Control of second-life hybrid battery energy storage system based on modular boost-multilevel buck converter

To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations

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

A multi-modular second life hybrid battery energy storage system for utility grid applications

The modern grid system or the smart grid is likely to be populated with multiple distributed energy sources, e.g. wind power, PV power, Plug-in Electric Vehicle (PEV). It will also include a variety of linear and nonlinear loads. The intermittent nature of renewable energies like PV, wind turbine and increased penetration of Electric Vehicle (EV) makes the stable operation of utility grid system challenging. In order to ensure a stable operation of the utility grid system and to support smart grid functionalities such as, fault ride-through, frequency response, reactive power support, and mitigation of power quality issues, an energy storage system (ESS) could play an important role. A fast acting bidirectional energy storage system which can rapidly provide and absorb power and/or VARs for a sufficient time is a potentially valuable tool to support this functionality. Battery energy storage systems (BESS) are one of a range suitable energy storage system because it can provide and absorb power for sufficient time as well as able to respond reasonably fast. Conventional BESS already exist on the grid system are made up primarily of new batteries. The cost of these batteries can be high which makes most BESS an expensive solution. In order to assist moving towards a low carbon economy and to reduce battery cost this work aims to research the opportunities for the re-use of batteries after their primary use in low and ultra-low carbon vehicles (EV/HEV) on the electricity grid system. This research aims to develop a new generation of second life battery energy storage systems (SLBESS) which could interface to the low/medium voltage network to provide necessary grid support in a reliable and in cost-effective manner. The reliability/performance of these batteries is not clear, but is almost certainly worse than a new battery. Manufacturers indicate that a mixture of gradual degradation and sudden failure are both possible and failure mechanisms are likely to be related to how hard the batteries were driven inside the vehicle. There are several figures from a number of sources including the DECC (Department of Energy and Climate Control) and Arup and Cenex reports indicate anything from 70,000 to 2.6 million electric and hybrid vehicles on the road by 2020. Once the vehicle battery has degraded to around 70-80% of its capacity it is considered to be at the end of its first life application. This leaves capacity available for a second life at a much cheaper cost than a new BESS Assuming a battery capability of around 5-18kWhr (MHEV 5kWh - BEV 18kWh battery) and approximate 10 year life span, this equates to a projection of battery storage capability available for second life of >1GWhrs by 2025. Moreover, each vehicle manufacturer has different specifications for battery chemistry, number and arrangement of battery cells, capacity, voltage, size etc. To enable research and investment in this area and to maximize the remaining life of these batteries, one of the design challenges is to combine these hybrid batteries into a grid-tie converter where their different performance characteristics, and parameter variation can be catered for and a hot swapping mechanism is available so that as a battery ends it second life, it can be replaced without affecting the overall system operation. This integration of either single types of batteries with vastly different performance capability or a hybrid battery system to a grid-tie 3 energy storage system is different to currently existing work on battery energy storage systems (BESS) which deals with a single type of battery with common characteristics. This thesis addresses and solves the power electronic design challenges in integrating second life hybrid batteries into a grid-tie energy storage unit for the first time. This study details a suitable multi-modular power electronic converter and its various switching strategies which can integrate widely different batteries to a grid-tie inverter irrespective of their characteristics, voltage levels and reliability. The proposed converter provides a high efficiency, enhanced control flexibility and has the capability to operate in different operational modes from the input to output. Designing an appropriate control system for this kind of hybrid battery storage system is also important because of the variation of battery types, differences in characteristics and different levels of degradations. This thesis proposes a generalised distributed power sharing strategy based on weighting function aims to optimally use a set of hybrid batteries according to their relative characteristics while providing the necessary grid support by distributing the power between the batteries. The strategy is adaptive in nature and varies as the individual battery characteristics change in real time as a result of degradation for example. A suitable bidirectional distributed control strategy or a module independent control technique has been developed corresponding to each mode of operation of the proposed modular converter. Stability is an important consideration in control of all power converters and as such this thesis investigates the control stability of the multi-modular converter in detailed. Many controllers use PI/PID based techniques with fixed control parameters. However, this is not found to be suitable from a stability point-of-view. Issues of control stability using this controller type under one of the operating modes has led to the development of an alternative adaptive and nonlinear Lyapunov based control for the modular power converter. Finally, a detailed simulation and experimental validation of the proposed power converter operation, power sharing strategy, proposed control structures and control stability issue have been undertaken using a grid connected laboratory based multi-modular hybrid battery energy storage system prototype. The experimental validation has demonstrated the feasibility of this new energy storage system operation for use in future grid applications

Cascaded Converters For Integration And Management Of Grid Level Energy Storage Systems

ABSTRACT CASCADED CONVERTERS FOR INTEGRATION AND MANAGEMENT OF GRID-LEVEL ENERGY STORAGE SYSTEMS by ZUHAIR ALAAS December 2017 Advisor: Dr. Caisheng Wang Major: ELECTRICAL ENGINEERING Degree: Doctor of Philosophy This research work proposes two cascaded multilevel inverter structures for BESS. The gating and switching control of switching devices in both inverter typologies are done by using a phase-shifted PWM scheme. The first proposed isolated multilevel inverter is made up of three-phase six-switch inverter blocks with a reduced number of power components compared with traditional isolated CHB. The suggested isolated converter has only one battery string for three-phase system that can be used for high voltage and high power applications such as grid connected BESS and alternative energy systems. The isolated inverter enables dq frame based simple control and eliminates the issues of single-phase pulsating power, which can cause detrimental impacts on certain dc sources. Simulation studies have been carried out to compare the proposed isolated multi-level inverter with an H-bridge cascaded transformer inverter. The simulation results verified the performance of the isolated inverter. The second proposed topology is a Hierarchal Cascaded Multilevel Converter (HCMC) with phase to phase SOC balancing capability which also for high voltage and high power battery energy storage systems. The HCMC has a hybrid structure of half-bridge converters and H-bridge inverters and the voltage can be hierarchically cascaded to reach the desired value at the half-bridge and the H-bridge levels. The uniform SOC battery management is achieved by controlling the half-bridge converters that are connected to individual battery modules/cells. Simulation studies and experimental results have been carried on a large scale battery system under different operating conditions to verify the effectiveness of the proposed inverters. Moreover, this dissertation presents a new three-phase SOC equalizing circuit, called six-switch energy-level balancing circuit (SSBC), which can be used to realize uniform SOC operation for full utilization of the battery capacity in proposed HCMC or any CMI inverter while keeping balanced three-phase operation. A sinusoidal PWM modulation technique is used to control power transferring between phases. Simulation results have been carried out to verify the performance of the proposed SSBC circuit of uniform three-phase SOC balancing

Smart battery pack for electric vehicles based on active balancing with wireless communication feedback

In this paper, the concept of smart battery pack is introduced. The smart battery pack is based on wireless feedback from individual battery cells and is capable to be applied to electric vehicle applications. The proposed solution increases the usable capacity and prolongs the life cycle of the batteries by directly integrating the battery management system in the battery pack. The battery cells are connected through half-bridge chopper circuits, which allow either the insertion or the bypass of a single cell depending on the current states of charge. This consequently leads to the balancing of the whole pack during both the typical charging and discharging time of an electric vehicle and enables the fault-tolerant operation of the pack. A wireless feedback for implementing the balancing method is proposed. This solution reduces the need for cabling and simplifies the assembling of the battery pack, making also possible a direct off-board diagnosis. The paper validates the proposed smart battery pack and the wireless feedback through simulations and experimental results by adopting a battery cell emulator

Evaluation of Battery Performance in MMC based BESS

abstract: Li-ion batteries are being used on a large scale varying from consumer electronics to electric vehicles. The key to efficient use of batteries is implementing a well-developed battery management system. Also, there is an opportunity for research for improving the battery performance in terms of size and capacity. For all this it is imperative to develop Li-ion cell model that replicate the performance of a physical cell unit. This report discusses a dual polarization cell model and a battery management system implemented to control the operation of the battery. The Li-ion cell is modelled, and the performance is observed in PLECS environment. The main aspect of this report studies the viability of Li-ion battery application in Battery Energy Storage System (BESS) in Modular multilevel converter (MMC). MMC-based BESS is a promising solution for grid-level battery energy storage to accelerate utilization and integration of intermittent renewable energy resources, i.e., solar and wind energy. When the battery units are directly integrated in submodules (SMs) without dc-dc interfaced converters, this configuration provides highest system efficiency and lowest cost. However, the lifetime of battery will be affected by the low-frequency components contained in arm currents, which has not been thoroughly investigated. This paper investigates impact of various low-frequency arm-current ripples on lifetime of Li-ion battery cells and evaluate performance of battery charging and discharging in an MMC-BESS without dc-dc interfaced converters.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Contributions to smart grids based on renewable energy sources with hydrogen as backup system. Energy management system: design, modeling and physical implementation based on model predictive control theory

Atendiendo al concepto de Smart Grid (Red Inteligente), estos sistemas están íntimamente relacionados con el uso de los sistemas de generación renovable. A pesar de los beneficios de esta tecnología, su dependencia de los recursos ambientales hace imposible garantizar el balance de energía entre generación y demanda en todo momento. Para ello, la hibridación de sistemas, así como el uso de sistemas basados en hidrógeno, se muestra como una solución técnica viable para resolver o mitigar los problemas asociados a este tipo de tecnologías. El empleo de este tipo de sistemas híbridos plantea una mayor complejidad en materia de gestión debido a la elevada cantidad de parámetros y factores a tener en cuenta de cara a garantizar un óptimo reparto energético en función de la aplicación y el estado energético del sistema. En este sentido, han de considerarse ciertos aspectos asociados a la operación real de los sistemas, tales como la topología del sistema, costes de operación y mantenimiento, la necesidad de un control de tensión de carga para baterías, la degradación de los equipos, la dinámica de cada sistema, las pérdidas asociadas al punto de trabajo, o parámetros relacionados con la calidad del suministro eléctrico. A tenor de lo anterior, es necesario el empleo de estrategias de gestión de la energía que permitan determinar el reparto energético entre dispositivos, con el objetivo de optimizar la respuesta del sistema desde el punto de vista técnico y económico, planteándose por lo tanto un problema de optimización multiobjetivo. Para dar respuesta al problema de optimización multiobjetivo propuesto, en la presente Tesis, se hace uso de una arquitectura de control distribuida, compuesta en un primer nivel por controladores locales, y en el nivel superior, se propone el uso de un controlador supervisor basado en técnicas de control predictivo (MPC). La función principal del controlador propuesto es determinar la consigna de operación de cada uno de los equipos que componen la Smart Grid, dando respuesta a la función objetivo propuesta de acuerdo a los criterios de diseño del sistema. Las ventajas de la utilización de técnicas de control predictivo respecto a otro tipo de técnicas son claras; permite el empleo de técnicas de control multivariable, permitiendo plantear problemas de optimización multiobjetivo con restricciones; así como implementar una estrategia de control basado en un horizonte de predicción, lo que permite al sistema adaptar la respuesta del controlador en base a acontecimientos futuros, mejorando la respuesta del sistema frente a técnicas de control meramente pasivas. Como base de conocimientos del controlador propuesto, en esta tesis se presenta un modelo lineal discreto generalista de la planta, calculado en cada periodo de muestreo, en base a una linealización recursiva, lo que permite aument ar la calidad del modelo respecto a soluciones basadas en torno a un único punto de linealización. El modelo incluye todos los parámetros necesarios para el control de una planta real, incluyendo los términos asociados al estado energético del sistema, tensión de operación de baterías, así como los parámetros técnicos y económicos. tales como degradación. oérdidas o coste de operación con el obietivo de definir una función de coste del sistema que permita su generalidad para cualquier tipo de aplicación u objetivo de diseño. Atendiendo al diseño del controlador propuesto, y con el objetivo de garantizar la generalidad requerida en todo el proceso, en la presente tesis se propone una metodología de diseño basado en el modelo propuesto y una función de coste que incluye todos los parámetros técnicos y económicos necesarios para resolver el problema de optimización multiobjetivo propuesto, independientemente de la aplicación y topología del sistema. Esta función objetivo permite establecer un problema de tracking de acuerdo al balance de potencia instantáneo del sistema, a la vez que son considerados los parámetros técnicos y económicos asociados a la respuesta del sistema, véase degradación y rendimiento de equipos, límites y dinámica de operación, costes de operación y mantenimiento, criterios de carga de baterías, etc. Para garantizar la generalidad del controlador propuesto, fomentando así su uso, independientemente de la aplicación y topología del sistema, en la presente tesis se propone una metodología de diseño y tuning de los parámetros del controlador, de acuerdo a la función objetivo propuesta y los criterios de diseño en materia de prioridad de uso y distribución de energía entre equipos. La propuesta metodológica está basada en las relaciones causa-efecto entre los distintos parámetros, las cuales permiten definir el comportamiento del sistema de acuerdo a la estrategia de gestión de la energía y objetivos de diseño propuestos. De forma similar, con el objetivo de considerar la optimización a corto y largo plazo del sistema, limitada por el concepto de horizonte deslizante propio de las técnicas de control predictivo, se hace uso de técnicas de control adicionales, las cuales actúan directamente sobre el proceso de ajuste de los parámetros del controlador. En este sentido, en base a la historia del sistema, se recalculan los parámetros del controlador, en caso de que sea necesario, actuándose directamente sobre los parámetros de ponderación, de tal forma que permita adaptar la respuesta dinámica o reparto energético de acuerdo a los criterios de diseño del controlador. Finalmente, la metodología de diseño y el controlador propuesto fueron validados sobre la micro red experimental del grupo de investigación TEP-192. Para ello, fue necesario el diseño, desarrollo e implementación de toda la electrónica de control, adquisición y electrónica de potencia para la correcta operación e integración de los equipos.Attending to the concept of Smart Grid, these systems are closely related to the use of renewable generation systems. Despite the benefits of this technology, its dependence on environmental resources makes it impo ssible to guarantee the balance of energy between generation and demand at all times. Far this, the hybridization of systems, as well as the use of hydrogen-basedsystems, is shown as a viable technical solution to salve or mitigate the probel ms associated with this type of technologies. The use of this type of hybrid systems poses a greater compel xity in terms of managementdue to the high number of parameters and factors to be taken into account in arder to guarantee an optimal energy distribution dependingon the application and the energy status of the system. In this sense, certain aspects associated with the actual operation of the systems, such as the topology, the operating and maintenance costs, the need far a charge voltage control far batterie s, the degradation of equipment, dynamics of each system, the lossesassociated with the working point, or parameters related to the quality of the electricity supply.In the light of the above, it is necessary to use energy management strategies to determine the energy distribution between devices, in arder to optimize the response of the system from a technicaland economic point of view, thereforeposing a multi-objective optimization problem. In arder to respond to the proposed multiobjective optimization problem, in this Thesis, a distributed control architecture is used, composed of local controllers at th e first level, and at the top level, the use of a supervisory controlel r based on predictive control techniques (MPC). The main function of the proposed controlel r is to det ermine the operating setpoint of each of the equipment that makes up the Smart Grid, responding to the proposed objective function accordingto the system design criteria. The advantages of using predictive control techniques over other types of techniques are clear; allows the use of multivariable control techniques, allowing multiobjective optimization in constrained problems; as well as implementing a control strategy based on a prediction horizon, which allows the system to adapt the response of the controller based on future events, improvingthe response of the system against merely passive control techniques. As a knowledge base of the proposed controller, this Thesis presents a general discrete linear model of the plant, calculated in each sampling period, based on a recursive linearization, which allows to increase the quality of the model with respectto solutions based on lathe to a singlepoint of linearization. The model includes all the necessary parameters far the control of a real plant, including the terms associated with the energy status of the system, battery operating voltage, as well as technical and economic parameters, such as degradation, losses or operating cost, with the objective of defining a system cost function that allows its generality far any type of application or design objective. Based on the design of the proposed controller, and with the objective of guaranteeing the generality required throuqhout the orocess. in this Thesis a desian methodoloav basedon the orooosed model and a cost function that includes ali the necessary technical and economic parameters are proposed to solve the proposed multiobjective optimization problem, regardless of the application and system topology. This objective function allows to establish a tracking problem according to the instantaneous power balance of the system, while the technical and economic parameters associated with the system response are considered, see equipment degradation and performance, limits and operating dynamics, operation and maintenance costs, battery charging criteria, etc. To guarantee the generality of the proposed controller, thus promoting its use, regardless of the application and topology of the system, this Thesis proposes a design and tuning methodology of the controller parameters, according to the proposed objective function and the design criteria in terms of priority of use and energy distribution. The methodological proposal is based on the cause-effect relationships between the different parameters, which allow defining the behavior of the system according to the energy management strategy and proposed design objectives. Similarly, in order to consider the short and long-term optimization of the system, limited by the concept of the sliding horizon typical of predictive control techniques, additional control techniques are used, which act directly on the process of adjustment of the parameters of the controller. In this sense, based on the history of the system, the parameters of the controller are recalculated, if necessary, acting directly on the weighting parameters, in such a way that it allows adapting the dynamic response or energy distribution according to the controller design criteria. Finally, the design methodology and the proposed controller were validated on the experimental micro grid of the TEP-192 research group. For this, it was necessary to design, develop and implement ali the control, acquisition and power electronics for the correct operation and integration of the equipment

Autonomous Multi-Chemistry Secondary-Use Battery Energy Storage

Battery energy storage is poised to play an increasingly important role in the modern electric grid. Not only does it provide the ability to change the time-of-day and magnitude of energy produced by renewable resources like wind and solar, it can also provide a host of other 3ancillary grid-stabilizing services. Cost remains a limiting factor in deploying energy storage systems large enough to provide these services on the scale required by an electric utility provider. Secondary-use electric vehicle batteries are a source of inexpensive energy storage materials that are not yet ready for the landfill but cannot operate in vehicles any longer. However, the wide range of manufacturers using different battery chemistries and configurations mean that integrating these batteries into a large-format system can be difficult. This work demonstrates methods for the autonomous integration and operation of a wide range of stationary energy storage battery chemistries. A fully autonomous battery characterization is paired with a novel system architecture and transactive optimization to create a system which can provide utility-scale energy services using a multitude of battery chemistries in the same system. These claims are verified using a combination of in-situ testing and a computer modelling testbed. Results are presented which demonstrate the ability of the system to combine a wide range of batteries into an effective single system

Powering the future: a comprehensive review of battery energy storage systems

Global society is significantly speeding up the adoption of renewable energy sources and their integration into the current existing grid in order to counteract growing environmental problems, particularly the increased carbon dioxide emission of the last century. Renewable energy sources have a tremendous potential to reduce carbon dioxide emissions because they practically never produce any carbon dioxide or other pollutants. On the other hand, these energy sources are usually influenced by geographical location, weather, and other factors that are of stochastic nature. The battery energy storage system can be applied to store the energy produced by RESs and then utilized regularly and within limits as necessary to lessen the impact of the intermittent nature of renewable energy sources. The main purpose of the review paper is to present the current state of the art of battery energy storage systems and identify their advantages and disadvantages. At the same time, this helps researchers and engineers in the field to find out the most appropriate configuration for a particular application. This study offers a thorough analysis of the battery energy storage system with regard to battery chemistries, power electronics, and management approaches. This paper also offers a detailed analysis of battery energy storage system applications and investigates the shortcomings of the current best battery energy storage system architectures to pinpoint areas that require further study.This publication is part of the project TED2021-132864A-I00, funded by MCIN/ AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR”.Peer ReviewedPostprint (published version