Deployment of a battery energy storage system for the photovoltaic (PV) application has been increasing at a fast rate. Depending on the number of power conversion units and their type of connection, the PV-battery system can be classified into DC-and AC-coupled configurations. The number of the components and their electrical loading directly affects the reliability of each of the configurations. Hence, in order to assure high efficiency and lifetime of the PV-battery system, reliability assessment of power conversion units (representing the most reliability-critical system components) is necessary. With respect to that, in this paper, a reliability assessment of the PV-battery system is performed and a comparison of the DC-and AC-coupled configuration reliability is conducted. In the analysis, all parts of the power conversion system, i.e., DC/DC and DC/AC converter units, are taken into consideration and component-, converter-and system-level reliability is assessed. A case study of 6 kW PV system with integrated 3 kW/7.5 kWh battery system has shown that higher reliability is achieved for DC-coupled configuration. The obtained results indicate that the probability of failure for the 15% of the population for DC-coupled configuration occurs 7 years later than that is a case for AC-coupled configuration. Finally, the presented analysis can serve as a benchmark for lifetime and reliability assessment of power conversion units in PV-battery systems for both configuration types. It provides information about differences in electrical and thermal loading of the power conversion units and resulting reliability of the two configurations. Author Contributions: Conceptualization, M.S. and A.S.; Formal analysis, M.S.; Investigation, M.S.; Methodology, M.S. and A.S.; Software, M.S.; Supervision, A.S. and F.B.; Validation, A.S.; Visualization, M.S.; Writing-original draft, M.S.; Writing-review & editing, A.S. and F.B.

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This paper focuses on the sizing of a battery energy storage system providing frequency containment reserves in a power system with a large wind power penetration level. A three-stage sizing methodology including the different aspect of battery energy storage system performance is proposed. The first stage includes time-domain simulations, investigating battery energy storage system dynamic response and its capability of providing frequency reserves. The second stage involves lifetime investigation. An economic assessment of the battery unit is carried out by performing the last stage. The main outcome of the proposed methodology is to choose the suitable battery energy storage system size for providing frequency containment reserve from augmented wind power plants while fulfilling relevant evaluation criteria imposed for each stage.

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Energy storage systems (ESS) are being considered to overcome issues in modern grids, caused by increasing penetration of renewable generation. Nevertheless, integration of ESS should also be supplemented with an optimal energy management framework to ensure maximum benefits from ESS. Conventional energy management of battery, used with PV system, maximises self-consumption but does not mitigate grid congestion or address battery degradation. Model predictive control (MPC) can alleviate congestion and degradation while ensuring maximum self-consumption. Studies will be carried out to highlight the improvement with MPC based energy management over conventional method using simulations of oneyear system behaviour. As MPC uses forecast information in decision making, the impact of forecast uncertainties will be assessed and a method to address them through a constraint tightening will be presented.

To ensure optimal and economical battery operation, it is necessary to consider its lifetime-limiting aspects, e.g., performance degradation and degradation costs. Battery performance degradation is commonly assessed by offline lifetime models. They are suitable for battery planning and performance monitoring, but cannot be used in real-time operation. Therefore, in this letter, an incremental degradation cost estimation method for optimal battery real-time operation is proposed. It enables battery degradation evaluation for any time resolution and set of operating conditions during the real-time operation.

Increasing integration of photovoltaic (PV) system in electric grids cause congestion during peak power feed-in. Battery storage in PV systems increases self-consumption, for consumer's benefit. However with conventional maximising self consumption (MSC) control for battery scheduling, the issue of grid congestion is not addressed. The batteries tend to be fully charged early in the day and peak power is still fed-in to grid. This also increases battery degradation due to increased dwell time at high state of charge (SOC) levels. To address this issue, this work uses a model predictive control (MPC) for scheduling in PV system with battery storage to achieve multiple objectives of minimising battery degradation, grid congestion, while maximising self consumption. In order to demonstrate the improvement, this work compares the performances of MPC and MSC schemes when used in battery scheduling. The improvement is quantified through performance indices like self consumption ratio, peak power reduction and battery capacity fade for one-year operation. An analysis on computation burden and maximum deterioration in MPC performance under prediction error is also carried out. It is concluded that, compared to MSC, MPC achieves similar self consumption in PV systems while also reducing grid congestion and battery degradation.

To improve electric vehicle (EV) uptake, fast charging systems must be widely deployed. However, fast EV charging mission profiles expose power electronic components to extremely high-power stresses within short periods of time. Consequently, power electronic components in fast EV charging systems are expected to degrade/wear-out at a faster rate, requiring frequent replacement within the lifespan of the charging system. It is, therefore, important to both design and build fast EV charging systems with a known level of reliability. This paper proposes a model to investigate the reliability of fast EV charging systems. Using the model, the reliability of a typical fast EV charging system is analyzed, and results are presented to show how the lifetime and reliability of semiconductor switches used in fast EV charging systems can be predicted, even under widely varying mission profiles.