An optimal energy storage system (ESS) management procedure devoted to full renewable energy sources (RESs) exploitation is presented in this paper. It consists of an appropriate scheduling procedure and a real-time control strategy, which both aim to increase the RES penetration level as much as possible. In particular, the one-day-ahead scheduling procedure synthesizes the combined RES-ESS energy production profile with the aim of minimizing the RES energy production curtailments by means of ESS energy buffering. The real-time control strategy is developed in order to track the scheduled profile as well as possible by mitigating forecasting errors, thus improving RES reliability. The worth and effectiveness of the proposed management procedure is verified through a wide simulation study, which is carried out by means of the Matlab software package.

A novel online discrete-time parameter identification algorithm suitable for surface-mounted permanent magnet synchronous machines (SPMs) is presented in this paper. It is developed by means of the model reference adaptive system technique and the Popov Hyperstability Criterion in order to identify SPM discrete-time model parameters. In particular, good accuracy of discrete-time parameters is required by digital control systems, particularly by predictive control algorithms, which present a low robustness against parameter mismatches. Hence, an extensive simulation study is first carried out in the Matlab Simulink environment with the aim of testing the effectiveness and robustness of the proposed identification algorithm against inverter unidealities. Then, the proposed identification procedure is experimentally validated on a predictive controlled radial-flux SPM, driven by a field programmable gate arrays control board.

In this paper an analytical procedure for the preliminary design of a high-speed ferrite-based brushless dc machine (HS-BLDC) has been proposed. In particular, mechanical and electromagnetic modeling have been developed in order to take into account their mutual influence in the definition of the geometry of the electrical machine. In addition, suitable design targets have been imposed in accordance with electric vehicle application requirements. Hence, several mechanical and electromagnetic constraints have been introduced in order to comply with high-speed operation, preventing demagnetization issues of ferrite magnets as well. Subsequently, an HS-BLDC characterized by an inner rotor configuration has been designed in accordance with the proposed methodology. The analytical procedure and the corresponding results have been reported and validated by means of finite element analyses, highlighting the effectiveness of the proposed configuration and design solutions.

A model predictive control algorithm (MPC) suitable for Surface-Mounted Permanent Magnet Synchronous Machines (SPMs) is presented in this paper. It is based upon an accurate discrete-time model of the drive, accounting for both voltage saturation and current limitation constraints. It aims to properly manage these constraints in order to guarantee a good exploitation of both transient and steady state SPM performances, especially over flux-weakening operation. The effectiveness of the proposed MPC is first validated by a simulation study, in which the sensitivity of the proposed MPC against un-compensated inverter un-idealities and parameter uncertainties is properly highlighted and discussed, as well as the effects of sudden load torque variations. Then, an experimental study is performed on a radial-flux SPM driven by a Field Programmable Gate Arrays (FPGA) control board. The performances achievable by the proposed MPC are compared with those obtained by a conventional PI-based control system in order to highlight the improvements, especially regarding transient and flux-weakening operation.

A novel optimal power and energy management (OPEM) for centralized hybrid energy storage systems (HESS) in microgrids is presented in this paper. The proposed OPEM aims at providing multiple grid services by suitably exploiting the different power/energy features of electrochemical batteries (B) and supercapacitors (S). The first part of the paper focuses on the design and analysis of the proposed OPEM, by highlighting the advantages of employing hand-designed solutions based on Pontryagin’s minimum principle rather than resorting to pre-defined optimization tools. Particularly, the B power profile is synthesized optimally over a given time horizon in order to provide both peak shaving and reduced grid energy buffering, while S is employed in order to compensate for short-term forecasting errors and to prevent B from handling sudden and high-frequency power fluctuations. Both the B and S power profiles are computed in real-time in order to benefit from more accurate forecasting, as well as to support each other. Then, the effectiveness of the proposed OPEM is tested through numerical simulations, which have been carried out based on real data from the German island of Borkum. Particularly, an extensive and detailed performance analysis is performed by comparing OPEM with a frequency-based management strategy (FBM) in order to highlight the superior performance achievable by the proposed OPEM in terms of both power and energy management and HESS exploitation.