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

Linearizing Battery Degradation for Health-aware Vehicle Energy Management

The utilization of battery energy storage systems (BESS) in vehicle-to-grid (V2G) and plug-in hybrid electric vehicles (PHEVs) benefits the realization of net-zero in the energy-transportation nexus. Since BESS represents a substantial part of vehicle total costs, the mitigation of battery degradation should be factored into energy management strategies. This paper proposes a two-stage BESS aging quantification and health-aware energy management method for reducing vehicle battery aging costs. In the first stage, a battery aging state calibration model is established by analyzing the impact of cycles with various Crates and depth of discharges based on a semi-empirical method. The model is further linearized by learning the mapping relationship between aging features and battery life loss with a linear-in-the-parameter supervised learning method. In the second stage, with the linear battery life loss quantification model, a neural hybrid optimization-based energy management method is developed for mitigating vehicle BESS aging. The battery aging cost function is formulated as a linear combination of system states, which simplifies model solving and reduces computation cost. The case studies in an aggregated EVs peak-shaving scenario and a PHEV with an engine-battery hybrid powertrain demonstrate the effectiveness of the developed method in reducing battery aging costs and improving vehicle total economy. This work provides a practical solution to hedge vehicle battery degradation costs and will further promote decarbonization in the energy-transportation nexus.</p

UAV Control in Close Proximities - Ceiling Effect on Battery Lifetime

With the recent developments in the unmanned aerial vehicles (UAV), it is expected them to interact and collaborate with their surrounding objects, other robots and people in order to wisely plan and execute particular tasks. Although these interaction operations are inherently challenging as compared to free-flight missions, they might bring diverse advantages. One of them is their basic aerodynamic interaction during the flight in close proximities which can result in a reduction of the controller effort. In this study, by collecting real-time data, we have observed that the current drawn by the battery can be decreased while flying very close to the surroundings with the help of the ceiling effect. For the first time, this phenomenon is analyzed in terms of battery lifetime degradation by using a simple full equivalent cycle counting method. Results show that cycling related effect on battery degradation can be reduced by a 15.77% if the UAV can utilize ceiling effect.Comment: ICoIAS 201

New Energy Management Concepts for Hybrid and Electric Powertrains: Considering the Impact of Lithium Battery and Ultracapacitor Aging

During the lifetime of an energy storage system, its health deteriorates from use due to irreversible internal changes to the system. This degradation results in decreased capacity and efficiency of the battery or capacitor. This chapter reviews empirical aging models for lithium-ion battery and ultracapacitor energy storage systems. It will explore how operating conditions like large currents, high temperature, or deep discharge cycles impact the health of the energy storage system. After reviewing aging models, this chapter will then show how these models can be used in vehicle energy management control systems to reduce energy storage system aging. This includes both aging-aware control and control of hybrid energy storage systems (systems that include both a battery and an ultracapacitor)

Accurate Battery Modelling for Control Design and Economic Analysis of Lithium-ion Battery Energy Storage Systems in Smart Grid

Adoption of lithium-ion battery energy storage systems (Li-ion BESSs) as a flexible energy source (FES) has been rapid, particularly for active network management (ANM) schemes to facilitate better utilisation of inverter based renewable energy sources (RES) in power systems. However, Li-ion BESSs display highly nonlinear performance characteristics, which are based on parameters such as state of charge (SOC), temperature, depth of discharge (DOD), charge/discharge rate (C-rate), and battery-aging conditions. Therefore, it is important to include the dynamic nature of battery characteristics in the process of the design and development of battery system controllers for grid applications and for techno-economic studies analyzing the BESS economic profitability. This thesis focuses on improving the design and development of Li-ion BESS controllers for ANM applications by utilizing accurate battery performance models based on the second-order equivalent-circuit dynamic battery modelling technique, which considers the SOC, C-rate, temperature, and aging as its performance affecting parameters. The proposed ANM scheme has been designed to control and manage the power system parameters within the limits defined by grid codes by managing the transients introduced due to the intermittence of RESs and increasing the RES penetration at the same time. The validation of the ANM scheme and the effectiveness of controllers that manage the flexibilities in the power system, which are a part of the energy management system (EMS) of ANM, has been validated with the help of simulation studies based on an existing real-life smart grid pilot in Finland, Sundom Smart Grid (SSG). The studies were performed with offline (short-term transient-stability analysis) and real-time (long-term transient analysis) simulations. In long-term simulation studies, the effect of battery aging has also been considered as part of the Li-ion BESS controller design; thus, its impact on the overall power system operation can be analyzed. For this purpose, aging models that can determine the evolving peak power characteristics associated with aging have been established. Such aging models are included in the control loop of the Li-ion BESS controller design, which can help analyse battery aging impacts on the power system control and stability. These analyses have been validated using various use cases. Finally, the impact of battery aging on economic profitability has been studied by including battery-aging models in techno-economic studies.Aurinkosähköjärjestelmien ja tuulivoiman laajamittainen integrointi sähkövoimajärjestelmän eri jännitetasoille on lisääntynyt nopeasti. Uusiutuva energia on kuitenkin luonteeltaan vaihtelevaa, joka voi aiheuttaa nopeita muutoksia taajuudessa ja jännitteessä. Näiden vaihteluiden hallintaan tarvitaan erilaisia joustavia energiaresursseja, kuten energiavarastoja, sekä niiden tehokkaan hyödyntämisen mahdollistaviea älykkäitä ja aktiivisia hallinta- ja ohjausjärjestelmiä. Litiumioniakkuihin pohjautuvien invertteriliitäntäisten energian varastointijärjestelmien käyttö joustoresursseina aktiiviseen verkonhallintaan niiden pätö- ja loistehon ohjauksen avulla on lisääntynyt nopeasti johtuen niiden kustannusten laskusta, modulaarisuudesta ja teknisistä ominaisuuksista. Litiumioniakuilla on erittäin epälineaariset ominaisuudet joita kuvaavat parametrit ovat esimerkiksi lataustila, lämpötila, purkaussyvyys, lataus/ purkausnopeus ja akun ikääntyminen. Akkujen ominaisuuksien dynaaminen luonne onkin tärkeää huomioida myös akkujen sähköverkkoratkaisuihin liittyvien säätöjärjestelmien kehittämisessä sekä teknis-taloudellisissa kannattavuusanalyyseissa. Tämä väitöstutkimus keskittyy ensisijaisesti aktiiviseen verkonhallintaan käytettävien litiumioniakkujen säätöratkaisuiden parantamiseen hyödyntämällä tarkkoja, dynaamisia akun suorituskykymalleja, jotka perustuvat toisen asteen ekvivalenttipiirien akkumallinnustekniikkaan, jossa otetaan huomioon lataustila, lataus/purkausnopeus ja lämpötila. Työssä kehitetyn aktiivisen verkonhallintajärjestelmän avulla tehtävät akun pätö- ja loistehon ohjausperiaatteet on validoitu laajamittaisten simulointien avulla, esimerkiksi paikallista älyverkkopilottia Sundom Smart Gridiä simuloimalla. Simuloinnit tehtiin sekä lyhyen aikavälin offline-simulaatio-ohjelmistoilla että pitkän aikavälin simulaatioilla hyödyntäen reaaliaikasimulointilaitteistoa. Pitkän aikavälin simulaatioissa akun ikääntymisen vaikutus otettiin huomioon litiumioniakun ohjauksen suunnittelussa jotta sen vaikutusta sähköjärjestelmän kokonaistoimintaan voitiin analysoida. Tätä tarkoitusta varten luotiin akun ikääntymismalleja, joilla on mahdollista määrittää akun huipputehon muutos sen ikääntyessä. Akun huipputehon muutos taas vaikuttaa sen hyödynnettävyyteen erilaisten pätötehon ohjaukseen perustuvien joustopalveluiden tarjoamiseen liittyen. Lisäksi väitöstutkimuksessa tarkasteltiin akkujen ikääntymisen vaikutusta niiden taloudelliseen kannattavuuteen sisällyttämällä akkujen ikääntymismalleja teknis-taloudellisiin tarkasteluihin.fi=vertaisarvioitu|en=peerReviewed

Cost-optimal energy management of hybrid electric vehicles using fuel cell/battery health-aware predictive control

Energy management is an enabling technology for increasing the economy of fuel cell/battery hybrid electric vehicles. Existing efforts mostly focus on optimization of a certain control objective (e.g., hydrogen consumption), without sufficiently considering the implications for on-board power sources degradation. To address this deficiency, this article proposes a cost-optimal, predictive energy management strategy, with an explicit consciousness of degradation of both fuel cell and battery systems. Specifically, we contribute two main points to the relevant literature, with the purpose of distinguishing our study from existing ones. First, a model predictive control framework, for the first time, is established to minimize the total running cost of a fuel cell/battery hybrid electric bus, inclusive of hydrogen cost and costs caused by fuel cell and battery degradation. The efficacy of this framework is evaluated, accounting for various sizes of prediction horizon and prediction uncertainties. Second, the effects of driving and pricing scenarios on the optimized vehicular economy are explored

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

An Analysis of the Requirement for Energy Management Systems in India for Electric Vehicles

Conventional fuels used in combustion engines are the main sources of carbon dioxide emissions, which affect the environment. If energy is available from renewable sources compared to conventional sources, electric vehicles (EVs) offer efficient and cost-effective solutions to the above issue. However, EVs employ batteries for energy storage, which presents a number of issues. For example, overheating produced by chemical reactions during the charging and discharging process in high temperatures can result in the battery's fatal destruction. Hence, an effective energy management system (EMS) is in need of the technology required for the accomplishment of EVs in the long term. Monitoring and optimizing electricity use is the aim of energy management, which aims to cut costs and emissions without interfering with operations. When lifetime CO2 emissions are taken into consideration, EVs will be far more environmentally friendly than regular fuel vehicles because of the incorporation of sustainable power. Distributed solar energy will help reduce the distribution and transmission losses, which will further lower the lifetime CO2 emissions and operating costs of EVs and hasten their commercial viability. This paper presents a review of energy management challenges and their necessity. EV energy management is very important as it helps to minimize EV charging costs