FPGA-based implementation of real-time identification procedures for adaptive control in photovoltaic applications

2013 - 2014In this thesis two adaptive Maximum Power Point Tracking (MPPT) techniques for PhotoVoltaic (PV) applications, which are based on two different real-time identification procedures are proposed. The algorithms are implemented on the same low-cost Field Programmable Gate Array (FPGA) device in charge of controlling the switching converter that processes the power produced by the PV array. The Perturb & Observe (P&O) algorithm is the most common MPPT technique. Its efficiency is mainly related to two parameters: the perturbation amplitude and the perturbation period Tp. The optimal values of such parameters depend on the PV array type and on the irradiance and temperature conditions thereof, as well as on the parameters of the power processing circuit. Thus, a method for dynamically adapt the P&O parameters would be very useful for increasing the P&O MPPT performances. Several approaches presented in the current literature are focused on the adaptation of the perturbation amplitude. In this thesis, on the contrary, the on-line optimization of the value of Tp is proposed. The effects of such a parameter on both the tracking speed and the stationary MPPT efficiency are pointed out. Besides, the need for a real-time identification technique for identifying the minimum acceptable value of Tp in the actual PV operating conditions is demonstrated. Two different identification procedures aimed at developing the aforementioned adaptive MPPT controllers have been studied: the Cross-Correlation Method (CCM) and the Dual Kalman Filter (DKF). The first one belongs to the non-parametric techniques and allows identifying the impulse response and the frequency response of the PV system. Instead, the DKF is a model-based approach which estimates the states and the parameters of the system. One of the aims of this thesis is to demonstrate the usefulness of these identification procedures for the optimization of the PV P&O MPPT performances. In order to achieve a good trade-off between the desired performances and the cost of the controller, hardware digital solutions, such as FPGA, are adopted. They are able to reduce the execution time by exploiting the intrinsic parallelism of the algorithm to be implemented. Then, in this work, the challenging design of a high performances hardware architecture for the identification algorithms is dealt with. Moreover, the implemented identification techniques are compared in terms of accuracy, identification time and used hardware resources. Several simulations and experimental tests demonstrate the feasibility of the developed identification procedures. In fact, the proposed adaptive MPPT controllers suitably change in few tens of milliseconds the value of Tp ensuring a stable MPPT behaviour. The developed FPGA-based architectures of both the identification techniques is promising for embedding other functions that are of interest in the field of PV systems, e.g. related to on-line monitoring or diagnostic purposes. The work has been developed in co-tutorship between the Systèmes et Applications des Technologies de l’Information et de l’Energie (SATIE) laboratory in the Université de Cergy-Pontoise (France) and the Circuiti Elettronici di Potenza laboratory in the Universitá degli Studi di Salerno (Italy). The work has been supported by the Université Franco-Italienne by means the Vinci project 2013 n. C2-29. [edited by author]XIII n.s

Guest editorial: energy storage in smart grids

Energy storage systems and smart grids cooperation is now crucial and will encourage collaborative engagement by different players in the energy market, offering sophisticated management and control approaches. Therefore, new advances and innovative solutions for such cooperation are of preeminent importance. Moreover, electric mobility should also be considered in this scenario. Electric vehicles (EVs) can be seen as distributed energy storage systems that generally need to be charged but, in some cases, can be adopted to support the grid thanks to vehicle-to-grid (V2G) and vehicle-for-grid (V4G) modes, offering advantages of controlled operation with active or reactive power. So, energy storage systems can be distinguished into aggregated and distributed structures, and they can be based on different technologies, such as batteries, fuel-cells, and super-capacitors. Furthermore, the integration of new renewable energy solutions with energy storage systems in smart grids should also be promoted. Power and energy management are crucial for the upcoming challenges and novel opportunities in smart grids. In line with this trend, this Special Issue aims to present further research on and developments in energy storage systems in smart grids, including power electronics converters, novel modulation schemes, energy and power management strategies, advanced battery packs and Battery Management Systems (BMSs). Novel renewable energy solutions are also of interest, as well as their cooperative and strategic integration with storage and EV chargers. Advanced EV services, such as V2G and V4G in the perspective of contributions to improve power quality, can also be considered. Three main topics can be found in this Special Issue: power electronic converters, converter and machine modelling and lithium-ion battery packs. In the following section, the papers accepted per each topic will be rapidly summarized along with their main achievements

Efficiency comparison of a dc-dc interleaved converter based on SiC-MOSFET and Si-IGBT devices for EV chargers

The charging process is one of the main factors for the widespread dissemination of electric mobility, therefore, the use of optimized power electronics converters is of utmost importance. In addition to innovative topologies, the use of emerging technologies of semiconductors is also crucial. In this context, using a three-phase interleaved dc-dc topology, a comparison between the use of SiC-MOSFET and Si-IGBT is presented in this paper, mainly in terms of operating efficiency. Two cases have been presented: 1) with the same inductor, where only power device losses have been considered; 2) with the same inductor current ripple, where different inductors have been considered and the analysis included also the inductor design and losses. The simulations were carried out in LTspice simulation tool on realistic dynamic models of power switch modules obtained from the manufacturer’s experimental tests. The results validate the use of SiC-MOSFET for the three-phase interleaved dc-dc topology showing lower losses for both the power devices and inductor and, most important, prove the advantages of its use in terms of efficiency for a wide range of operating powers.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia with-in the Project Scope: UID/CEC/00319/2019, and by the FCT Project newERA4GRIDs PTDC/EEI-EEE/30283/2017

Design of an Integrated, Six-Phase, Interleaved, Synchronous DC/DC Boost Converter on a Fuel-Cell-Powered Sport Catamaran

This paper describes the preliminary analysis, design and implementation phases of a DC/DC boost converter dedicated to the Futura catamaran propulsion chain developed by the UniBoAT team at the University of Bologna. The main goal of the project was the reduction of the converter’s weight by eliminating the use of heat sinks and by reducing the component size, especially inductors and capacitors. The obtained converter is directly integrated into the structure containing the fuel-cell stack. The realized converter was based on an interleaved architecture with six phases controlled through the average current mode control. The design was validated through simulations carried out using the LT-Spice software, whereas experimental validations were performed by means of both bench tests and on-field tests. Detailed thermal and efficiency analyses were provided with the bench tests under the two synchronous and non-synchronous operating modes and with the adoption of the phase-shedding technique. Prototype implementation and performance in real operating conditions are discussed in relation to on-field tests. The designed converter can be used in other applications requiring a voltage-controlled boost converter

Overview of Lithium-Ion battery modeling methods for state-of-charge estimation in electrical vehicles

As a critical indictor in the Battery Management System (BMS), State of Charge (SOC) is closely related to the reliable and safe operation of lithium-ion (Li-ion) batteries. Model-based methods are an effective solution for accurate and robust SOC estimation, the performance of which heavily relies on the battery model. This paper mainly focuses on battery modeling methods, which have the potential to be used in a model-based SOC estimation structure. Battery modeling methods are classified into four categories on the basis of their theoretical foundations, and their expressions and features are detailed. Furthermore, the four battery modeling methods are compared in terms of their pros and cons. Future research directions are also presented. In addition, after optimizing the parameters of the battery models by a Genetic Algorithm (GA), four typical battery models including a combined model, two RC Equivalent Circuit Model (ECM), a Single Particle Model (SPM), and a Support Vector Machine (SVM) battery model are compared in terms of their accuracy and execution time

Smart charging for electric car-sharing fleets based on charging duration forecasting and planning

Electric car-sharing (ECS) is an increasingly popular service in many European cities. The management of an ECS fleet is more complex than its thermal engine counterpart due to the longer ”refueling“ time and the limited autonomy of the vehicles. To ensure adequate autonomy, the ECS provider needs high-capacity charging hubs located in urban areas where available peak power is often limited by the system power rating. Lastly, electric vehicle (EV) charging is typically entrusted to operators who retrieve discharged EVs in the city and connect them to the charging hub. The timing of the whole charging process may strongly differ among the vehicles due to their different states of charge on arrival at the hub. This makes it difficult to plan the charging events and leads to non-optimal exploitation of charging points. This paper provides a smart charging (SC) method that aims to support the ECS operators’ activity by optimizing the charging points’ utilization. The proposed SC promotes charging duration management by differently allocating powers among vehicles as a function of their state of charge and the desired end-of-charge time. The proposed method has been evaluated by considering a real case study. The results showed the ability to decrease charging points downtime by 71.5% on average with better exploitation of the available contracted power and an increase of 18.8% in the average number of EVs processed per day

Electric Vehicles Charging Management System for Optimal Exploitation of Photovoltaic Energy Sources Considering Vehicle-to-Vehicle Mode

The growing penetration of distributed renewable energy sources (RES) together with the increasing number of new electric vehicle (EV) model registrations is playing a significant role in zero-carbon energy communities’ development. However, the ever-larger share of intermittent renewable power plants, combined with the high and uncontrolled aggregate EV charging demand, requires an evolution toward new planning and management paradigms of energy districts. Thus, in this context, this paper proposes novel smart charging (SC) techniques that aim to integrate as much as possible RES generation and EV charging demand at the local level, synergically acting on power flows and avoiding detrimental effects on the electrical power system. To make this possible, a centralized charging management system (CMS) capable of individually modulating each charging power of plugged EVs is presented in this paper. The CMS aims to maximize the charging self-consumption from local RES, flattening the peak power required to the external grid. Moreover, the CMS guarantees an overall good state of charge (SOC) at departure time for all the vehicles without requiring additional energy from the grid even under low RES power availability conditions. Two methods that differ as a function of the EV power flow direction are proposed. The first SC only involves unidirectional power flow, while the second one also considers bidirectional power flow among vehicles, operating in vehicle-to-vehicle (V2V) mode. Finally, simulations, which are presented considering an actual case study, validate the SC effects on a reference scenario consisting of an industrial area having a photovoltaic (PV) plant, non-modulable electrical loads, and EV charging stations (CS). Results are collected and performance improvements by operating the different SC methods are compared and described in detail in this paper