Abstract
In this paper, we propose an optimal sizing model for a solar plus energy storage (PV-ESS) system for behind the meter applications. A dynamic optimization algorithm is proposed that maximizes the net worth of a project; the method can account for decreasing technology costs in the future and defer some of the investment costs. Two kinds of uncertainties are considered and mitigated according to their frequency of occurrence and forecast accuracy. The proposed optimization model is decomposed and structured in such a way that it can be efficiently solved using parallel computation. The simulation results provide evidence of the algorithm's ability to optimally size and time the investment in a PV-ESS system so that the total project cost is minimized.
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