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Highlights • Proposes a second-order dynamic model to represent an actual So–Nick BESS. • An input–output identification procedure is proposed for parameters identification. • The procedure is based on the Sensitivity theory involving the Lyapunov function. • Experimental tests prove the practical applicability of the proposed methodology. Abstract The aim of this paper is to derive an accurate input/output dynamic equivalent model of a So–Nick Battery Energy Storage System (BESS). For this purpose, an on-line identification methodology has been applied. By this methodology, unknown model parameters are identified in the continuous time domain by solving an optimization problem aimed at minimizing the error between output trajectories of the physical system and its dynamic equivalent model. The methodology is based on the Sensitivity theory involving the Lyapunov function, ensuring the stability of the algorithm. Experimental results are used to validate the proposed approach by adopting the Sodium–Nickel Battery Energy Storage System (BESS) embedded into the experimental Prince Lab of the Polytechnic University of Bari, Italy. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes an auto-adaptive controller that enables to suitably manage the reactive power supplied by the inverters of PV units whishing to provide the reactive power ancillary service on the base of standard needs or on a voluntary basis. The derived controller is based on an optimization procedure involving the sensitivity theory in conjunction with the Lyapunov function and provides control laws feeding the inverters of the PV units. The controller promptly minimizes system losses preserving the active power produced by the PV plants against the reactive one. In fact, when the PV modules do not get enough sunlight to generate active power, the proposed procedure forces the PV inverters to provide a reactive power equal to the rated power. On the contrary, in order to preserve the major economic benefits for the investor deriving from the produced active power during the sunlight hours, the method automatically reduces the injection of reactive power. The computer simulations, performed on a distribution system, demonstrate that the controller is capable to control the network in the real-time, mainly due to its ability to be auto-adaptive at any changes in the system operating conditions. [Copyright &y& Elsevier]