Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 14, Issue 1, Pages 537-549Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2022.3219347
Keywords
Dynamic programing; energy storage; optimal investment; stochastic and distributionally robust optimization
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In this paper, an optimal sizing model for a solar plus energy storage (PV-ESS) system for behind the meter applications is proposed. A dynamic optimization algorithm is presented to maximize the net worth of a project, considering decreasing technology costs in the future. The proposed model efficiently solves the optimization problem using parallel computation, and simulation results demonstrate its ability to minimize the total project cost.
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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