Data Post-Processing strategies for the application of short-term PV forecasting in microgrids

Jamal, T. and Shahnia, F.ORCID: 0000-0002-8434-0525 (2019) Data Post-Processing strategies for the application of short-term PV forecasting in microgrids. In: 9th International Conference on Power and Energy Systems (ICPES) 2019, 10 - 12 December 2019, Perth, WA

Abstract

It is essential to eliminate the uncertainties in the variability of the output power of the solar photovoltaics (PV) as much as possible to improve the penetration level of such systems in microgrids. Hence, employing PV forecasting tools can be very helpful in this aspect. This paper has used a battery energy storage system and short-term PV forecasting together to assess the potential of fuel-saving in diesel generator-PV-battery hybrid microgrids. An innovative framework has been proposed to address the problems of forecast error for short-time horizon, realizing the persistence of the forecast's performance variation for various sky and cloud conditions throughout the year. This approach helps to build a confidence level for utilizing the PV forecast method as short as 1-min ahead. The studies have shown that PV forecasting mechanism yields in promising results when innovative strategies comprising of the post-processing of forecast data is effectively utilized.

Item Type:	Conference Paper
Murdoch Affiliation(s):	Engineering and Energy
URI:	http://researchrepository.murdoch.edu.au/id/eprint/56617

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