production data, so the interplay between consumption and generation can be better understood.
KW - Energy Consumption
KW - energy storage
KW - load modeling
KW - solar power generation
UR - https://www.scopus.com/pages/publications/84988424213
U2 - 10.1109/EEEIC.2016.7555885
DO - 10.1109/EEEIC.2016.7555885
M3 - Chapter
AN - SCOPUS:84988424213
T3 - EEEIC 2016 - International Conference on Environment and Electrical Engineering
BT - EEEIC 2016 - International Conference on Environment and Electrical Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Environment and Electrical Engineering, EEEIC 2016
Y2 - 7 June 2016 through 10 June 2016
ER -