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  5. An Analysis on PV Forecast Allocation for Distribution System Planning
 
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An Analysis on PV Forecast Allocation for Distribution System Planning

Author(s)
Rigoni, Valentin  
Melhorn, Alexander C.  
Keane, Andrew  
Taylor, Jason  
Uri
http://hdl.handle.net/10197/26113
Date Issued
2019-09-02
Date Available
2024-05-31T11:58:45Z
Abstract
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.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2019 IEEE
Subjects

Distributed generatio...

Forecasting

Power distribution

Power systems plannin...

Power generation econ...

Power generation plan...

DOI
10.1109/ISGTEurope.2019.8905670
Web versions
https://site.ieee.org/isgt-europe-2019
Language
English
Status of Item
Peer reviewed
Journal
Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
Conference Details
The 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, Romania, 29 September - 2 October 2019
ISBN
9781538682180
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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ISGT Europe 2019.pdf

Size

2.28 MB

Format

Adobe PDF

Checksum (MD5)

d0750811f75a8dbd79234ee7f22e45e4

Owning collection
Electrical and Electronic Engineering Research Collection
Mapped collections
Energy Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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