Development of a Control Strategy for Islanded Remote Hybrid Microgrids Integrating Nowcasting

Remember Samu

The integration of solar photovoltaic (PV) technology into electricity networks presents technical challenges due to varying PV output. Of particular concern are power ramp events caused by cloud movements, especially for islanded remote hybrid microgrids (RHMGs) with high PV penetration. In such systems, the fluctuation of PV power output during scattered cloud conditions can be significant, requiring a high spinning reserve (SR) to cover for drops in PV power. This results in increased consumption of diesel fuel and operation costs. To address this issue, a control strategy incorporating nowcasting is proposed to reduce the SR and the amount of consumed diesel fuel. An international survey was conducted, indicating that the use of nowcasting tools in RHMG operations is still limited. However, the survey recognised the possibility of reducing SR and increasing PV penetration levels in RHMGs by incorporating nowcasting tools. To test the applicability of nowcasting in RHMGs, an all-sky imager (ASI)-based solar irradiance nowcasting system (SINS) was installed, trialled, and evaluated at Murdoch University in Perth, Western Australia. A new solar irradiance classification method was developed to provide a simplified classification of irradiance variability. With low errors observed in lower lead times (LTs), in all variability classes, the integration of nowcasting into the control of RHMGs was anticipated to provide benefits. A control strategy was developed using nowcast data and coded in the DigSILENT Programming Language (DPL). Nonetheless, like any forecasts, nowcast data exhibited errors and these were also incorporated into the analysis. The strategy was applied to an RHMG comprising 2.3MW controllable PV (later increased to 3.6MW) and up to five 1.6MW diesel generators with a constant system load of 3.6MW. The RHMG was simulated using DigSILENT PowerFactory (PF) simulation software. The developed control strategy was compared against the existing control strategy for three irradiance variability classes namely intermittently cloudy, mostly clear sky and overcast, resulting in an average fuel consumption reduction of 20% over a 10-hour simulation period for the 2.3MW PV penetration case. Furthermore, a novel PV curtailment methodology was developed and applied to allow an increase in PV penetration without violating SR constraints. This increase in PV penetration resulted in an average fuel consumption reduction of 12% for the same simulation period, compared to the modified existing strategy which allowed curtailment. The developed control strategy was evaluated using results from a simulation of an actual RHMG with diesel generators, PV, and irradiance data, and the findings are expected to be transferrable to similar RHMGs.

Development of a Control Strategy for Islanded Remote Hybrid Microgrids Integrating Nowcasting

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