DC Optimal Power Flow Model to Assess the Irradiance Effect on the Sizing and Profitability of the PV-Battery System

Fernando García-Muñoz, Miguel Alfaro, Guillermo Fuertes and Manuel Vargas
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Fernando García-Muñoz: Industrial Engineering Department, University of Santiago de Chile, Avenida Ecuador 3769, Santiago 9170124, Chile
Miguel Alfaro: Industrial Engineering Department, University of Santiago de Chile, Avenida Ecuador 3769, Santiago 9170124, Chile
Guillermo Fuertes: Industrial Engineering Department, University of Santiago de Chile, Avenida Ecuador 3769, Santiago 9170124, Chile
Manuel Vargas: Industrial Engineering Department, University of Santiago de Chile, Avenida Ecuador 3769, Santiago 9170124, Chile

Energies, 2022, vol. 15, issue 12, 1-16

Abstract: The decreasing cost of renewable energy resources and the developments in storage system technologies over recent years have increased the penetration of photovoltaic systems to face the high rise in the electricity load. Likewise, there has also been an increase in the demand for tools that make this integration process in the current power systems profitable. This paper proposes a mathematical model based on the DC optimal power flow equations to find the optimal capacity of the PV panels and batteries for a standalone system or a system supported by the grid, while the investment and the energy required by the grid are minimized. In this regard, five different locations have been used as case studies to measure the influence of the irradiance level on the PV-Battery capacity installed and on the economic indicators such as CAPEX, OPEX, NPV, IRR, and the payback period. Thus, a modified 14-bus system has been used to replicate the grid technical limitations and show that a PV-Battery system connected to the grid could produce 26.9% more savings than a standalone PV-Battery and that a location with irradiance levels over 6.08 (kWh/m 2 /yr) could reduce the payback period for two years.

Keywords: distributed generation; energy storage systems; power system planning; renewable energy sources (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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