Optimal control strategy of NG piston engine as a DG unit obtained by an utilization of Artificial Neural Network

Milewski, Jarosław; Szabłowski, Łukasz; Kuta, J.

doi:10.1109/peam.2012.6612550

Cited by 4 publications

(1 citation statement)

References 33 publications

(29 reference statements)

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“…There are possibilities to use nonlinear functions with few variables in approximation, as well as the gradient-based and rapid calculation of ANN equations parameters. In the ANN method, there is an advantage over the analytical energy-balance procedure, [34][35][36] because the exact equations and physical parameters of the battery are no longer needed. Only the cause-effect relationships between the variables of the described model are necessary.…”

Section: Introductionmentioning

confidence: 99%

Comparison of hybrid recurrent neural networks and dual‐polarization models of valve regulated lead acid battery

et al. 2020

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Summary Distributed energy storage using low‐cost valve regulated lead acid (VRLA) batteries becomes a promising solution, especially in prosumer microinstallations. In herein work, the model‐based research of VRLA battery in pseudo‐random and hybrid power pulse cycles has been presented. The major goal of the article was to develop and compare parametric, analytical, and data‐driven models of the battery. There were chosen the dual polarization model and the hybrid recurrent neural network model based on long short‐term memory and nonlinear autoregressive with exogenous input model for estimating voltage values and determining nonmeasurable parameters of a VRLA battery for different values of the state of charge. Satisfactory results were obtained for both methods, with the favor of the dual polarization model. Finally, the advantages and disadvantages of both methods are discussed.

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Section: Introductionmentioning

confidence: 99%