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• A cooperative control for the online energy management of a microgrid. • The methodology adopts the Lyapunov theorem encompassing the sensitivity theory. • It aims to ensure real-time power balance within the MG at minimal operating cost. • Simulations demonstrated the self-adaptability of the proposed controller. This paper develops a cooperative control methodology for the online energy management of grid-connected microgrids. The main aim of this methodology is to actively manage the active power outputs of all dispatchable energy sources available within the microgrid as well as the power exchanged with the utility grid so as to match the total load demand at the minimum operating cost. This implies to solve a constrained multi-objective dynamic optimization problem aimed at minimizing the total microgrid operating costs and ensuring the real-time balance within the microgrid in compliance with its technical-operational constraints. Lyapunov's theorem using sensitivity theory is adopted to solve this optimization. To test the performances of the proposed control methodology, several computer simulations corresponding to different operating scenarios have been conducted on the PrInCE Lab experimental microgrid built at the Polytechnic University of Bari. [Display omitted] [ABSTRACT FROM AUTHOR]

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]

This paper deals with the development of an on-line identification method for deriving simplified dynamic models. The practical applicability of the derived algorithm has been tested on the Capstone C30 microturbine installed at the Polytechnic University of Bari, Italy. For this purpose, a second order model has been identified by adopting the sensitivity theory involving the Lyapunov function giving rise to stable solutions in the on-line environment, renewing model parameters at every changes occurring on the physical system. This characteristic can be fruitfully adopted for implementing actual models in time domain simulators, giving rise to accurate results even if some internal parameters change. In order to investigate on the effectiveness of the proposed methodology in deriving a simplified dynamic model, several simulations and experimental tests were conducted in the Prince Lab of the Polytechnic University of Bari. The good agreement between simulations and laboratory tests confirm the validity and the applicability of the proposed methodology. [ABSTRACT FROM AUTHOR]

The aim of this paper is to define an organized approach for improving the economic, reliable and secure operation of microgrids operating either in the On-grid or in the Off-grid. According to this methodological approach, a microgrid can be operated into five Operating Modes and five Transitions. Proper management of each of them has been examined and implemented on the existing microgrid developed at the Prince — Electrical Energy System Lab of the Polytechnic of Bari. This microgrid can be considered a hard test bed for dynamic stability studies since it is an inertialess system. [ABSTRACT FROM AUTHOR]

Abstract: In this paper a novel methodology for evaluating the external equivalent model of a distributed network is presented. The proposed method is based on a non-linear parameter identification process which involves an artificial dynamic system, whose dynamics are explicitly designed to be stable by adopting the Lyapunov theory. This dynamic identification method is competitive with existing reduction methods, since it does not require system linearization or any a priori information about the system under study. Few measurements at boundary nodes are required to obtain the essential information regarding the external system. Even if these measurements are strongly corrupted by noise, the algorithm is quite insensible to it. Due to its ability to be auto-adaptive at any changes in the system operating conditions and to its great speed convergence, the identification procedure can be usefully applied for real-time applications. [Copyright &y& Elsevier]