TY - GEN
T1 - An Analysis on PV Forecast Allocation for Distribution System Planning
AU - Rigoni, Valentin
AU - Melhorn, Alexander C.
AU - Keane, Andrew
AU - Taylor, Jason
N1 - Funding Information:
This work was carried out at the Electric Power Research Institute and has been supported by its members. V. Rigoni and A. Keane are supported by Science Foundation Ireland under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125. 978-1-5386-8218-0/19/$31.00 ©2019 IEEE
Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - As the adoption of residential photovoltaic (PV) continues to increase, its influence on distribution feeder voltage and currents also increases. Effective allocation or modelling on the appearance of PV across the system as a function of an adoption forecast is an important consideration for future distribution planning. The spatial information required for the forecast/allocation process is expected to be available to utilities at a cost proportional to its level of detail. Naturally, there is a need to understand the potential trade-offs between different modelling approaches and options. This paper explores three allocation models that differ on the complexity of their allocation mechanism. Both the error due to ignoring customers' PV adoption mechanisms and due to the PV forecast uncertainty are explored and compared.
AB - As the adoption of residential photovoltaic (PV) continues to increase, its influence on distribution feeder voltage and currents also increases. Effective allocation or modelling on the appearance of PV across the system as a function of an adoption forecast is an important consideration for future distribution planning. The spatial information required for the forecast/allocation process is expected to be available to utilities at a cost proportional to its level of detail. Naturally, there is a need to understand the potential trade-offs between different modelling approaches and options. This paper explores three allocation models that differ on the complexity of their allocation mechanism. Both the error due to ignoring customers' PV adoption mechanisms and due to the PV forecast uncertainty are explored and compared.
KW - Distributed generation
KW - Forecasting
KW - Power distribution
KW - Power system planning
KW - Renewable energy sources
UR - http://www.scopus.com/inward/record.url?scp=85075896870&partnerID=8YFLogxK
U2 - 10.1109/ISGTEurope.2019.8905670
DO - 10.1109/ISGTEurope.2019.8905670
M3 - Conference contribution
AN - SCOPUS:85075896870
T3 - Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
BT - Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 September 2019 through 2 October 2019
ER -