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This paper presents experimental investigations into a hybrid energy storage system comprising directly parallel connected lead-acid and lithium batteries. This is achieved by the charge and discharge cycling of five hybrid battery configurations at rates of 0.2–1C, with a 10–50% depth of discharge (DoD) at 24 V and one at 48 V. The resulting data include the overall round-trip efficiency, transient currents, energy transfers between the strings, and the amount of energy discharged by each string across all systems. The general observation is that the round-trip efficiency drops from a maximum of around 94–95% in the first stages of the charge/discharge process, when only the Li-ion strings are active, to around 82–90% when the lead-acid strings reach a DoD of up to 50%. The most important parameters in the round-trip efficiency function are the ratio between the Li-ion and lead-acid energy available and the charge/discharge current. The energy transfer between the strings, caused by the transient currents, is negligible in the first stages of the discharge and then grows, with the DoD peaking at around 60% DoD. Finally, during the first stage of discharge, when only the Li-ion strings are active, the amount of energy discharged varies with the discharge C rate, decreasing to almost half at between 0.2 and 1C.

The current study investigates public intentions to use an innovative, off-grid renewably powered EV charging technology called FEVER (Future Electric Vehicle Energy networks supporting Renewables). We report the findings of a questionnaire-based survey (QBS) conducted at a zoo in the south of England, exploring the prospect of demonstrating FEVER. The QBS was designed around a context-specific technology acceptance model (TAM) and administered both face-to-face (n = 63) and online (n = 158) from April to May 2023. The results indicate that most participants were willing to pay to use FEVER, particularly where revenue would benefit the zoo. The participants agreed they intended to use the chargers, and that they would be useful and easy to use. The participants agreed that there would be normative pressure to use the chargers, but that their use would be enjoyable. Of greatest concern was that the chargers would be blocked by others. The participants were ambivalent about concerns over charging duration and charge sufficiency. Structural equation modelling confirmed that the context-specific TAM explained 58% of people’s use intentions. The core relationships of the TAM were confirmed, with ‘perceived usefulness’ additionally predicted by subjective norms and ‘perceived ease of use’ additionally predicted by anticipated enjoyment. Of the other variables, only concern that the chargers would be blocked was retained as a marginal predictor of ‘perceived ease of use’. The implications of these findings for the co-design and demonstration of FEVER are discussed.

This paper presents a capacity planning framework for a microgrid based on renewable energy sources and supported by a hybrid battery energy storage system which is composed of three different battery types, including lithium-ion (Li-ion), lead acid (LA), and second-life Li-ion batteries for supplying electric vehicle (EV) charging stations. The objective of this framework is to determine the optimal size for the wind generation systems, PV generation systems, and hybrid battery energy storage systems (HBESS) with the least cost. The framework is formulated as a mixed integer linear programming (MILP) problem, which incorporates constraints for battery ageing and the amount of unmet load for each year. The system uncertainties are managed by conducting the studies for various scenarios, generated and reduced by generative adversarial networks (GAN) and the k-means clustering algorithm for wind speed, global horizontal irradiation, and EV charging load. The studies are conducted for three levels of unmet load, and the outputs are compared for these reliability levels. The results indicate that the cost of hybrid energy storage is lower than individual battery technologies (21% compared to Li-ion, 4.6% compared to LA, and 6% compared to second-life Li-ion batteries). Additionally, by using HBESS, the capacity fade of LA batteries is decreased (for the unmet load levels of 0, 1%, 5%, 4.2%, 6.1%, and 9.7%, respectively), and the replacement of the system is deferred proportional to the degradation reduction.

In this paper, an optimisation framework is presented for planning a stand-alone microgrid for supplying EV charging (EVC) stations as a design and modelling approach for the FEVER (future electric vehicle energy networks supporting renewables) project. The main problem of the microgrid capacity sizing is making a compromise between the planning cost and providing the EV charging load with a renewable generation-based system. Hence, obtaining the optimal capacity for the microgrid components in order to acquire the desired level of reliability at minimum cost can be challenging. The proposed planning scheme specifies the size of the renewable generation and battery energy storage systems not only to maintain the generation–load balance but also to minimise the capital cost (CAPEX) and operational expenditures (OPEX). To study the impact of renewable generation and EV charging uncertainties, the information gap decision theory (IGDT) is used to include risk-averse (RA) and opportunity-seeking (OS) strategies in the planning optimisation framework. The simulations indicate that the planning scheme can acquire the global optimal solution for the capacity of each element and for a certain level of reliability or obtain the global optimal level of reliability in addition to the capacities to maximise the net present value (NPV) of the system. The total planning cost changes in the range of GBP 79,773 to GBP 131,428 when the expected energy not supplied (EENS) changes in the interval of 10 to 1%. The optimiser plans PV generation systems in the interval of 50 to 63 kW and battery energy storage system in the interval of 130 to 280 kWh and with trivial capacities of wind turbine generation. The results also show that by increasing the total cost according to an uncertainty budget, the uncertainties caused by EV charging load and PV generation can be managed according to a robustness radius. Furthermore, by adopting an opportunity-seeking strategy, the total planning cost can be decreased proportional to the variations in these uncertain parameters within an opportuneness radius.

The storage capacity of the batteries in an electric vehicle (EV) could be utilised to store electrical energy and give it back to the grid when needed by participating in vehicle to grid (V2G) schemes. This participation could be a source of revenue for vehicle owners thus reducing the total charging cost of their EVs. A V2G simulator has been developed using MATLAB to find out the potential cost saving from participation of EVs in V2G schemes. A standard IEEE30 network has been modelled in the simulator which uses the MATPOWER engine to undertake power flow analysis. A novel control algorithm has been developed to take advantage of the difference between the selling and buying electricity prices by charging and discharging EVs at the appropriate time. Two scenarios are simulated to compare the total charging cost of EVs with or without the utilisation of V2G technology within the power system assuming a total of 5000 EVs. The results of the simulation show that the applied control strategy with V2G is able to reduce the charging cost of EVs by 13.6 % while satisfying the minimum requirement for state of charge (SoC) of the EV batteries to complete their next journey.

This paper presents both the techno-economic planning and a comprehensive sensitivity analysis of an off-grid fully renewable energy-based microgrid (MG) intended to be used as an electric vehicle (EV) charging station. Different possible plans are compared using technical, economic, and techno-economic characteristics for different numbers of wind turbines and solar panels, and both single and hybrid energy storage systems (ESSs) composed of new Li-ion, second-life Li-ion, and new lead–acid batteries. A modified cost of energy (MCOE) index including EVs’ unmet energy penalties and present values of ESSs is proposed, which can combine both important technical and economic criteria together to enable a techno-economic decision to be made. Bi-objective and multi-objective decision-making are provided using the MCOE, total met load, and total costs in which different plans are introduced as the best plans from different aspects. The number of wind turbines and solar panels required for the case study is obtained with respect to the ESS capacity using weather data and assuming EV demand according to the EV population data, which can be generalized to other case studies according to the presented modelling. Through studies on hybrid-ESS-supported MGs, the impact of two different global energy management systems (EMSs) on techno-economic characteristics is investigated, including a power-sharing-based and a priority-based EMS. Single Li-ion battery ESSs in both forms, new and second-life, show the best plans according to the MCOE and total met load; however, the second-life Li-ion shows lower total costs. The hybrid ESSs of both the new and second-life Li-ion battery ESSs show the advantages of both the new and second-life types, i.e., deeper depths of discharge and cheaper plans.

The potential for low cost, environmentally friendly and high rate energy storage has led to the study of anatase-TiO2 as an electrode material in aqueous Al3+ electrolytes. This paper describes the improved performance from an electrochemically treated composite TiO2 electrode for use in aqueous Al-ion batteries. After application of the cathodic electrochemical treatment in 1 mol/dm3 KOH, Mott–Schottky analysis showed the treated electrode as having an increased electron density and an altered open circuit potential, which remained stable throughout cycling. The cathodic treatment also resulted in a change in colour of TiO2. Treated-TiO2 demonstrated improved capacity, coulombic efficiency and stability when galvanostatically cycled in 1 mol·dm−3AlCl3/1 mol·dm−3 KCl. A treated-TiO2 electrode produced a capacity of 15.3 mA·h·g−1 with 99.95% coulombic efficiency at the high specific current of 10 A/g. Additionally, X-ray diffraction, scanning electron microscopy and X-ray photoelectron spectroscopy were employed to elucidate the origin of this improved performance.

Controlling the frequency of power systems with high wind power penetration is more difficult due to the high variability of the wind power. One possible mainstream energy carrier in the future, particularly for the transportation sector, is Hydrogen, and water electrolysis is one of the most attractive ways to produce it. In this study, a detailed model of a steam turbine generator has been produced in MATLAB Simulink and used to investigate a scenario in which there is a 25% penetration of wind power. To improve the frequency stability of the power system, large scale alkaline electrolysers used in future Hydrogen filling stations could adjust their load with respect to the frequency deviation from nominal and can significantly reduce fluctuations in system frequency. For the case examined, five times less spinning reserve is required in order to maintain the power system frequency within operational limits when electrolysers are utilised as a form of demand side management (DSM), compared to the base case where no electrolyser DSM plant is available. Actual operational data from a pressurised alkaline electrolyser is used to evidence the fast load changing capability of such electrolysers.

Solidity (σ) is a critical design parameter for vertical-axis wind turbines (VAWTs), influencing its performance across various operational conditions. This study examines the impact of solidity on VAWT performance through a series of experimental investigations. Consensus points to lower solidity for high tip speed ratio (TSR) and higher solidity for lower TSR conditions. As turbine solidity increases, both torque and power generation improve, alongside enhanced self-starting capabilities. However, exceeding optimal solidity results in significant performance degradation, with the coefficient of performance (CP) dropping by 96.5% between solidities of 0.500 and 1.000. Furthermore, the maximal rotational speed decreased by 162 RPM from a solidity of 0.375 to 1.000. This study also highlights the limitation of solidity of vertical axis wind turbines at low TSRs, underscoring the importance of optimizing solidity to balance lift forces and maintain efficient energy conversion. These findings provide valuable insights for the design and optimization of VAWTs to enhance their efficiency and operational range.

A transformer-less Buck-Boost direct current–direct current (DC–DC) converter in use for the fast charge of electric vehicles, based on powerful high-voltage isolated gate bipolar transistor (IGBT) modules is analyzed, designed and experimentally verified. The main advantages of this topology are: simple structure on the converter’s power stage; a wide range of the output voltage, capable of supporting contemporary vehicles’ on-board battery packs; efficiency; and power density accepted to be high enough for such a class of hard-switched converters. A precise estimation of the loss, dissipated in the converter’s basic modes of operation Buck, Boost, and Buck-Boost is presented. The analysis shows an approach of loss minimization, based on switching frequency reduction during the Buck-Boost operation mode. Such a technique guarantees stable thermal characteristics during the entire operation, i.e., battery charge cycle. As the Buck-Boost mode takes place when Buck and Boost modes cannot support the output voltage, operating as a combination of them, it can be considered as critically dependent on the characteristics of the semiconductors. With this, the necessary duty cycle and voltage range, determined with respect to the input-output voltages and power losses, require an additional study to be conducted. Additionally, the tolerance of the applied switching frequencies for the most versatile silicon-based powerful IGBT modules is analyzed and experimentally verified. Finally, several important characteristics, such as transients during switch-on and switch-off, IGBTs’ voltage tails, critical duty cycles, etc., are depicted experimentally with oscillograms, obtained by an experimental model.