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This research presents a 100% renewable energy (RE) scenario by 2050 with a high share of electric vehicles on the grid (V2G) developed in Ecuador with the support of the EnergyPLAN analysis tool. Hour-by-hour data iterations were performed to determine solutions among various features, including energy storage, V2G connections that spanned the distribution system, and long-term evaluation. The high participation in V2G connections keeps the electrical system available; meanwhile, the high proportions of variable renewable energy are the pillar of the joint electrical system. The layout of the sustainable mobility scenario and the high V2G participation maintain the balance of the electrical system during most of the day, simplifying the storage equipment requirements. Consequently, the influence of V2G systems on storage is a significant result that must be considered in the energy transition that Ecuador is developing in the long term. The stored electricity will not only serve as storage for future grid use. Additionally, the V2G batteries serve as a buffer between generation from diversified renewable sources and the end-use stage.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

Due to the increasing penetration of distributed generation and new high-power consumption loads - such as electric vehicles (EVs) - distribution system operators (DSO) are facing new grid security challenges. DSOs have historically dealt with such issues by making investments in grid reinforcement. However, an alternative solution, enabled by the expected roll-out of smart meters and high penetration of flexible loads, would be the increased use of flexibility services. Flexible loads, with EVs at their forefront, can modulate their consumption or even inject power back to the grid depending on current grid conditions. In return, flexibility provision should be remunerated accordingly. In this paper, the authors are interested in making an accurate description of the flexibility services at the distribution level which could be provided by EVs as well as their requirements, e.g. location, activation time and duration. Market design recommendations for enhancing the provision of DSO grid services by EVs are derived from the conducted analysis.

Electric vehicles are able to provide immediate power through the vehicle-to-grid function, and they can adjust their charging power level when in the grid-to-vehicle mode. This allows them to provide ancillary services such as frequency control. Their batteries differ from conventional energy storage systems in that the owner’s energy requirement constraint must be met when the vehicles participate in a frequency control system. An optimization problem was defined by considering both the owner satisfaction and frequency control performance. The main contribution of the proposed paper, compared to the literature, are (1) to keep the total available energy stored in the batteries connected to a charging station in an optimal region that favors the frequency regulation capability of the station and the proposed QoS and (2) to consider the optimal region bounded by the efficiency thresholds of the charger to allow for maximum regulation power. The problem is expressed as a multi-criteria optimization problem with time-dependent references. The paper presents an energy management strategy for frequency control, describes a concept of an optimal time-dependent state of charge for electric vehicle charging demands, and considers the power dependence of the electric vehicle charger efficiency. Finally, the simulation results are presented via Matlab/Simulink to prove the effectiveness of the proposed algorithm.

The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows better integration of EV bidirectional energy exchange, photovoltaic panels, and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of an envisaged EV service fleet for the Bari port authority.

The present study aims to evaluate the difference in the fluid-dynamic behavior of an overtopping wave energy converter under the incidence of irregular waves based on a realistic sea state when compared to the incidence of regular waves, representative of this sea state. Thus, the sea data of three regions from the Rio Grande do Sul coast, Brazil, were considered. Fluent software was employed for the computational modeling, which is based on the finite volume method (FVM). The numerical generation of waves occurred through the imposition of the velocity boundary conditions using transient discrete values through the WaveMIMO methodology. The volume of fluid (VOF) multiphase model was applied to treat the water–air interaction. The results for the water amount accumulated in the device reservoir showed that the fluid-dynamic behavior of the overtopping converter has significant differences when comparing the two proposed approaches. Differences up to 240% were found for the water mass accumulated in the overtopping device reservoir, showing evidence that the results can be overestimated when the overtopping device is analyzed under the incidence of the representative regular waves. Furthermore, for all studied cases, it was possible to approximate the water volume accumulated over time in the overtopping reservoir through a first-degree polynomial function.

Sensorless control of Electric Vehicle (EV) drives is considered to be an effective approach to improve system reliability and to reduce component costs. In this paper, relevant aspects relating to the sensorless operation of EVs are reported. As an initial contribution, a hybrid sensorless control algorithm is presented that is suitable for a variety of synchronous machines. The proposed method is simple to implement and its relatively low computational cost is a desirable feature for automotive microprocessors with limited computational capabilities. An experimental validation of the proposal is performed on a full-scale automotive grade platform housing a 51¿kW Permanent Magnet assisted Synchronous Reluctance Machine (PM-assisted SynRM). Due to the operational requirements of EVs, both the strategy presented in this paper and other hybrid sensorless control strategies rely on High Frequency Injection (HFI) techniques, to determine the rotor position at standstill and at low speeds. The introduction of additional high frequency perturbations increases the power losses, thereby reducing the overall efficiency of the drive. Hence, a second contribution of this work is a simulation platform for the characterization of power losses in both synchronous machines and a Voltage Source Inverters (VSI). Finally, as a third contribution and considering the central concerns of efficiency and autonomy in EV applications, the impact of power losses are analyzed. The operational requirements of High Frequency Injection (HFI) are experimentally obtained and, using state-of-the-art digital simulation, a detailed loss analysis is performed during real automotive driving cycles. Based on the results, practical considerations are presented in the conclusions relating to EV sensorless control. Peer Reviewed