This paper presents a method for achieving individual electrochemical cell balancing by using a cascaded full bridge multilevel converter where a single electrochemical cell is connected to each converter module. As a result, balancing at cell level is possible without additional circuitry, making this topology ideal for long service life grid storage and applications using second-life cells where the cells are inherently poorly matched. In order to estimate the relative state of charge between cells, the control flexibility of the multilevel converter is used to remove each cell from the current path without interrupting the operation of the system. This process eliminates the effect of the internal cell resistance and fast transient electrochemical phenomena and therefore the measured voltage serves as a high quality 'pseudo open circuit' voltage measurement. The proposed balancing strategy is validated using a 25 level cascaded full bridge multilevel converter prototype for the individual balancing of twelve lithium polymer cells, during consecutive charging and discharging cycles. Successful balancing to within 5 mV of open circuit voltage is observed between cells with 45% difference in nominal capacity and 55% initial state of charge variation.

This paper presents a method for evaluating gridconnected Battery Energy Storage System (BESS) designs. The steady-state power losses of the grid interface converter, the battery pack and the balancing circuit are calculated. The reliability of each complete system is calculated using a Markovbased modelling approach that takes into account the built-in redundancy of the system as well as performance degradation caused by faults. Finally, a simple economic analysis based on capital cost and efficiency is used to provide a basis for direct comparison between competing system designs. Three design options for a 1 MW, 1 MWh BESS connected at 11 kV are compared: a conventional BESS using parallel low-voltage power blocks, a BESS using a high-voltage intelligent battery pack and a BESS using a cascaded H-bridge converter. The results of the analysis indicate that additional power electronics included in the battery pack as part of the intelligent battery pack and H-bridge designs can enhance the reliability of the BESS by an order of magnitude under typical conditions, without increasing the overall cost of the system.

© 2015 The Authors.This paper presents an integrated modelling methodology which includes reduced-order models of a lithium ion battery and a power electronic converter, connected to a 35-bus distribution network model. The literature contains many examples of isolated modelling of individual energy storage mediums, power electronic interfaces and control algorithms for energy storage. However, when assessing the performance of a complete energy storage system, the interaction between components gives rise to a range of phenomena that are difficult to quantify if studied in isolation. This paper proposes an integrated electro-thermo-chemical modelling methodology that seeks to address this problem directly by integrating reduced-order models of battery cell chemistry, power electronic circuits and grid operation into a computationally efficient framework. The framework is capable of simulation speeds over 100 times faster than real-time and captures phenomena typically not observed in simpler battery and power converter models or non-integrated frameworks. All simulations are performed using real system load profiles recorded in the United Kingdom. To illustrate the advantages inherent in such a modelling approach, two specific interconnected effects are investigated: the effect of the choice of battery float state-of-charge on overall system efficiency and the rate of battery degradation (capacity/power fade). Higher state-of-charge operation offers improved efficiency due to lower polarisation losses of the battery and lower losses in the converter, however, an increase in the rate of battery degradation is observed due to the accelerated growth of the solid-electrolyte interphase layer. We demonstrate that grid control objectives can be met in several different ways, but that the choices made can result in a substantial improvement in system roundtrip efficiency, with up to a 43% reduction in losses, or reduction in battery degradation by a factor of two, depending on battery system use case

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The loss of wetlands and semi-natural grasslands throughout much of Europe has led to a historic decline of species associated with these habitats. The reinstatement of these habitats, however, requires spatially explicit predictions of the most suitable sites for restoration, to maximize the ecological benefit per unit effort. One species that demonstrates such declines is the white stork Ciconia ciconia, and the restoration of habitat for this flagship species is likely to benefit a suite of other wetland and grassland biota. Storks are also being reintroduced into southern Sweden and elsewhere, and the a priori identification of suitable sites for reintroduction will greatly improve the success of such programmes. Here a simple predictive habitat-use model was developed, where only a small but reliable presence-only dataset was available. The model is based on the extent and relative soil moisture of semi-natural pastures, the extent of wetlands and the extent of hayfields in southern Sweden. Here the model was used to predict the current extent of stork habitat that is suitable for successful breeding, and the extent of habitat that would become suitable with moderate habitat restoration. The habitat model identifies all 10 occupied nesting sites where breeding is currently successful. It also identifies $300 km 2 of habitat that is predicted to be suitable stork habitat, but that is presently unused; these sites were identified as potential areas for stork reintroduction. The model also identifies over 100 areas where moderate habitat restoration is predicted to have a disproportionate effect (relative to the restoration effort) on the area of suitable habitat for storks; these sites were identified as priorities for habitat restoration. By identifying areas for reintroduction and restoration, such habitat suitability models have the potential to maximize the effectiveness of such conservation programmes.

Recent advances in quantum key distribution (QKD) have given rise to systems that operate at transmission periods significantly shorter than the dead times of their component singlephoton detectors. As systems continue to increase in transmission rate, security concerns associated with detector dead times can limit the production rate of sifted bits. We present a model of high-speed QKD in this limit that identifies an optimum transmission rate for a system with given link loss and detector response characteristics.

Ampere-hour (Ah) efficiency: The quantity of electricity measured in Ampere-hours which may be delivered by a cell or battery under specified conditions. Ampere-hour capacity: The total number of Ampere-hours or watt-hours that can be withdrawn from a fully charged cell, indicated by Ah or mAh. Battery: Two or more electrochemical cells connected together electrically in series, parallel, or both, to provide the required operating voltage and current levels. Crate: Charge or discharge current, in Ampere, expressed in multiples of the rated capacity. For example, C/10 charge current for a cell rated at 20 Ah is: 20 Ah/10 = 2 A. Capacity: See Ampere-hour capacity. Cell: The smallest electrochemical unit of a battery used to generate or store electrical energy. Coulombic efficiency: See Ampere-hour efficiency. Cutoff voltage: The cell voltage at which the discharge process is terminated (it is generally a function of discharge rate). Cycle life: The number of times a cell can be discharged and recharged until the cell capacity drops to a specified minimum value usually 80 % of rated capacity. Depth of discharge: The quantity of electricity (Ampere-hours) removed from a fully charged cell, expressed as a percentage of its rated Ampere-hour capacity. Energy density: The ratio of the energy available from a cell to its volume (Wh/L) or mass (Wh/kg). xxi Internal resistance: Expressed in ohms, the total DC resistance to the flow of current through internal components (grids, active materials, separators, electrolyte, straps, and terminal) of a cell. Module: The smallest modular unit, consisting of a number of individual cells connected together electrically in series, parallel, or both. Nominal voltage: The average voltage of the cell. The operating voltage of the system may go above or below this value. Open circuit voltage (OCV): The difference in potential between the terminals of a cell when no load is applied. Pack: Two or more modules connected in series, parallel or both. Power density: The ratio of the available power from a cell to its volume (W / L). Round-trip efficiency: The ratio of energy put in (in MWh) to energy retrieved from storage (in MWh). Self-discharge: The loss of useful capacity of a cell on storage due to internal chemical action (local action) and parasitic currents. State-of-charge (SoC): The present cell capacity in relation to maximum capacity. Terminal voltage: The difference in potential between the terminals of a cell when a load is applied.

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