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The development of public charging infrastructure is crucial to support mass electric vehicle (EV) adoption. Although many cities worldwide have already installed an initial network of public chargers, it is often unclear whether the current supply of infrastructure is in line with demand and how many more charging stations are required to cope with future EV growth. In this sense, transactional charging data on the existing network can help answer these questions. We present a novel method that uses historical charging data as input to obtain answers to the following questions: (a) How many more chargers are required to meet future demand? and (b) Where should these new chargers be installed? By mining the individual charging behavior of EV drivers, we show that overflow dynamics can be found between charging stations. That is, when a preferred charging station is fully occupied, it is found that EV drivers divert to other charging stations nearby. Identifying these dynamics allows us to simulate the impact of a demand increase on the charging infrastructure network more accurately. We found the number of new chargers required to be significantly lower when considering overflow dynamics. Our simulations indicate that if demand is doubled, 30%–50% fewer charging points are needed compared with a situation in which overflow dynamics are neglected but the same failure rate is still maintained (i.e., percentage of failed charging sessions in the network). Determining the exact number of chargers will depend on the failure rate policymakers are willing to accept, reflecting the trade-off between charging convenience and utilization.

This paper presents a high-fidelity electro-thermal model of a half-bridge that consists of IGBTs and anti-parallel diodes. The model calculates and estimates the half-bridge voltages, currents, switching and conduction losses considering the operating temperature and current conditions. Moreover, this model is suitable for varying switching frequency operation. The electro-thermal model can be used as an evaluation tool to analyze the performance of control strategies for traction inverter from efficiency, temperature and component stress point of view. In this paper performance of Direct Torque Model Predictive Control (DTMPC) of an Interior Permanent Magnet Synchronous Motor (IPMSM) is evaluated in comparison with Indirect Field Oriented Control (IFOC) with sinusoidal pulse width modulation (PWM). The inverter model and the MPC are both implemented in C-Mex for rapid execution. The MPC algorithm implemented in this research tracks torque reference while using Maximum-Torque-Per-Ampere (MTPA) strategy and minimizing switching losses. Both control systems are able to follow the speed reference. The MPC shows a decrease in losses compared to IFOC when tested with low-speed and high-speed parts of the WLTC profile.

Abstract Purpose Policy implementation in the logistics sector might drive unexpected side-effects which sometimes undermine the performance of key economic activities of logistics operators, especially in areas such as transport service, sustainability of operations, etc. Especially for the latter, there is a lack of understanding how the sustainability performance if retail logistics solutions is impacted on by policy implementation and, in turn, by operators’ responsive measures. This paper conducts a sustainability analysis of concrete innovative and already tested retail logistics solutions addressing the research question “what are the effects of retail logistics solutions on total costs and sustainability performance?” Methods The analysis relies on the development and application of an indicator-based framework based on the key sustainability components (economy, environment, society) and enriched by the addition of the transport component. The framework assesses three different scenarios together with a business-as-is one: Urban Consolidation Centre, Tethering and Shared Bus accompanied with a Strengths-Weaknesses analysis. Data are provided by an international food retailer operating within the city of Antwerp, Belgium, but conclusions can be generalized due to wider applicability of measures and solutions examined. Results External costs analysis shows that higher degree of internalization is achieved in the line-haul transport. Within an urban context, the measures that do not require significant initial investment and broad interventions are assessed as the most sustainable in our analysis. Tethering is the solution that indicates the highest sustainability score. Conclusions The impact of innovative and already tested solutions relies on a variety of factors: organizational, urban context, type of goods transported, engagement of stakeholders, etc.. In any case, innovation is crucial for urban retail logistics impacting on transport service, society, economy and environment. Any new retail business model should be designed with respect to cost efficiency and through a socially acceptable transition path.

Electric vehicle (EV) markets have evolved. In this regard, rechargeable batteries such as lithium-ion (Li-ion) batteries become critical in EV applications. However, the nonlinear features of Li-ion batteries make their performance over their lifetime, reliability, and control more difficult. In this regard, the battery management system (BMS) is crucial for monitoring, handling, and improving the lifespan and reliability of this type of battery from cell to pack levels, particularly in EV applications. Accordingly, the BMS should control and monitor the voltage, current, and temperature of the battery system during the lifespan of the battery. In this article, the BMS definition, state of health (SoH) and state of charge (SoC) methods, and battery fault detection methods were investigated as crucial aspects of the control strategy of Li-ion batteries for assessing and improving the reliability of the system. Moreover, for a clear understanding of the voltage behavior of the battery, the open-circuit voltage (OCV) at three ambient temperatures, 10 °C, 25 °C, and 45 °C, and three different SoC levels, 80%, 50%, and 20%, were investigated. The results obtained showed that altering the ambient temperature impacts the OCV variations of the battery. For instance, by increasing the temperature, the voltage fluctuation at 45 °C at low SoC of 50% and 20% was more significant than in the other conditions. In contrast, the rate of the OCV at different SoC in low and high temperatures was more stable.

Extra virgin olive-oil (EVO) production is an important economic activity for several countries, especially in the Mediterranean area such as Spain, Italy, Greece and Tunisia. The two major by-products from olive oil production, solid-liquid Olive Pomace (OP) and the Olive Mill Waste Waters (OMWW), are still mainly disposed on soil, in spite of the existence of legislation which already limits this practice. The present study compares the environmental impacts associated with two different scenarios for the management of waste from olive oil production through a comparative Life Cycle Assessment (LCA). The two alternative scenarios are: (I) Anaerobic Digestion and (II) Disposal on soil. The analysis was performed through SimaPro software and the assessment of the impact categories was based on International Life Cycle Data and Cumulative Energy Demand methods. Both the scenarios are mostly related to the cultivation and harvesting phase and are highly dependent on the irrigation practice and related energy demand. Results from the present study clearly show that the waste disposal on soil causes the worst environmental performance of all the impact categories considered here. Important environmental benefits have been identified when anaerobic digestion is chosen as the final treatment. It was consequently demonstrated that anaerobic digestion should be a feasible alternative for olive mills, to produce biogas from common olive oil residues, reducing the environmental burden and adding value to the olive oil production chain.

The integration of distributed renewable energy sources (RES) and the electrification of devices raise new challenges for the distribution system operator (DSO). This paper assesses PAR versus cost tradeoff when scheduling an electric vehicle (EV) fleet. We formulate a bilevel Mixed-Integer Linear Programming optimization problem. At the lower level, we minimize individual household electricity bills using dynamic pricings. At the upper level, we aim to smooth the power load curve of a typical Brussels MV/LV transformer. We show that a small deviation from cost-only optimization can reduce significantly the Peak-to-Average Ratio of the power load curve of a transformer. Harnessing load flexibility from EV allows the DSO to manage the transformer load to avoid grid congestion and also incentivizes load aggregators to participate in the ancillary services market.

Methamphetamine (MET) is one of the most used illicit drugs in Europe and is recognized as one of the Emerging Organic Micropollutants. It is discharged into the sewerage system from different sources and then enters the wastewater treatment plants. The present study aimed at providing a better knowledge of the fate of MET through the wastewater treatment plants. The study addressed two different issues: (1) optimization of the analytical methods for MET determination in both liquid and sludge phases, focusing on the effects of potentially interfering substances and (2) investigation on the behaviour of MET in the biological treatment process, with specific concern for the biomass activity at different drug concentrations. Results of the study on issue 1 highlighted that the applied analytical method for MET determination (UPLC-MS/MS) is affected by the main components of wastewater for about 9-23%, which is comparable with the uncertainties of the method (about ± 28%). The method showed also to be repeatable and reliable (recovery > 75%; repeatability < 10-15%; bias uncertainty < 30%), and relatively easy-to-use. Therefore, it can be considered suitable for measurements on routine base in the WWTPs. Batch tests conducted to address issue 2 showed total removal of 84, 90, and 96% at 50, 100, and 200 ng/L initial MET concentration, respectively, for a contact time of 6 h. The removal process was mainly ascribed to the biological activity of both heterotrophic and autotrophic bacteria. The pseudo first-order kinetic model provided the best fitting of the experimental data of the overall biological processes at all the tested concentrations. Furthermore, the respirometric tests showed that MET does not induce any inhibition. Adsorption of MET on activated sludge was always very low.

The relevance of sector coupling is increasing when shifting from the current highly centralised and mainly fossil fuel-based energy system to a more decentralized and renewable energy system. Cross-sectoral linkages are already recognized as a cost-effective decarbonisation strategy that provides significant flexibility to the system. Modelling such cross-sectoral interconnections is thus highly relevant. In this work, these interactions are considered in a long-term perspective by uni-directional soft-linking of two models: JRC-EU-TIMES, a long term planning multisectoral model, and Dispa-SET, a unit commitment and optimal dispatch model covering multiple energy sectors such as power, heating & cooling, transportation etc. The impact of sector coupling in future Europe-wide energy systems with high shares of renewables is evaluated through five scenarios. Results show that the contributions of individual sectors are quite diverse. The transport sector provides the highest flexibility potential in terms of power curtailment, load shedding, congestion in the interconnection lines and resulting greenhouse gas emissions reduction. Nevertheless, allowing combinations of multiple flexibility options such as hydro for the long-term, electric vehicles and flexible thermal units for the short-term provides the best solution in terms of system adequacy, greenhouse gas emissions and operational costs. Comisión Europea