TY - GEN
T1 - Load Variation Reduction by Aggregation in a Community of Rooftop PV Residences
AU - Gong, Huangjie
AU - Rallabandi, Vandana
AU - Ionel, Dan M.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - This paper performs computational studies and develops control schemes for a virtual power plant (VPP) network formed by a community of homes with rooftop solar PV generation, and battery energy storage. Appropriate control and scheduling of the battery operations, and peer-peer power flow between the homes provide a possible solutions for reducing the higher costs and uncertainties brought to grid by high solar PV penetration. The residential community studied here includes twelve homes categorized into four types depending on whether they have energy storage or rooftop solar PV panels. The homes exchange power among themselves, and the real-time electricity rate and the energy assignment for each are decided based on their individual bidding schemes. The homes benefit due to the lower electricity rate enabled by this aggregation, as compared with that available from the utility grid. In this work, the PV generation and load consumption for the different types of homes are calculated from building models. Simulation studies demonstrate that the advantages of the proposed transactive power flow include lower maximum power demand as well as reduced peak-peak power on the duck curve.
AB - This paper performs computational studies and develops control schemes for a virtual power plant (VPP) network formed by a community of homes with rooftop solar PV generation, and battery energy storage. Appropriate control and scheduling of the battery operations, and peer-peer power flow between the homes provide a possible solutions for reducing the higher costs and uncertainties brought to grid by high solar PV penetration. The residential community studied here includes twelve homes categorized into four types depending on whether they have energy storage or rooftop solar PV panels. The homes exchange power among themselves, and the real-time electricity rate and the energy assignment for each are decided based on their individual bidding schemes. The homes benefit due to the lower electricity rate enabled by this aggregation, as compared with that available from the utility grid. In this work, the PV generation and load consumption for the different types of homes are calculated from building models. Simulation studies demonstrate that the advantages of the proposed transactive power flow include lower maximum power demand as well as reduced peak-peak power on the duck curve.
KW - Aggregation
KW - Battery Control Scheme
KW - Smart Home
KW - Time of Use Rate
KW - Virtual Power Plant (VPP)
UR - http://www.scopus.com/inward/record.url?scp=85097585731&partnerID=8YFLogxK
U2 - 10.1109/PESGM40551.2019.8974029
DO - 10.1109/PESGM40551.2019.8974029
M3 - Conference contribution
AN - SCOPUS:85097585731
T3 - IEEE Power and Energy Society General Meeting
BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Y2 - 4 August 2019 through 8 August 2019
ER -