Document Type

Journal Article

Publication Title







School of Science / School of Engineering




Edith Cowan University

ECU-HEC joint scholarship


Hassan, A., Al-Abdeli, Y. M., Masek, M., & Bass, O. (2022). Optimal sizing and energy scheduling of grid-supplemented solar PV systems with battery storage: Sensitivity of reliability and financial constraints. Energy, 238(Part A), article 121780.


Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay between the level of reliability (LPSP), financial constraints, and CO2 emissions. This paper investigates the impact of these factors on stand-alone (SA) and grid-supplemented (GS) solar PV systems over multiple seasons. The research uses established hardware models, detailed power management strategies as well as realistic Australian grid tariffs and Genetic Algorithms to find the minimum Cost of Energy (COE) subject to LPSP and financial constraints. The developed power management strategies are also tested experimentally on a real solar PV system. The results indicate that the grid-supplemented system yields 30% lower COE compared to the stand-alone at baseline (LPSP<0.01) but achieves this at the expense of 17% higher life cycle emissions (LCE, kgCO2-eq/kWh). The results also revealed that in the grid-supplemented systems, only optimum renewable to grid penetration ratios can yield minimum COE which were found to be 95% and 5% respectively in this case study. A typical increase in the COE with tighter LPSP is found for the stand-alone systems. Whilst in the grid-supplemented systems, higher system's reliability can be achieved at almost the same COE but with increased emissions. In terms of tariff structures, the time of use tariff structure offers a marginally lower COE (0.30$/kWh) compared to the anytime flat tariff (COE = 0.32$/kWh), but with the latter outperforming in terms of LCE. The analyses presented help identifying the parameters to be considered in establishing more cost-effective solar PV systems.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.