Optimal replacement strategy for residential solar panels using monte carlo simulations and nonlinear optimization methods
Optimal replacement strategy for residential solar panels using monte carlo simulations and nonlinear optimization methods
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Date
2017-05
Authors
Poissant, Andrew
Advisor
Adomaitis, Raymond
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Abstract
The purpose of this analysis is to determine the optimal replacement strategy for a residential
photovoltaic (PV) array. Specifically, the optimal year and number of solar modules that should
be replaced on a residential solar panel system. This analysis aims at saving the stakeholder,
a homeowner with a residential PV array, money. A Monte Carlo simulation and nonlinear
mixed-integer programming are the analytic techniques used in determining the replacement
strategy. Localized cost of electricity (LCOE) is the objective function in these analyses. Modular, environmental, and market factors are all variables that can affect the LCOE. University
of Maryland’s LEAFHouse was the basis of these analyses because it is a house equipped with
an aging PV array and readily accessible data. Based on the findings in this report, it was
determined that 0 ± 0 solar modules should be replaced after 1.42 ± 0.32 years with a reference
year of initial installation being 2007. While the analysis results were not expected, they were
proven to be reasonable based on cost trends for solar panels and the calculated monetary value of the power production lost from the PV array.