TY - GEN
T1 - Robust allocation of residential solar photovoltaic systems paired with battery units in South Australia
AU - Aghamohamadi, Mehrdad
AU - Mahmoudi, Amin
AU - Haque, Mohammed H.
PY - 2019/11/28
Y1 - 2019/11/28
N2 - A huge portion of solar photovoltaic (PV) systems is installed in residential sector, recently. Considering the uncertain nature of PV generation, battery units are coupled with these systems to provide a better performance when trading power with upstream network. Although, pairing PVs with battery units (PV-battery) provides a promising operation, the uncertainties of load and solar radiation poses a noticeable effect on optimal sizing of such systems. Therefore, an appropriate characterization of these uncertainties is essential when sizing residential PV-battery systems. This can assist decision makers to 1) optimally design their system from both economical and operational perspectives, and 2) avoid non-optimal sizing decisions, regarding the huge investment costs of these systems. This study presents a robust optimization (RO) approach for sizing residential PV-battery systems, characterizing the uncertainties of load and solar radiation. The proposed model determines the optimal capacity of a residential PV-battery system while minimizing its operation costs considering the uncertain parameters' variations. The RO model is developed as a max-min optimization problem. According to the obtained results, the proposed robust model gives a greater sizing solution (50% increase in PV capacity), which is more reliable when the uncertain parameters deviate from the forecasted values.
AB - A huge portion of solar photovoltaic (PV) systems is installed in residential sector, recently. Considering the uncertain nature of PV generation, battery units are coupled with these systems to provide a better performance when trading power with upstream network. Although, pairing PVs with battery units (PV-battery) provides a promising operation, the uncertainties of load and solar radiation poses a noticeable effect on optimal sizing of such systems. Therefore, an appropriate characterization of these uncertainties is essential when sizing residential PV-battery systems. This can assist decision makers to 1) optimally design their system from both economical and operational perspectives, and 2) avoid non-optimal sizing decisions, regarding the huge investment costs of these systems. This study presents a robust optimization (RO) approach for sizing residential PV-battery systems, characterizing the uncertainties of load and solar radiation. The proposed model determines the optimal capacity of a residential PV-battery system while minimizing its operation costs considering the uncertain parameters' variations. The RO model is developed as a max-min optimization problem. According to the obtained results, the proposed robust model gives a greater sizing solution (50% increase in PV capacity), which is more reliable when the uncertain parameters deviate from the forecasted values.
KW - Battery
KW - Residential energy system
KW - Robust optimization
KW - Solar photovoltaic
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85076777775&partnerID=8YFLogxK
U2 - 10.1109/ECCE.2019.8913208
DO - 10.1109/ECCE.2019.8913208
M3 - Conference contribution
T3 - 2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019
SP - 6673
EP - 6679
BT - 2019 IEEE Energy Conversion Congress and Exposition, ECCE 2019
PB - Institute of Electrical and Electronics Engineers
T2 - 11th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2019
Y2 - 29 September 2019 through 3 October 2019
ER -