Power Electronics-Enabled Self-X Multicell Batteries: A Design Toward Smart Batteries

The traditional multicell battery design usually employs a fixed configuration to connect multiple cells in series and in parallel during operation in order to achieve the required voltage and current. However, this fixed configuration results in low reliability, low fault tolerance, and non-optimal energy conversion efficiency. This paper proposes a novel power electronics-enabled self-X, multicell battery design. The proposed multicell battery can automatically configure itself according to the dynamic load/storage demand and the condition of each cell. The proposed battery can self-heal from failure or abnormal operation of single or multiple cells, self-balance from cell state variations, and self-optimize to achieve optimal energy conversion efficiency. These features are achieved by a new cell switching circuit and a high performance battery management system proposed in this paper. The proposed design is validated by simulation and experiment for a 6 × 3 cell polymer lithium-ion battery. The proposed design is universal and can be applied to any type and size of battery cells

Improving the Efficiency of Energy Harvesting Embedded System

In the past decade, mobile embedded systems, such as cell phones and tablets have infiltrated and dramatically transformed our life. The computation power, storage capacity and data communication speed of mobile devices have increases tremendously, and they have been used for more critical applications with intensive computation/communication. As a result, the battery lifetime becomes increasingly important and tends to be one of the key considerations for the consumers. Researches have been carried out to improve the efficiency of the lithium ion battery, which is a specific member in the more general Electrical Energy Storage (EES) family and is widely used in mobile systems, as well as the efficiency of other electrical energy storage systems such as supercapacitor, lead acid battery, and nickel–hydrogen battery etc. Previous studies show that hybrid electrical energy storage (HEES), which is a mixture of different EES technologies, gives the best performance. On the other hand, the Energy Harvesting (EH) technique has the potential to solve the problem once and for all by providing green and semi-permanent supply of energy to the embedded systems. However, the harvesting power must submit to the uncertainty of the environment and the variation of the weather. A stable and consistent power supply cannot always be guaranteed. The limited lifetime of the EES system and the unstableness of the EH system can be overcome by combining these two together to an energy harvesting embedded system and making them work cooperatively. In an energy harvesting embedded systems, if the harvested power is sufficient for the workload, extra power can be stored in the EES element; if the harvested power is short, the energy stored in the EES bank can be used to support the load demand. How much energy can be stored in the charging phase and how long the EES bank lifetime will be are affected by many factors including the efficiency of the energy harvesting module, the input/output voltage of the DC-DC converters, the status of the EES elements, and the characteristics of the workload. In this thesis, when the harvesting energy is abundant, our goal is to store as much surplus energy as possible in the EES bank under the variation of the harvesting power and the workload power. We investigate the impact of workload scheduling and Dynamic Voltage and Frequency Scaling (DVFS) of the embedded system on the energy efficiency of the EES bank in the charging phase. We propose a fast heuristic algorithm to minimize the energy overhead on the DC-DC converter while satisfying the timing constraints of the embedded workload and maximizing the energy stored in the HEES system. The proposed algorithm improves the efficiency of charging and discharging in an energy harvesting embedded system. On the other hand, when the harvesting rate is low, workload power consumption is supplied by the EES bank. In this case, we try to minimize the energy consumption on the embedded system to extend its EES bank life. In this thesis, we consider the scenario when workload has uncertainties and is running on a heterogeneous multi-core system. The workload variation is represented by the selection of conditional branches which activate or deactivate a set of instructions belonging to a task. We employ both task scheduling and DVFS techniques for energy optimization. Our scheduling algorithm considers the statistical information of the workload to minimize the mean power consumption of the application while satisfying a hard deadline constraint. The proposed DVFS algorithm has pseudo linear complexity and achieves comparable energy reduction as the solutions found by mathematical programming. Due to its capability of slack reclaiming, our DVFS technique is less sensitive to small change in hardware or workload and works more robustly than other techniques without slack reclaiming

Reconfigurable Battery Techniques and Systems: A Survey

Battery packs with a large number of battery cells are becoming more and more widely adopted in electronic systems, such as robotics, renewable energy systems, energy storage in smart grids, and electronic vehicles. Therefore, a well-designed battery pack is essential for battery applications. In the literature, the majority of research in battery pack design focuses on battery management system, safety circuit, and cell-balancing strategies. Recently, the reconfigurable battery pack design has gained increasing attentions as a promising solution to solve the problems existing in the conventional battery packs and associated battery management systems, such as low energy efficiency, short pack lifespan, safety issues, and low reliability. One of the most prominent features of reconfigurable battery packs is that the battery cell topology can be dynamically reconfigured in the real-time fashion based on the current condition (in terms of the state of charge and the state of health) of battery cells. So far, there are several reconfigurable battery schemes having been proposed and validated in the literature, all sharing the advantage of cell topology reconfiguration that ensures balanced cell states during charging and discharging, meanwhile providing strong fault tolerance ability. This survey is undertaken with the intent of identifying the state-of-the-art technologies of reconfigurable battery as well as providing review on related technologies and insight on future research in this emerging area

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

Stochastic management framework of distribution network systems featuring large-scale variable renewable energy sources and flexibility options

The concerns surrounding climate change, energy supply security and the growing demand are forcing changes in the way distribution network systems are planned and operated, especially considering the need to accommodate large-scale integration of variable renewable energy sources (vRESs). An increased level of vRESs creates technical challenges in the system, bringing a huge concern for distribution system operators who are given the mandate to keep the integrity and stability of the system, as well as the quality of power delivered to end-users. Hence, existing electric energy systems need to go through an eminent transformation process so that current limitations are significantly alleviated or even avoided, leading to the so-called smart grids paradigm. For distribution networks, new and emerging flexibility options pertaining to the generation, demand and network sides need to be deployed for these systems to accommodate large quantities of variable energy sources, ensuring an optimal operation. Therefore, the management of different flexibility options needs to be carefully handled, minimizing the sideeffects such as increasing costs, worsening voltage profile and overall system performance. From this perspective, it is necessary to understand how a distribution network can be optimally operated when featuring large-scale vRESs. Because of the variability and uncertainty pertinent to these technologies, new methodologies and computational tools need to be developed to deal with the ensuing challenges. To this end, it is necessary to explore emerging and existing flexibility options that need to be deployed in distribution networks so that the uncertainty and variability of vRESs are effectively managed, leading to the real-time balancing of demand and supply. This thesis presents an extensive analysis of the main technologies that can provide flexibility to the electric energy systems. Their individual or collective contributions to the optimal operation of distribution systems featuring large-scale vRESs are thoroughly investigated. This is accomplished by taking into account the stochastic nature of intermittent power sources and other sources of uncertainty. In addition, this work encompasses a detailed operational analysis of distribution systems from the context of creating a sustainable energy future. The roles of different flexibility options are analyzed in such a way that a major percentage of load is met by variable RESs, while maintaining the reliability, stability and efficiency of the system. Therefore, new methodologies and computational tools are developed in a stochastic programming framework so as to model the inherent variability and uncertainty of wind and solar power generation. The developed models are of integer-mixed linear programming type, ensuring tractability and optimality.As mudanças climáticas, a crescente procura por energia e a segurança de abastecimento estão a modificar a operação e o planeamento das redes de distribuição, especialmente pela necessidade de integração em larga escala de fontes de energia renováveis. O aumento desses recursos energéticos sustentáveis gera enormes desafios a nível técnico no sistema, atendendo a que o operador do sistema de distribuição tem o dever de manter a integridade e a estabilidade da rede, bem como a qualidade de energia entregue aos consumidores. Portanto, os sistemas de energia elétrica existentes devem passar por um eminente processo de transformação para que as limitações atuais sejam devidamente atenuadas ou mesmo evitadas, esperando-se assim chegar ao paradigma das redes elétricas inteligentes. Para as redes de distribuição acomodarem fontes variáveis de energia renovável, novas e emergentes opções de flexibilidade, que dizem respeito à geração, carga e à própria rede, precisam de ser desenvolvidas e consideradas na operação ótima da rede de distribuição. Assim, a gestão das opções de flexibilidade deve ser cuidadosamente efetuada para minimizar os efeitos secundários como o aumento dos custos, agravamento do perfil de tensão e o desempenho geral do sistema. Desta perspetiva, é necessário entender como uma rede de distribuição pode operar de forma ótima quando se expõe a uma integração em larga escala de fontes variáveis de energia renovável. Devido à variabilidade e incerteza associadas a estas tecnologias, novas metodologias e ferramentas computacionais devem ser desenvolvidas para lidar com os desafios subsequentes. Desta forma, as opções de flexibilidade existentes e emergentes devem ser implantadas para gerir a incerteza e variabilidade das fontes de energia renovável, mantendo o necessário balanço entre carga e geração. Nesta tese é feita uma análise extensiva das principais tecnologias que podem providenciar flexibilidade aos sistemas de energia elétrica, e as suas contribuições para a operação ótima dos sistemas de distribuição, tendo em consideração a natureza estocástica dos recursos energéticos intermitentes e outras fontes de incerteza. Adicionalmente, este trabalho contém investigação detalhada sobre como o sistema pode ser otimamente gerido tendo em conta estas tecnologias de forma a que a uma maior percentagem de carga seja fornecida por fontes variáveis de energia renovável, mantendo a fiabilidade, estabilidade e eficiência do sistema. Por esse motivo, novas metodologias e ferramentas computacionais usando programação estocástica são desenvolvidas para modelizar a variabilidade e incerteza inerente à geração eólica e solar. A convergência para uma solução ótima é garantida usando programação linear inteira-mista para formular o problema

하이브리드 전력 저장 시스템의 설계 및 운용 최적화

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 2. 장래혁.전기 에너지 저장 (electrical energy storage, EES) 시스템은 필요에 따라 에너지를 저장하였다가 사용함으로써 에너지 효율과 안정성을 높이고 에너지 단가를 낮추는 등의 기능을 한다. EES 시스템은 비상용 전기 공급, 부하 평준화, 첨두부하 분산, 재생에너지 발전을 위한 에너지 저장 등의 다양한 분야에서 응용할 수 있다. 현재 EES 시스템은 주로 단일 종류의 에너지 저장 기술을 사용하고 있는데, 아직까지 그 어떤 에너지 저장 기술도 높은 에너지 및 전력 밀도, 낮은 가격, 높은 충방전 효율, 긴 수명 등 이상적인 에너지 저장 기술의 모든 요건을 충족시키고 있지 못하고 있다. 하이브리드 전력 저장 (hybrid electrical energy storage, HEES) 시스템은 여러 다른 종류의 에너지 저장 소자를 이용하여 각각의 장점을 활용하여 단점을 보완하는 기법으로, EES 시스템의 성능을 개선시시키기 위한 실용적인 접근 방법 가운데 하나이다. HEES 시스템은 정교한 시스템 설계와 제어기법을 통해 각각의 에너지 저장 소자의 장점을 모두 합친 것과 같은 성능을 갖출 수 있다. 본 학위 논문은 HEES 시스템의 에너지 효율을 최대화하기 위한 고수준의 최적화 기법들을 소개한다. HEES 시스템의 새로운 구조들과 체계적인 최적 설계 기법들을 제시한다. 제안된 네트워크 전하 전송망 (charge transfer interconnect, CTI) 구조와 뱅크 (bank) 재구성 구조는 전력 변환 손실을 최소화하여 HEES 시스템의 전하 전송 효율을 최대화한다. 또한 기존의 제어 기법들이 가진 한계점을 지적하고, 이를 보완하기 위해 전력원을 동시에 고려하여 설계하고 제어하는 기법을 제시한다. 제안된 최대 전력 전달 추종 (maximum power transfer tracking, MPTT) 기법과 이를 고려한 설계 기법은 실직적인 에너지 수집량을 증가시키고 실제적으로 사용 가능한 에너지량을 증가시킨다. 마지막으로 제안된 기법의 실현 가능성을 검증하기 위한 HEES 시스템 프로토타입 구현을 소개한다.Electrical energy storage (EES) systems provides various benefits of high energy efficiency, high reliability, low cost, and so on, by storing and retrieving energy on demand. The applications of the EES systems are wide, covering contingency service, load leveling, peak shaving, energy buffer for renewable power sources, and so on. Current EES systems mainly rely on a single type of energy storage technology, but no single type of EES element can fulfill all the desirable characteristics of an ideal electrical energy storage, such as high power/energy density, low cost, high cycle efficiency, and long cycle life. A hybrid electrical energy storage (HEES) system is composed of multiple, heterogeneous energy storage elements, aiming at exploiting the strengths of each energy storage element while hiding its weaknesses, which is a practical approach to improve the performance of EES systems. A HEES system may achieve the a combination of performance metrics that are superior to those for any of its individual energy storage elements with elaborated system design and control schemes. This dissertation proposes high-level optimization approaches for HEES systems in order to maximize their energy efficiency. We propose new architectures for the HEES systems and systematic design optimization methods. The proposed networked charge transfer interconnect (CTI) architecture and bank reconfiguration architecture minimizes the power conversion loss and thus maximizes the charge transfer efficiency of the HEES system. We also point out the limitation of the conventional control schemes and propose a joint optimization design and control considering the power sources. The proposed maximum power transfer tracking (MPTT) operation and MPTT-aware design method effectively increases energy harvesting efficiency and actual available energy. We finally introduce a prototype of a HEES system implementation that physically proves the feasibility of the proposed HEES system.1 Introduction 1.1 Motivations 1.2 Contribution and Significance 1.3 Organization of Dissertation 2 Background and Related Work 2.1 Electrical Energy Storage Elements 2.1.1 Performance Metrics 2.1.1.1 Power and Energy Density 2.1.1.2 Capital Cost 2.1.1.3 Cycle Efficiency 2.1.1.4 State-of-Health and Cycle Life 2.1.1.5 Self-Discharge Rate 2.1.1.6 Environmental Impacts 2.1.2 Energy Storage Elements 2.1.2.1 Lead-Acid Batteries 2.1.2.2 Lithium-Ion Batteries 2.1.2.3 Nickel-Metal Hydride Batteries 2.1.2.4 Supercapacitors 2.1.2.5 Other Energy Storage Elements 2.2 Homogeneous Electrical Energy Storage Systems 2.2.1 Energy Storage Systems 2.2.2 Applications of EES Systems 2.2.2.1 Grid Power Generation 2.2.2.2 Renewable Energy 2.2.3 Previous Homogeneous EES Systems 2.2.3.1 Battery EES Systems 2.2.3.2 Supercapacitor EES Systems 2.2.3.3 Other EES Systems 2.3 Hybrid Electrical Energy Storage Systems 2.3.1 Hybridization Architectures 2.3.2 Applications of HEES Systems 2.4 EES System Components Characteristics 2.4.1 Power Converter 2.4.2 Photovoltaic Cell 3 Hybrid Electrical Energy Storage Systems 3.1 Design Considerations of HEES Systems 3.2 HEES System Architecture 3.3 Charge Transfer and Charge Management 3.4 HEES System Components 3.4.1 Nodes 3.4.1.1 Energy Storage Banks 3.4.1.2 Power Sources and Load Devices 3.4.2 Charge Transfer Interconnect 3.4.3 System Control and Communication Network 4 System Level Design Optimization 4.1 Reconfigurable Storage Element Array 4.1.1 Cycle Efficiency and Capacity Utilization of EES Bank 4.1.2 General Bank Reconfiguration Architecture 4.1.3 Dynamic Reconfiguration Algorithm 4.1.3.1 Cycle Efficiency 4.1.3.2 Capacity Utilization 4.1.4 Cycle Efficiency and Capacity Utilization Improvement 4.2 Networked Charge Transfer Interconnect 4.2.1 Networked Charge Transfer Interconnect Architecture 4.2.1.1 Charge Transfer Conflicts 4.2.1.2 Networked CTI Architecture 4.2.2 Conventional Placement and Routing Problems 4.2.3 Placement and Routing Problems 4.2.4 Force-Directed Node Placement 4.2.5 Networked Charge Transfer Interconnect Routing 4.2.6 Energy Efficiency Improvement 4.2.6.1 Experimental Setup 4.2.6.2 Experimental Results 5 Joint Optimization with Power Sources 5.1 Maximum Power Transfer Tracking 5.1.1 Maximum Power Transfer Point 5.1.1.1 Sub-Optimality of Maximum Power Point Tracking 5.1.1.2 Maximum Power Transfer Tracking 5.1.2 MPTT-Aware Energy Harvesting System Design 5.1.2.1 Optimal System Design Problem 5.1.2.2 Design Optimization 5.1.2.3 Systematic Design Optimization 5.1.2.4 Energy Harvesting Improvement 5.2 Photovoltaic Emulation for MPTT 5.2.1 Model Parameter Extraction 5.2.2 Dual-Mode Power Regulator with Power Hybridization 5.2.2.1 PV Module I-V Characteristics 5.2.2.2 Modes of Operation 5.2.2.3 Circuit Design Principle 5.2.2.4 Dual-Mode Power Regulator Control 5.2.2.5 Implementation 5.2.2.6 Experiments 6 Experiments 6.1 HEV Application 6.1.1 Regenerative Brake 6.1.2 PV Modules 6.1.3 EES Bank Reconfiguration and Networked CTI 6.1.4 Overall Improvement and Cost Analysis 6.2 HEES Prototype Implementation 6.2.1 Design Specifications 6.2.1.1 Power Input and Output 6.2.1.2 Power and Energy Capacity 6.2.1.3 Voltage and Current Ratings 6.2.1.4 EES Elements 6.2.2 Implementation 6.2.2.1 Bank Module 6.2.2.2 Controller and Converter Module 6.2.2.3 Charge Transfer Interconnect Capacitor Module 6.2.2.4 Bidirectional Charger 6.2.2.5 Supervising Control Software 6.2.2.6 Component Assembly 6.2.3 Control Method 7 Conclusions and Future DirectionsDocto

Next-Generation Battery Management Systems: Dynamic Reconfiguration

Batteries are widely applied to the energy storage and power supply in portable electronics, transportation, power systems, communication networks, etc. They are particularly demanded in the emerging technologies of vehicle electrification and renewable energy integration for a green and sustainable society. To meet various voltage, power, and energy requirements in large-scale applications, multiple battery cells have to be connected in series and/or parallel. While battery technology has advanced significantly in the past decade, existing battery management systems (BMSs) mainly focus on state monitoring and control of battery systems packed in fixed configurations. In fixed configurations, though, the battery system performance is in principle limited by the weakest cells, which can leave large parts severely underutilized. Allowing dynamic reconfiguration of battery cells, on the other hand, allows individual and flexible manipulation of the battery system at cell, module, and pack levels, which may open up a new paradigm for battery management. Following this trend, this paper provides an overview of next-generation BMSs featuring dynamic reconfiguration. Motivated by numerous potential benefits of reconfigurable battery systems (RBSs), the hardware designs, management principles, and optimization algorithms for RBSs are sequentially and systematically discussed. Theoretical and practical challenges during the design and implementation of RBSs are highlighted in the end to stimulate future research and development

Operational Planning and Optimisation in Active Distribution Systems for Flexible and Resilient Power

The electricity network is undergoing significant changes to cater to environmental-deterioration and fuel-depletion issues. Consequently, an increasing number of renewable resources in the form of distributed generation (DG) are being integrated into medium-voltage distribution networks. The DG integration has created several technical and economic challenges for distribution network operators. The main challenge is basically the problem of managing network voltage profile and congestion which is caused by increasing demand and intermittent DG operations. The result of all of these changes is a paradigm shift in the way distribution networks operate (from passive to active) and are managed that is not limited only to the distribution network operator but actively engages with network users such as demand aggregators, DG owners, and transmission-system operators. This thesis expands knowledge on the active distribution system in three specific areas and attempts to fill the gaps in existing approaches. A comprehensive active network management framework in active distribution systems is developed to allow studies on (i) the flexibility of network topology using modern power flow controllers, (ii) the benefits of centralised thermal electricity storage in achieving the required levels of flexibility and resiliency in an active distribution system, and (iii) system resiliency toward fault occurrence in hybrid AC/DC distribution systems. These works are implemented within the Advanced Interactive Multidimensional Modelling Systems (AIMMS) software to carry out optimisation procedure. Results demonstrate the benefit provided by a range of active distribution system solutions and can guide future distribution-system operators in making practical decisions to operate active distribution systems in cost-effective ways

Mitigating unbalance using distributed network reconfiguration techniques in distributed power generation grids with services for electric vehicles: A review

© 2019 Elsevier Ltd With rapid movement to combat climate change by reducing greenhouse gases, there is an increasing trend to use more electric vehicles (EVs) and renewable energy sources (RES). With more EVs integration into electricity grid, this raises many challenges for the distribution service operators (DSOs) to integrate such RES-based, distributed generation (DG) and EV-like distributed loads into distribution grids. Effective management of distribution network imbalance is one of the challenges. The distribution network reconfiguration (DNR) techniques are promising to address the issue of imbalance along with other techniques such as the optimal distributed generation placement and allocation (OPDGA) method. This paper presents a systematic and thorough review of DNR techniques for mitigating unbalance of distribution networks, based on papers published in peer-reviewed journals in the last three decades. It puts more focus on how the DNR techniques have been used to manage network imbalance due to distributed loads and DG units. To the best of our knowledge, this is the first attempt to review the research works in the field using DNR techniques to mitigate unbalanced distribution networks. Therefore, this paper will serve as a prime source of the guidance for mitigating network imbalance using the DNR techniques to the new researchers in this field

Analysis and Estimation of the Maximum Switch Current during Battery System Reconfiguration

Batteries are interconnected in series and/or parallel to meet wide-range power or energy demands in various industrial applications. To pursue the benefits of multiple connection structures in one system, reconfigurable battery systems (RBSs) have recently emerged for safe and efficient operation, extended energy storage and delivery, etc. Switches are the essential elements to enable the battery system reconfiguration, but selecting appropriate switches for RBS designs has not been systematically investigated. To bridge this gap, analytical expressions are derived in this paper to estimate the maximum switch current and its upper limit to facilitate the selection of RBS switches. An RBS prototype based on H-bridges is set up and experimental results verify the effectiveness and advantage of the proposed estimation method. These analytical expressions, relying only on resistances of batteries and switches, are readily applicable to practical RBS design and much more efficient than conducting numerous circuit experiments, simulation tests, or circuit analyses, especially for large-scale systems. Moreover, the analysis framework and estimation method proposed for series-parallel mutual conversion can be adaptively extended to other complex system reconfigurations to facilitate various RBS designs