Probabilistic methodology for estimating the optimal photovoltaic capacity in distribution systems to avoid power flow reversals

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Abstract

The large-scale integration of photovoltaic generation (PVG) on distribution systems (DSs) preserving their technical constraints related to voltage fluctuations and active power (AP) flow is a challenging problem. Solar resources are accompanied by uncertainty regarding their estimation and intrinsically variable nature. This study presents a new probabilistic methodology based on quasi-static time-series analysis combined with the golden section search algorithm to integrate low and high levels of PVG into DSs to prevent AP flow in reverse direction. Based on the analysis of two illustrative case studies, it was concluded that the successful integration of PVG is not only related to the photovoltaic-cell manufacturing prices and conversion efficiency but also with the manufacturing prices of power electronic devices required for reactive power control.

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Lujano-Rojas, J. M., Dufo-López, R., Bernal-Agustín, J. L., Domínguez-Navarro, J. A., & Catalaõ, J. P. S. (2018). Probabilistic methodology for estimating the optimal photovoltaic capacity in distribution systems to avoid power flow reversals. IET Renewable Power Generation, 12(9), 1045–1064. https://doi.org/10.1049/iet-rpg.2017.0777

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