TY - JOUR
T1 - Residential load and rooftop PV generation
T2 - an Australian distribution network dataset
AU - Ratnam, Elizabeth L.
AU - Weller, Steven R.
AU - Kellett, Christopher M.
AU - Murray, Alan T.
N1 - Publisher Copyright:
© 2015 Taylor & Francis.
PY - 2017/9/14
Y1 - 2017/9/14
N2 - Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting ‘clean’ dataset, we identify key customer-specific and aggregated characteristics of rooftop PV generation and residential load.
AB - Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting ‘clean’ dataset, we identify key customer-specific and aggregated characteristics of rooftop PV generation and residential load.
KW - Solar photovoltaics
KW - dataset
KW - feed-in tariffs
KW - residential load
KW - time-of-use metering
UR - http://www.scopus.com/inward/record.url?scp=84945260766&partnerID=8YFLogxK
U2 - 10.1080/14786451.2015.1100196
DO - 10.1080/14786451.2015.1100196
M3 - Article
SN - 1478-6451
VL - 36
SP - 787
EP - 806
JO - International Journal of Sustainable Energy
JF - International Journal of Sustainable Energy
IS - 8
ER -