期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 11, 期 1, 页码 232-241出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2014.2365703
关键词
Distribution network; forecasting; smart grid; smart metering; solar power; spatial-temporal
类别
资金
- North Portugal Regional Operational Programme (ON.2-O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF)
- BEST CASE project [NORTE-07-0124-FEDER-000056]
- Fundacao para a Ciencia e a Tecnologia (FCT)
- 7th Research and Technological Development (RTD) Framework Programme within the SuSTAINABLE project [308755]
- COMPETE Programme
- FCT [SMAGIS-PTDC/SEN-ENR/113094/2009, DYMONDS-CMU-PT/SIA/0043/2009]
The solar power penetration in distribution grids is growing fast during the last years, particularly at the low-voltage (LV) level, which introduces new challenges when operating distribution grids. Across the world, distribution system operators (DSO) are developing the smart grid concept, and one key tool for this new paradigm is solar power forecasting. This paper presents a new spatial-temporal forecasting method based on the vector autoregression framework, which combines observations of solar generation collected by smart meters and distribution transformer controllers. The scope is 6-h-ahead forecasts at the residential solar photovoltaic and medium-voltage (MV)/LV substation levels. This framework has been tested in the smart grid pilot of vora, Portugal, and using data from 44 microgeneration units and 10 MV/LV substations. A benchmark comparison was made with the autoregressive forecasting model (AR-univariate model) leading to an improvement on average between 8% and 10%.
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