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How did Norway get a highly developed database for charging stations, capable of real-time updates on availability, ready and free to be adopted by any country? A co-operation between Transnova, a governmental entity, and the association of EV-users to develop an open database which allows everyone to build services upon standardized data.

The vast capabilities of autonomous underwater vehicles (AUVs)—such as in assisting scientific research, conducting military tasks, and repairing oil pipelines—are limited by high operating costs and the relative inaccessibility of power in the open ocean. Wave powered AUV charging stations may address these issues. With projected increases in usage of AUVs globally in the next five years, AUV charging stations can enable less expensive and longer AUV missions. This paper summarizes the design process and investigates the feasibility of a wave powered, mobile AUV charging station, including the choice of a wave energy converter and AUV docking station as well as the ability to integrate the charging station with an autonomous surface vehicle. The charging station proposed in this paper meets many different commercial, scientific, and defense needs, including continuous power availability, data transmission capabilities, and mobility. It will be positioned as a hub for AUV operations, enabling missions to run autonomously with no support ship. The potential market for this design is very promising, with an estimated $1.64 million market size just for AUV technologies by 2025.

Electric vehicles (EVs) have the advantages of low pollution, low energy consumption, and high energy efficiency, so they are highly valued by governments, enterprises, and consumers. However, the promotion and use of electric vehicles is restricted to a certain extent because of their limited range. This paper selects electric vehicle intercity medium- and long-distance travel as the research object, and takes the classical flow-capturing location problem as the theoretical basis for the expressway network or national highway network. This paper also considers the driver's charging choice behavior and range anxiety, studies the electric vehicle charging station location problem, establishes the charging station location model, and uses the Tabu search algorithm to solve the problem. Finally, the effectiveness of the model and algorithm is verified by empirical analysis. The results show that the charging station location model considering the driver's charging choice behavior and range anxiety performs better.

Growing environmental awareness and strong political impetus have resulted in plug-in electric vehicles (PEV) becoming ever more attractive means of transportation. They are expected to have a significant impact to the overall loading of future distribution networks. Thus, current distribution grids need to be updated in order to accommodate PEV fleets, which are recognized in smart grid (SG) objective. The prevailing concern in that sense is the combined impact of a large number of randomly connected PEVs in the distribution network. On the other hand, continually growing PEVs are likely to impose more specific and acute challenges in short term, it is also expected to expect that grid operators will impose strict demand-response requirements for the operation of charging stations (CS)s. Accordingly, this PhD project proposed a fast charging station structure which is combined with flywheel energy storage system (FESS). The proposed PhD project supports a corresponding smart control strategy that could be termed "charging station to grid (CS2G)". It explores the possibility of using a dedicated energy storage system (FESS) within the charging station to alleviate grid and market conditions but not compromise the PEV's battery charging algorithms or place the daily routine of the PEV owners in jeopardy. The overall control of FCS is divided into two layers organized into a hierarchical structure with the layer being the closest to the physical equipment termed as primary layer and the one on top of it as secondary layer. Control design is hence carried out by following the common principle for management of both large interconnected and small distributed generation (DG) systems. For the purpose of control optimization and parameter tuning of the primary layer, detailed modeling of grid ac/dc and FESS converters is built and analyzed. |Based on modeling analysis, centralized and distributed control methods are both explored to realize the coordination control of each components in the system. Specially, this project proposes a "dc voltage vs speed" droop strategy for FESS control based on distributed bus signaling (DBS) concept. Then the concept is extended to apply for control of multi-parallel FESS structure. Additionally, an adaptive dc bus voltage control for grid converter is proposed to enhance the system stability and efficiency. Aiming at alleviating the unexpected conditions in grid-side and providing ancillary services to distributed network, multi-functional controller in secondary control layer which enables four-quadrate operation ability is proposed to cope with different scenarios, such as PEV sudden connection and disconnection, active power compensation (load shifting), reactive power compensation, loss of grid power. Moreover, Centralized and distributed secondary control methods are explored and compared; especially a dynamic consensus control concept is applied into the system for coordinating paralleled grid interfaces and FESS. Furthermore, stability issues are discussed and analyzed based on proposed control algorithm feature. First, small-signaling model of each component are built to study the dynamic stability of system operating at different stages in details. Due to the switching modes existing in the system, stability of switching system is studied based on common Lyapunov function method when the system switches its operation behavior between two modes. Finally, a downscaled FCS prototype with FESS is built in the intelligent MG lab, and experiments and hardware-in-loop simulation results are conducted to verify the effectiveness and feasibility with the proposed FCS concept, control schemes, modeling and stability analysis.

[EN] The electric vehicle (EV) is gradually being introduced in cities. The impact of this introduction is less due, among other reasons, to the lack of charging infrastructure necessary to satisfy the demand. In today¿s cities there is no adequate infrastructure and it is necessary to have action plans that allow an easy deployment of a network of EV charging points in current cities. These action plans should try to place the EV charging stations in the most appropriate places for optimizing their use. According to this, this paper presents an agent-oriented approach that analyses the different configurations of possible locations of charging stations for the electric vehicles in a specific city. The proposed multi-agent system takes into account data from a variety of sources such as social networks activity and mobility information in order to estimate the best configurations. The proposed approach employs a genetic algorithm (GA) that tries to optimize the possible configurations of the charging infrastructure. Additionally, a new crossover method for the GA is proposed considering this context. ; This work was partially supported by MINECO/FEDER RTI2018-095390-B-C31 and MODINVECI project of the Spanish government. Vicent Botti and Jaume Jordan are funded by UPV PAID-06-18 project. Jaume Jordan is funded by grant APOSTD/2018/010 of GVA-FSE ; Jordán, J.; Palanca Cámara, J.; Del Val Noguera, E.; Julian Inglada, VJ.; Botti, V. (2021). Localization of charging stations for electric vehicles using genetic algorithms. Neurocomputing. 452:416-423. https://doi.org/10.1016/j.neucom.2019.11.122 ; S ; 416 ; 423 ; 452

Published Article ; Renewable energy charging stations can play a key role in the successful development and deployment of electric vehicles in the areas not connected to the electrical grid. This paper discusses the possibilities of using electric Tuketuk battery charging station in the rural areas of the Democratic Republic of Congo (DRC); the basic specifications of the proposed vehicle propulsion system are taken into account. The proposed charging station is powered by renewable energy source such as wind or photovoltaic (PV) used as stand alone or in hybrid configuration with battery storage system to avoid the use of diesel generators or additional stresses on the very weak electrical grid, where it is available. Different feasible configurations of the charging station using renewable energies are simulated using HOMER software and the results compared to the corresponding diesel generator while responding to the battery charging energy requirements of the Tuketuk. Two different strategies for operating the charging station are simulated and the results are analyzed and discussed in order to select the best configuration. The decision criteria used for these comparisons include the equipment setup, energy production, financial viability for a project lifetime of 20 years.