The lifetime of a battery pack consisting of many cells in series is determined by the weakest cell. Heterogeneous degradation of the battery cell, as a result of inherent discrepancy between cells, accelerates the aging of the weakest cell, which cannot be overcome by conventional passive and active balancing techniques. Therefore, this paper presents a methodology for charging series-reconfigurable Lithium-ion battery packs. To mitigate the negative effects of unregulated temperature increases, thermal gradients, state-of-charge imbalances, and other cell-tocell variations, we formulate and evaluate a charging strategy that addresses temperature and charge homogenization and temperature tracking. Model Predictive Control (MPC) was used to optimally homogenize the charge and temperature in the reconfigurable battery. Comparative simulations were carried out on the passive and the proposed reconfigurable battery, showing the superior perormance of reconfigurable battery dealing with battery cells with different aging conditions. Moreover, the scalability of the proposed method is verified on a string of 100 serial cells with low computational time. Finally experiments were conducted for four different case studies to verify the proposed MPC-based charge and temperature homogenization and control.

Motivated by recent advances in industrial data communications, MW-class PV parks are increasingly utilizing communication-based coordination among different power converters to achieve accurate voltage regulation and stability, particularly during grid events. However, communication delays present in data transfer networks reduce coordination quality and deteriorate the ability of the PV park to respond in a timely manner. This paper investigates the impact of such delays on the voltage recovery performance of grid-tied converters in a PV park, coordinated by a centralized secondary voltage controller (SecVC), under different grid and delay conditions. In addition, to enhance the coordination quality, a local strategy for the converter-level controller is proposed to reduce the control sensitivity to the communication delays. The theoretical results obtained from nonlinear model and Monte-Carlo analysis are validated using a real communication setup between two Hardware-in-the-Loop devices (HIL), interfaced through a communication network emulator using the Modbus-TCP protocol.

During fast charging of Lithium-Ion batteries (LIB), cell overheating and overvoltage increase safety risks and lead to faster battery deterioration. Moreover, in conventional Battery Management Systems (BMS), the cell balancing, charging strategy and thermal regulation are treated separately at the expense of faster cell deterioration. Hence, this paper proposes an optimized fast charging and balancing strategy with electrothermal regulation of LIB packs. Thereby, the power dissipation constraints of the passive balancing are introduced in the proposed integrated optimal framework and cell balancing is achieved by bypassing the extra charging current. The electrothermal model of the cells, along with a battery pack formed by a string of cells, is implemented. Extensive experiments are carried out to identify the coefficients for the Lithium-Ion cell model, i.e. Samsung-INR18650-20R, and the charging current trajectory as well as the balancing signals are generated with Model Predictive Control (MPC). The pack level simulations and experiments show that the proposed algorithm maintains the electro-thermal boundaries throughout the charging process, increasing the safe charge acceptance of the battery pack.

Stability analysis of power electronics-dominated grids is challenging due to the need of manufacturers to protect the intellectual property of converters control systems. Black-box dq impedance models have been proposed to overcome this challenge in grid stability analysis. However, such models are limited to small-signal analyses and are accurate only around a predefined and pre-computed equilibrium point. Conversely, the recently proposed nonlinear Differential-Algebraic Equations (DAE) models of converter-dominated grids can be used for stability analyses in every operating conditions and additionally for generalized power flow analysis and transient time-domain simulations. Despite these advantages, nonlinear state-space converters models require the full knowledge of their control system. To overcome this limitation, this paper proposes a nonlinear grey-box modeling strategy which uses structured perturbations to represent the converters’ control system uncertainties. The stability boundaries and control loops sensitivity are analyzed in a multi-vendor converter-dominated grid at different operating points through robust control theory. Hardware-In-the-Loop results are provided.

Grid forming converters can offer fast voltage support during grid disturbances through a prompt injection of reactive current. Nevertheless, the large overcurrents experienced during grid faults can trigger the converter current limiter, which is often responsible of transient instability problems. While over-dimensioning the power rating of the converter enhances its grid supporting capabilities, it significantly increases the costs. Online monitoring of the semiconductor junction temperature, instead, enables the converter to perform a safe over-current operation for a limited time interval, potentially improving the transient stability without converter overdimensioning. Nevertheless, the transient stability analysis and current limitation design considering thermal dynamics is very challenging due to the high order of the model, which makes conventional methodologies based on second-order models not applicable. This article proposes a temperaturedependent current limitation in grid-forming converters, enabling overcurrent operation and significantly improving transient stability. A methodology for transient stability analysis is proposed based on numerical methods applied to the nonlinear state-space model of the converter under thermally stressed conditions during over-current scenarios caused by grid faults. The proposed method is implemented in a simulation of a grid-forming medium voltage Modular Multilevel Converter (MMC) considering the dynamics of junction temperatures.

Stability of multi-vendor power electronics-dominated grids requires proper specifications for converters interoperability, e.g. tuning boundaries for the converters' control loops to be respected by all vendors. The confidentiality and variety of implementation of the converters' control system by different vendors and the nonlinear dynamics of power converters make this task arduous. This paper formulates this research question as a robust stability problem, embedding frequency-dependent uncertainties in the converter control systems and analytically quantifying the amount of uncertainty able to warranty the power grid stability. Grid following converters are considered and modeled with a nonlinear grey-box approach, in contrast with conventional small-signal black-box models which suffer from inaccuracy when their operating point deviates from the nominal one. This paper also demonstrates both analytically and with Hardware-In-the-Loop (HIL) experiments that different converters operating points (e.g. active power injections, ac bus voltages) radically affect their stability, empathizing the necessity of nonlinear converters models to realize accurate power grid stability analyses.