Manejo de potencia para un vehículo con acople fotovoltaico en motor híbrido

Nowadays, the vision of the industries around the world is focused in developing and presenting new solutions that are ecofriendly, being one of this solutions, hybrid and electric motors. This paper presents the simulation of an algorithm for the management of power for a hybrid motor, which electric part is being supplied using a photovoltaic system, allowing the analysis of the car battery, in terms of acceleration and deceleration of the vehicle. Obtaining as a result, a study of the behavior of the photovoltaic system along with the hybrid motor, and the battery according to the meteorological conditions affecting the system.Actualmente, la visión de la industria en todo el mundo se está enfocando en desarrollar y realizar soluciones nuevas que sean amigables con el medio ambiente; una de estas son los motores híbridos y eléctricos. Este artículo propone realizar la simulacón de un algoritmo de manejo de potencias para un motor híbrido, cuya parte eléctrica será abastecida mediante un sistema fotovoltaico; con ello se busca analizar la batería del carro en función de la aceleración y desaceleración de este. Se obtiene como resultado un estudio del comportamiento de un sistema fotovoltaico en conjunto con un motor híbrido, donde se analiza el comportamiento de la batería según las condiciones meteorológicas que afecten al sistema

Electric vehicles charging infrastructure demand and deployment : challenges and solutions

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper

Electric vehicle scheduling and optimal charging problem: complexity, exact and heuristic approaches

International audienceThis paper deals with the Electric Vehicle Scheduling and Optimal Charging Problem.More precisely, given a fleet of Electric Vehicles - EVs and Combustion Engine Vehicles - CVs, aset of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimizethe assignment of vehicles to tours and minimize the charging cost of EVs, while considering severaloperational constraints mainly related to chargers, electricity grid, and EVs driving range. We provethat the Electric Vehicle Scheduling and Charging Problem (EVSCP) is NP-hard in the ordinary sense.We provide a mixed-integer linear programming formulation to model the EVSCP and use CPLEX tosolve small and medium instances. To solve large instances, we propose two heuristics: a SequentialHeuristic - SH and a Global Heuristic - GH. The SH considers the EVs sequentially. To each EV, itassigns a set of tours and guarantees the feasibility of a charging schedule using the Maximum WeightClique Problem. Then, it generates an optimal charging schedule for this EV using a Minimum CostFlow formulation. However, the GH computes, in the first step, a feasible assignment of tours to allEVs. In the second step, it applies a global Min-Cost-Flow-based charging algorithm to minimize thecharging cost of the EVs fleet. To evaluate the efficiency of our solving approaches, computationalresults on a large set of real and randomly generated test instances are reported and compared. Testedinstances include large random instances with up to 200 EVs and 320 tours

Electric Vehicle Scheduling and Optimal Charging Problem: Complexity, Exact and Heuristic Approaches

This paper deals with the Electric Vehicle Scheduling and Optimal Charging Problem.More precisely, given a eet of Electric Vehicles - EVs and Combustion Engine Vehicles - CVs, aset of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimizethe assignment of vehicles to tours and minimize the charging cost of EVs, while considering severaloperational constraints mainly related to chargers, electricity grid, and EVs driving range. We provethat the Electric Vehicle Scheduling and Charging Problem (EVSCP) is NP-hard in the ordinary sense.We provide a mixed-integer linear programming formulation to model the EVSCP and use CPLEX tosolve small and medium instances. To solve large instances, we propose two heuristics: a SequentialHeuristic - SH and a Global Heuristic - GH. The SH considers the EVs sequentially. To each EV, itassigns a set of tours and guarantees the feasibility of a charging schedule using the Maximum WeightClique Problem. Then, it generates an optimal charging schedule for this EV using a Minimum CostFlow formulation. However, the GH computes, in the rst step, a feasible assignment of tours to allEVs. In the second step, it applies a global Min-Cost-Flow-based charging algorithm to minimize thecharging cost of the EVs eet. To evaluate the eciency of our solving approaches, computationalresults on a large set of real and randomly generated test instances are reported and compared. Testedinstances include large random instances with up to 200 EVs and 320 tours

DEVELOPMENT AND EVALUATION OF AN INTELLIGENT TRANSPORTATION SYSTEMS-BASED ARCHITECTURE FOR ELECTRIC VEHICLES

The rapid development of increasingly complex in-vehicle electronics now offers an unprecedented level of convenience and versatility as well as accelerates the demand for connected driving experience, which can only be achieved in a comprehensive Intelligent Transportation Systems (ITS) technology based architecture. While a number of charging and range related issues continue to impede the Electric Vehicle (EV) market growth, integrating ITS technologies with EVs has the potential to address the problems and facilitate EV operations. This dissertation presents an ITS based vehicle infrastructure communication architecture in which abundant information can be exchanged in real time through vehicle-to-vehicle and vehicle-to- infrastructure communication, so that a variety of in-vehicle applications can be built to enhance the performance of EVs. This dissertation emphasizes on developing two applications that are specifically designed for EVs. First, an Ant Colony Optimization (ACO) based routing and recharging strategy dedicated to accommodate EV trips was devised. The algorithm developed in this study seeks, in real time, the lowest cost route possible without violating the energy constraint and can quickly provide an alternate suboptimal route in the event of unexpected situations (such as traffic congestion, traffic incident and road closure). If the EV battery requires a recharge, the algorithm can be utilized to develop a charging schedule based on recharging locations, recharging cost and wait time, and to simultaneously maintain the minimum total travel time and energy consumption objectives. The author also elucidates a charge scheduling model that maximizes the net profit for each vehicle-to-grid (V2G) enabled EV owner who participates in the grid ancillary services while the energy demands for their trips can be guaranteed as well. By applying ITS technologies, the charge scheduling model can rapidly adapt to changes of variables or coefficients within the model for the purpose of developing the latest optimal charge/discharge schedule. The performance of EVs involved in the architecture was validated by a series of simulations. A roadway network in Charleston, SC was created in the simulator and a comparison between ordinary EVs and connected EVs was performed with a series of simulation experiments. Analysis revealed that the vehicle-to-vehicle and vehicle-to- infrastructure communication technology resulted in not only a reduction of the total travel time and energy consumption, but also in the reduction of the amount of the recharged electricity and corresponding cost, thus significantly relieving the concerns of range anxiety. The routing and recharging strategy also potentially allows for a reduction in the EV battery capacity, in turn reducing the cost of the energy storage system to a reasonable level. The efficiency of the charge scheduling model was validated by estimating optimal annual financial benefits and leveling the additional load from EV charging to maintain a reliable and robust power grid system. The analysis showed that the scheduling model can indeed optimize the profit which substantially offsets the annual energy cost for EV owners and that EV participants can even make a positive net profit with a higher power of the electrical circuit. In addition, the extra load distribution from the optimized EV charging operations was more balanced than that from the unmanaged EV operations. Grid operators can monitor and ease the load in real time by adjusting the prices should the load exceed the capacity. The ITS supported architecture presented in this dissertation can be used in the evolution of a new generation of EVs with new features and benefits for prospective owners. This study suggests a great promise for the integration of EVs with ITS technologies for purpose of promoting sustainable transportation system development

Smart charging strategies for electric vehicle charging stations

Although the concept of transportation electrification holds enormous prospects in addressing the global environmental pollution problem, consumer concerns over the limited availability of charging stations and long charging/waiting times are major contributors to the slow uptake of plug-in electric vehicles (PEVs) in many countries. To address the consumer concerns, many countries have undertaken projects to deploy a network of both fast and slow charging stations, commonly known as electric vehicle charging networks. While a large electric vehicle charging network will certainly be helpful in addressing PEV owners\u27 concerns, the full potential of this network cannot be realised without the implementation of smart charging strategies. For example, the charging load distribution in an EV charging network would be expected to be skewed towards stations located in hotspot areas, instigating longer queues and waiting times in these areas, particularly during afternoon peak traffic hours. This can also lead to a major challenge for the utilities in the form of an extended PEV charging load period, which could overlap with residential evening peak load hours, increasing peak demand and causing serious issues including network instability and power outages. This thesis presents a smart charging strategy for EV charging networks. The proposed smart charging strategy finds the optimum charging station for a PEV owner to ensure minimum charging time, travel time and charging cost. The problem is modelled as a multi-objective optimisation problem. A metaheuristic solution in the form of ant colony optimisation (ACO) is applied to solve the problem. Considering the influence of pricing on PEV owners\u27 behaviour, the smart charging strategy is then extended to address the charging load imbalance problem in the EV network. A coordinated dynamic pricing model is presented to reduce the load imbalance, which contributes to a reduction in overlaps between residential and charging loads. A constraint optimization problem is formulated and a heuristic solution is introduced to minimize the overlap between the PEV and residential peak load periods. In the last part of this thesis, a smart management strategy for portable charging stations (PCSs) is introduced. It is shown that when smartly managed, PCSs can play an important role in the reduction of waiting times in an EV charging network. A new strategy is proposed for dispatching/allocating PCSs during various hours of the day to reduce waiting times at public charging stations. This also helps to decrease the overlap between the total PEV demand and peak residential load

Gestión eficiente de los convertidores de potencia conectados al bus DC de una Microrred híbrida de generación distribuida

Tesis por compendio[ES] Dos aspectos críticos en la operación de una microrred son las estrategias de control y gestión de potencia implementadas, las cuales son esenciales para proporcionar su buen funcionamiento. La aplicación adecuada de dichas estrategias permite compensar los desequilibrios de potencia causados por la discontinuidad de la generación y de la demanda de energía en las microrredes. En este sentido, el objetivo global de estas estrategias de gestión es equilibrar adecuadamente el flujo de potencia en la microrred, mediante la aplicación de diferentes algoritmos que permiten cumplir con los criterios de estabilidad, protección, balance de potencia, transiciones, sincronización con la red y gestión adecuada de la microrred. En el caso de microrredes de pequeña escala de potencia con bajo número de generadores y sistemas de almacenamiento distribuidos, las estrategias de control centralizado ofrecen un alto nivel de flexibilidad para lograr funcionalidades avanzadas en la microrred y una adecuada distribución de la potencia entre los convertidores que la conforman. Esta tesis se ha enmarcado en el contexto de algoritmos de gestión centralizada de potencia de una microrred de generación distribuida en modo conectado a red. Los algoritmos presentados se pueden aplicar a los convertidores de potencia conectados al bus DC de una microrred AC/DC híbrida o en una microrred de DC, donde el despacho de potencia es observado y gestionado por un controlador central. Este último adquiere datos del sistema mediante una infraestructura de comunicaciones y estima la potencia que gestionará cada uno de los convertidores de potencia, sistemas de almacenamiento y cargas en funcionamiento. En este estudio se muestra la validación experimental de las estrategias de gestión aplicadas en la microrred desde el enfoque del comportamiento de los convertidores de potencia, de las baterías y las cargas ante dicha gestión. Se verifica la estabilidad de la microrred sometiendo a los convertidores a diferentes escenarios de funcionamiento. Estos escenarios pueden ser fluctuaciones en la irradiación, la demanda, el estado de carga de las baterías, los límites máximos de exportación/importación de potencia desde/hacia la microrred hacia/desde la red principal y de la tarifa eléctrica. Adicionalmente, se propone un sistema de almacenamiento de energía en baterías encargado de mantener el equilibrio de potencia en el bus de DC de la microrred que permite aprovechar las fuentes de generación renovables presentes en la microrred y maximizar el tiempo de servicio de las baterías mediante la aplicación de un algoritmo de carga de las baterías. Este último se ajusta al procedimiento de carga especificado por el fabricante, estableciendo las tasas de carga en función de los escenarios en que la microrred se encuentre. El procedimiento de carga en las baterías es fundamental para garantizar las condiciones adecuadas de operación de las mismas, ya que toman en consideración los parámetros establecidos por el fabricante, como son: tasas de carga/descarga, tensión máxima de carga, temperaturas de operación, etc.[CA] Dos dels aspectes crítics en l'operació d'una micro-xarxa són les estratègies de control i gestió de potència implementades, les quals són essencials per proporcionar el seu bon funcionament. L'aplicació adequada de dites estratègies permet compensar els desequilibris de potència causats per la discontinuïtat de la generació i demanda d'energia en les micro-xarxes. En aquest sentit, l'objectiu global de les nomenades estratègies de gestió és equilibrar adequadament el flux de potència en la micro-xarxa mitjançant l'aplicació de diferents algoritmes que permeten complir amb els criteris d'estabilitat, protecció, balanç de potència, transicions, sincronització amb la xarxa i gestió adequada de la micro-xarxa. En el cas de micro-xarxes de potència a petita escala i amb baix nombre de generadors i sistemes d'emmagatzematge distribuïts, les estratègies de control centralitzades ofereixen un alt nivell de flexibilitat per aconseguir funcionalitats avançades en la micro-xarxa i una adequada distribució de la potència entre els convertidors que la conformen. Aquesta tesi s'ha emmarcat al context d'algoritmes de gestió centralitzada de potència d'una micro-xarxa de generació distribuïda en mode de connexió a xarxa. Els algoritmes presentats es poden aplicar als convertidors de potència connectats al bus DC d'una micro-xarxa AC/DC hibrida o en una micro-xarxa de DC, on el despatx de potència és observat i gestionat per un controlador central. Aquest últim adquireix dades del sistema mitjançant una infraestructura de comunicacions i estima la potència que gestionarà cadascun dels convertidors de potència, sistemes d'emmagatzematge i càrregues en funcionament. En aquest estudi es mostren la validació experimental de les estratègies de gestió aplicades en la micro-xarxa des d'un enfocament dels convertidors de potència, de les bateries i les càrregues davant d'aquesta gestió. Es verifica l'estabilitat de la micro-xarxa exposant als convertidors a diferents escenaris de funcionament. Aquest escenaris poden ser fluctuants en la irradiació, la demanda, l'estat de càrrega de les bateries, els límits màxims d'exportació/importació de potència des de/cap a la micro-xarxa cap a/des de la xarxa principal i de la tarifa elèctrica. Addicionalment, es proposa un sistema d'emmagatzematge d'energia en bateries encarregats de mantindre l'equilibri de potència al bus DC de la micro-xarxa i que permet aprofitar les fonts de generació renovables presents en la micro-xarxa i maximitzar el temps de servei de les bateries mitjançant l'aplicació d'un algoritme de càrrega de bateries. Aquest últim s'ajusta al procediment de càrrega especificat pel fabricant, establint les taxes de càrrega en funció dels escenaris en que la micro-xarxa es trobe. El procediment de càrrega a les bateries es fonamental per garantir les condicions adequades d'operació de les mateixes, ja que prenen en consideració els paràmetres establerts pel fabricant, com ara són: taxes de càrrega/descàrrega, tensió màxima de càrrega, temperatures d'operació, etc.[EN] Two critical aspects in microgrids operation are the control and power management strategies, which are essential for their efficient operation. The adequate application of these strategies allows compensating the power imbalance caused by the discontinuity in the energy generation or changes in the power demand of the microgrid. In this sense, the overall objective of these power management strategies is to keep the power balance between the generation and the demand in the microgrid through the application of different algorithms that fulfill the criteria of stability, protection, smooth transitions and synchronization with the main grid. In the case of small-scale microgrids with a low number of distributed generators and energy storage systems, the centralized control strategies offer a higher level of flexibility to achieve advanced features in the microgrid and for the suitable power sharing between the converters that compose it. This thesis has been focused on centralized power management algorithms of a microgrid working in grid connected mode. These algorithms can be applied to the power converters connected to the DC bus of both hybrid AC/DC and DC microgrids, where the power dispatch is controlled by a central controller which acquires system data through a communication infrastructure and sets the power to be managed by each of the converters under operation. In this thesis, the experimental validation of the power management strategies of the microgrid is presented, from the point of view of the behavior of the power converters, batteries and loads. It is provided with a realistic evaluation under different microgrid operation scenarios. These scenarios were sudden changes of the irradiation, load, state of charge, the maximum power to be exported/imported from/to the microgrid to/from the grid, and the electricity tariff. Additionally, it is proposed a battery energy storage system that keeps the power balance at the DC bus of the microgrid, taking advantage from the renewable energy sources and adjusting the battery energy storage through a suitable charging procedure specified by the manufacturer. The proposed procedure changes the charging parameters of the batteries depending on the microgrid states. Its goal is to extend the service time of batteries and to allow proper energy management in the system.Salas Puente, RA. (2019). Gestión eficiente de los convertidores de potencia conectados al bus DC de una Microrred híbrida de generación distribuida [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118658TESISCompendi

Learning Automata based Shiftable Domestic Load Scheduling in Smart Grid: Accuracy and Fairness

Master's thesis in Information- and communication technology IKT590 - University of Agder 2016In this thesis, investigation is carried out on scheduling of shiftable loads which involves partly selection of loads within the power budget of operator. Domestic shiftable loads are scheduled along multiple timeslots with the considerations of the accuracy of scheduling in terms of optimization of capacity and of the fairness between appliances in terms of frequency of usage in smart grids. Since the scheduled load can not be over the capacity, the global optimal point is a combination of loads which are most close or equal to but not over the capacity. This optimization problem is shown to be NP hard, and has been formulated as a potential game. To solve this problem in a distributed manner, Learning Automata (LA) based methods are proposed. Although the LA based methods do not favour any participants of scheduling which can serve as a fair selection in the long run, the fairness among the loads in finite time is still worth studying. To make the scheduling process fair in short time, virtual coin game is employed into the scheduling. Simulations have been performed by implementing two LA methods, namely BLA and LR−I, under different number of timeslots, with and without consideration of coin game to evaluate and compare the results. Simulation results show that the accuracy in terms of the closeness of the converged result to the global optimal point achieved by both LA based scheduling methods is high and the fairness of the system is increased by applying the virtual coin game

Research on economic planning and operation of electric vehicle charging stations

Appropriately planning and scheduling strategies can improve the enthusiasm of Electric vehicles (EVs), reduce charging losses, and support the power grid system. Thus, this dissertation studies the planning and operating of the EV charging station. First, an EV charging station planning strategy considering the overall social cost is proposed. Then, to reduce the charging cost and guarantee the charging demand, an optimal charging scheduling method is proposed. Additionally, by considering the uncertainty of charging demand, a data-driven intelligent EV charging scheduling algorithm is proposed. Finally, a collaborative optimal routing and scheduling method is proposed