Solar Irradiance Nowcasting System Trial and Evaluation for Islanded Microgrid Control Purposes

Remember Samu (), Satya Girdhar Bhujun, Martina Calais, Shafiullah Gm (), Moayed Moghbel, Md Asaduzzaman Shoeb and Bijan Nouri
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Remember Samu: Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Satya Girdhar Bhujun: Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Martina Calais: Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Shafiullah Gm: Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Moayed Moghbel: Australian Energy Market Operator, Level 45, 152 St. Georges Terrace, Perth, WA 6000, Australia
Md Asaduzzaman Shoeb: Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Bijan Nouri: German Aerospace Center (DLR), Institute of Solar Research, Ctra de Senes s/n km 4, 04200 Tabernas, Spain

Energies, 2022, vol. 15, issue 17, 1-21

Abstract: The rapid increase in solar photovoltaic (PV) integration into electricity networks introduces technical challenges due to varying PV outputs. Rapid ramp events due to cloud movements are of particular concern for the operation of remote islanded microgrids (IMGs) with high solar PV penetration. PV systems and optionally controllable distributed energy resources (DERs) in IMGs can be operated in an optimised way based on nowcasting (forecasting up to 60 min ahead). This study aims to evaluate the performance under Perth, Western Australian conditions, of an all-sky imager (ASI)-based nowcasting system, installed at Murdoch University in Perth, Western Australia (WA). Nowcast direct normal irradiance (DNI) and global horizontal irradiance (GHI) are inputted into a 5 kWp solar PV system with a direct current (DC) power rating/alternating current (AC) power rating ratio of 1.0. A newly developed classification method provided a simplified irradiance variability classification. The obtained nowcasting system evaluation results show that the nowcasting system’s accuracy decreases with an increase in lead time (LT). Additionally, the nowcasting system’s accuracy is higher when the weather is either mostly clear (with a recorded LT15 mean absolute deviation (MAD) of 0.38 kW) or overcast (with a recorded LT15 MAD of 0.19 kW) than when the weather is intermittently cloudy with varying cloud conditions (with a recorded LT15 MAD of 0.44 kW). With lower errors observed in lower LTs, overall, it might be possible to integrate the nowcasting system into the design of IMG controllers. The overall performance of the nowcasting system at Murdoch University was as expected as it is comparable to the previous evaluations in five other different sites, namely, PSA, La Africana, Evora, Oldenburg, and Julich.

Keywords: direct normal irradiance; global horizontal irradiance; nowcasting; solar photovoltaic; DigSILENT PowerFactory; irradiance variability classification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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