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

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT

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

Lessons learned from the design of a mobile multimedia system in the Moby Dick project

Recent advances in wireless networking technology and the exponential development of semiconductor technology have engendered a new paradigm of computing, called personal mobile computing or ubiquitous computing. This offers a vision of the future with a much richer and more exciting set of architecture research challenges than extrapolations of the current desktop architectures. In particular, these devices will have limited battery resources, will handle diverse data types, and will operate in environments that are insecure, dynamic and which vary significantly in time and location. The research performed in the MOBY DICK project is about designing such a mobile multimedia system. This paper discusses the approach made in the MOBY DICK project to solve some of these problems, discusses its contributions, and accesses what was learned from the project

Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

CleanTX Analysis on the Smart Grid

The utility industry in the United States has an opportunity to revolutionize its electric grid system by utilizing emerging software, hardware and wireless technologies and renewable energy sources. As electricity generation in the U.S. increases by over 30% from today’s generation of 4,100 Terawatt hours per year to a production of 5,400 Terawatt hours per year by 2030, a new type of grid is necessary to ensure reliable and quality power. The projected U.S. population increase and economic growth will require a grid that can transmit and distribute significantly more power than it does today. Known as a Smart Grid, this system enables two- way transmission of electrons and information to create a demand-response system that will optimize electricity delivery to consumers. This paper outlines the issues with the current grid infrastructure, discusses the economic advantages of the Smart Grid for both consumers and utilities, and examines the emerging technologies that will enable cleaner, more efficient and cost- effective power transmission and consumption.IC2 Institut

Review of a disruptive vision of future power grids: a new path based on hybrid AC/DC grids and solid-state transformers

Power grids are evolving with the aim to guarantee sustainability and higher levels of power quality for universal access to electricity. More specifically, over the last two decades, power grids have been targeted for significant changes, including migration from centralized to decentralized paradigms as a corollary of intensive integration of novel electrical technologies and the availability of derived equipment. This paper addresses a review of a disruptive vision of future power grids, mainly focusing on the use of hybrid AC/DC grids and solid-state transformers technologies. Regarding hybrid AC/DC grids in particular, they are analyzed in detail in the context of unipolar and bipolar DC grids (i.e., two-wire or three-wire DC grids), as well as the different structures concerning coupled and decoupled AC configurations with low-frequency or high-frequency isolation. The contextualization of the possible configurations of solid-state transformers and the different configurations of hybrid transformers (in the perspective of offering benefits for increasing power quality in terms of currents or voltages) is also analyzed within the perspective of the smart transformers. Additionally, the paper also presents unified multi-port systems used to interface various technologies with hybrid AC/DC grids, which are also foreseen to play an important role in future power grids (e.g., the unified interface of renewable energy sources and energy storage systems), including an analysis concerning unified multi-port systems for AC or DC grids. Throughout the paper, these topics are presented and discussed in the context of future power grids. An exhaustive description of these technologies is made, covering the most relevant and recent structures and features that can be developed, as well as the challenges for the future power grids. Several scenarios are presented, encompassing the mentioned technologies, and unveiling a progressive evolution that culminates in the cooperative scope of such technologies for a disruptive vision of future power grids.This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. This work has been supported by the FCT Project newERA4GRIDs PTDC/EEI-EEE/30283/2017, and by the FCT Project DAIPESEV PTDC/EEIEEE/30382/2017