Ultracapacitor Research Articles

REUSE OF A CLOSED LANDFILL SITE FOR INSTALLATION AND OPERATION OF A BIOMASS UTILIZATION PLANT

The professional management of landfills during operation and after landfill capping is an important task to prevent environmental impacts. Landfill maintenance after closure can become economically favourable if landfill sites can be reused. Several approaches and experiences for reuse of capped landfills exist for example in livestock farming or installation and operation of solar power plants. Also the utilization for spare time activities after green capping and recreation or the industrial reuse for the development of a waste utilization plant is a common practice in Europe. The feasibility of reuse options depend on the site conditions including size and location of the landfill, the climatic conditions and the interests of the involved stakeholders. For the urban landfill site Gò Cát in Ho Chi Minh City (HCMC) experts from Germany and Vietnam developed a variant assessment for the preferred reuse options. One of three investigated options is considering the reuse of the landfill site for the development of a biomass utilization plant. In terms of the above described approach for Gò Cát the landfill operator is strongly involved in the landfill closure and long term maintenance works (leachate treatment, landfill gas utilization). Moreover, the operator can reuse the landfill site for an additional or new business. The design and operation criteria for the biomass utilization plant and best practice examples are presented. Beside the economic evaluation results of water and landfill gas balance will be discussed.

Investigating power capping toward energy‐efficient scientific applications

SummaryThe emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale‐level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore how different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. We quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.

Towards a performance-aware power capping orchestrator for the Xen hypervisor

In the last few years, multi-core processors entered into the domain of embedded systems: this, together with virtualization techniques, allows multiple applications to easily run on the same System-on-Chip (SoC). As power consumption remains one of the most impacting costs on any digital system, several approaches have been explored in literature to cope with power caps, trying to maximize the performance of the hosted applications. In this paper, we present some preliminary results and opportunities towards a performance-aware power capping orchestrator for the Xen hypervisor. The proposed solution, called XeMPUPiL, uses the Intel Running Average Power Limit (RAPL) hardware interface to set a strict limit on the processor's power consumption, while a software-level Observe-Decide-Act (ODA) loop performs an exploration of the available resource allocations to find the most power efficient one for the running workload. We show how XeMPUPiL is able to achieve higher performance under different power caps for almost all the different classes of benchmarks analyzed (e.g., CPU-, memory-and IO-bound).

SPECTR

Resource management strategies for many-core systems need to enable sharing of resources such as power, processing cores, and memory bandwidth while coordinating the priority and significance of system- and application-level objectives at runtime in a scalable and robust manner. State-of-the-art approaches use heuristics or machine learning for resource management, but unfortunately lack formalism in providing robustness against unexpected corner cases. While recent efforts deploy classical control-theoretic approaches with some guarantees and formalism, they lack scalability and autonomy to meet changing runtime goals. We present SPECTR, a new resource management approach for many-core systems that leverages formal supervisory control theory (SCT) to combine the strengths of classical control theory with state-of-the-art heuristic approaches to efficiently meet changing runtime goals. SPECTR is a scalable and robust control architecture and a systematic design flow for hierarchical control of many-core systems. SPECTR leverages SCT techniques such as gain scheduling to allow autonomy for individual controllers. It facilitates automatic synthesis of the high-level supervisory controller and its property verification. We implement SPECTR on an Exynos platform containing ARM»s big.LITTLE-based heterogeneous multi-processor (HMP) and demonstrate that SPECTR»s use of SCT is key to managing multiple interacting resources (e.g., chip power and processing cores) in the presence of competing objectives (e.g., satisfying QoS vs. power capping). The principles of SPECTR are easily applicable to any resource type and objective as long as the management problem can be modeled using dynamical systems theory (e.g., difference equations), discrete-event dynamic systems, or fuzzy dynamics.

Determining rational parameters of the capacitive energy storage system for the underground railway rolling stock

An approach was proposed for determining rational parameters of the on-board capacitive energy storage for the underground railway rolling stock with recuperation systems. The essence of the approach is to determine the maximum power and energy intensity of the on-board CESS based on the analysis of the payback period of the storage systems. The main distinctive features of this approach include taking into account a number of operating conditions and technical features of the underground railway rolling stock.Using this approach, rational parameters of the on-board capacitive energy storage system for standard operating conditions of the experimental rolling stock with the recovery systems were determined at the Sviatoshyno ‒ Brovary line of the Kyiv Metropoliten. Based on the analysis of diagrams of the payback period of the chosen storage systems, it was established that for the given conditions of operation of the underground railway rolling stock, it is rational to introduce a capacitive storage with a maximum power of 1,000 kW and a working energy intensity of 3 kWh. It was calculated that for the given operating conditions, introduction of a storage system with rational parameters will save 16.1 % of the quantity of electric energy consumed for traction of the underground railway rolling stock.

Nonlinear Controller Analysis of Fuel Cell–Battery–Ultracapacitor-based Hybrid Energy Storage Systems in Electric Vehicles

Rapidly depleting oil and natural gas resources, global warming issue, and depletion of fossil fuels are motivating the development of alternative technology for vehicular systems. Thus, an increasing number of studies have been conducted on fuel cell electric vehicles (FCEVs). This paper proposes a modeling and nonlinear control for hybrid energy storage system (HESS) in FCEVs. HESS consists of fuel cell (FC) as the main source and battery and ultracapacitor (UC) as secondary sources. Each source is connected to DC bus via DC–DC converter: FC is connected to DC bus via boost converter, while battery and UC are connected to DC bus via buck–boost converter. Based on the nonlinear behavior of power sources and converters, a dynamic model of the system is developed. A nonlinear control technique based on Lyapunov theory is applied to meet the following requirements: (1) accurate DC bus voltage regulation and (2) rapid tracking of battery and UC current to their desired reference values. Both mathematical analysis and simulations are performed to prove the asymptotic convergence of the proposed controller. To verify the performance of the controller, simulations have been done on MATLAB/Simulink, which show that the proposed controller ensures the stability of closed loop system and meet all the control objectives.

Onboard Energy Storage Systems: Ground-Fault Detection and Protection

Cities and transit authorities are procuring hybrid streetcars with onboard energy storage systems (OESSs). The energy storage system needs to be protected from both external and internal ground faults that may transfer to the vehicle. A hybrid streetcar has an OESS consisting of lithium batteries or supercapacitors, with an OESS converter connected to, or integrated with, the traction inverter. During a ground fault of the high-voltage (HV) circuit, the freewheeling diode in an OESS charger creates a fault path between the energy storage elements and the ground.

The electrical resistance of gold-capped chromium thin films

We studied the electrical resistance of polycrystalline chromium films capped by a gold layer. No anomaly was detected by resistance measurements of 10 nm thick film around room temperature, indicating that the antiferromagnetic interaction may be suppressed as decreasing the thickness of the chromium film. The sheet resistance Rs(T) curves differ from polycrystalline chromium films in previous studies because of the electrical current flows through a gold capping layer. On the other hand, the resistance drop is observed at TC = 1.15±0.05 K as that of polycrystalline chromium films in the previous report. It means that such resistance drop is not related to the chromium oxide layer on a polycrystalline chromium films. However, it is difficult to conclude that superconducting transition occurs because of the large residual resistance below the temperature where the resistance drop is observed.

Integrated Optimization of Speed Profiles and Power Split for a Tram with Hybrid Energy Storage Systems on a Signalized Route

A tram with on-board hybrid energy storage systems based on batteries and supercapacitors is a new option for the urban traffic system. This configuration enables the tram to operate in both catenary zones and catenary-free zones, and the storage of regenerative braking energy for later usage. This paper presents a multiple phases integrated optimization (MPIO) method for the coordination of speed profiles and power split considering the signal control strategy. The objective is to minimize the equivalent total energy consumption of all the power sources, which includes both the energy from the traction substation and energy storage systems. The constraints contain running time, variable gradients and curves, speed limits, power balance and signal time at some intersections. The integrated optimization problem is formulated as a multiple phases model based on the characters of the signalized route. An integrated calculation framework, using hp-adaptive pseudospectral method, is proposed for the integrated optimization problem. The effectiveness of the method is verified under fixed time signal (FTS) control strategy and tram priority signal (TPS) control strategy. Illustrative results show that this method can be successfully applied for trams with hybrid energy storage systems to improve their energy efficiency.

An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

A single-objective optimization energy management strategy (EMS) for an onboard hybrid energy storage system (HESS) for light rail (LR) vehicles is proposed. The HESS uses batteries and supercapacitors (SCs). The main objective of the proposed optimization is to reduce the battery and SC losses while maintaining the SC state of charge (SOC) within specific limits based on the distance between consecutive LR stations. To do this, a series of optimized SOC limits is used to prevent the SC from becoming exhausted prematurely instead of the standard SC SOC penalty term in the cost function. Meanwhile, a rule-based EMS (RB-EMS) is used to give the SCs charging priority over the batteries when the vehicle is braking. Moreover, a simplified method for the optimization is proposed to reduce the computational burden. Simulation and experimental results for the proposed EMS and a standard SC SOC penalty-based cost function optimization are provided to evaluate losses. As a result, it is shown that the proposed EMS, compared with standard SC SOC penalty-based cost function optimization, decreases losses and prevents the SOC from reach the discharging limits.

Peak Demand Cutting Strategy with an On-Board Energy Storage System in Mass Rapid Transit

An energy storage system (ESS) in electric railways can be installed on a train, at trackside, or at substations. The main purpose of the ESS application is to reduce energy demand and peak power with good voltage regulation. This paper presents a control strategy for efficient regenerative braking of a vehicle equipped with an on-board ESS (OBESS) and evaluates the effects on the energy consumption, voltage profile, and power drawn from substations and the OBESS during vehicle acceleration and braking. This proposed strategy is to store recovered braking energy into the OBESS and find appropriate positions to deliver its stored energy back in such a way that the peak demand of all the substations is cut. The Bangkok Transit System (BTS)-Sky Train Silom (Green) Line in Thailand is used as a case study. This system has a service distance of 13.649 km with 13 passenger stations and 7 traction substations. It employs 750-V DC rectifier substations to supply electric power through its 3rd rails. The results showed that the proposed strategy can cut the peak power at the substations approximately 75% and the overall energy consumption of the system can be reduced by 16%.

A Hierarchical Optimal Operation Strategy of Hybrid Energy Storage System in Distribution Networks with High Photovoltaic Penetration

In this paper, a hierarchical optimal operation strategy for a hybrid energy storage system (HESS) is proposed, which is suitable to be utilized in distribution networks (DNs) with high photovoltaic (PV) penetration to achieve PV power smoothing, voltage regulation and price arbitrage. Firstly, a fuzzy-logic based variable step-size control strategy for an ultracapacitor (UC) with the improvement of the lifetime of UC and tracking performance is adopted to smooth PV power fluctuations. The impact of PV forecasting errors is eliminated by adjusting the UC power in real time. Secondly, a coordinated control strategy, which includes centralized and local controls, is proposed for lithium-ion batteries. The centralized control is structured to determine the optimal battery unit for voltage regulation or price arbitrage according to lithium-ion battery performance indices. A modified lithium-ion battery aging model with better accuracy is proposed and the coupling relationship between the lifetime and the effective capacity is also considered. Additionally, the local control of the selected lithium-ion battery unit determines the charging/discharging power. A case study is used to validate the operation strategy and the results show that the lifetime equilibrium among different lithium-ion battery units can be achieved using the proposed strategy.

Fractional order unknown input filter design for fault detection of discrete fractional order linear systems

In this study, a new method is introduced to design an estimator for discrete-time linear fractional order systems, which are affected by unknown disturbances. The main goal of this study is decoupling disturbance and uncertainties from the true states for discrete fractional order systems in noisy environment. The fractional Kalman filter framework is exploited to develop a robust estimator against unknown inputs (UIs) in noisy environment. The proposed filter is exploited to detect faults in fractional order systems. Simulation results illustrate the advantages of this robust filter for state estimation and fault detection of fractional order model of ultra-capacitor (UC). The robustness of the designed filter is shown in the sense of disturbance decoupling in the presence of noise.

Improving fuel economy and performance of a fuel-cell hybrid electric vehicle (fuel-cell, battery, and ultra-capacitor) using optimized energy management strategy

Fuel-Cell System (FCS) is the primary energy supply of a Fuel-Cell Vehicle (FCV). Battery or Ultra-Capacitor (UC), as a secondary power source, is used along the FCS to improve the FCV’s power response. Battery and UC composition, as a hybrid power source presenting the term of Fuel-Cell Hybrid Electric Vehicle (FCHEV), provides the FCV with the advantages of high energy density and high dynamic response. The supervisory system of the FCHEV could be managed efficiently to exploit the benefits of battery and UC at the same time. As a matter of fact, in such a combination, the performance of the hybrid powertrain largely depends on how to distribute the requested power through different types of energy sources.In this paper, we design the powertrain elements of an FCHEV in advance, with FCS/Battery/UC considerations. The energy management strategy (EMS) is achieved by presenting a novel power sharing method and by implementing an intelligent control technique constructed based on Fuzzy Logic Control (FLC). The control parameters are accurately adjusted by the genetic algorithm (GA) while considering targets and restrictions within a multi-objective optimization function over a combined city/highway driving cycle. This optimized supervisory system is examined by Advanced Vehicle Simulator (ADVISOR) to evaluate the performance of the proposed EMS over 22 different driving cycles and some specific performance tests. The results of simulation show that the presented strategy progressively affects the vehicle characteristics. Fuel economy enhancement, vehicle performance improvement, battery charge-sustaining capability, and optimal energy distribution are some of the significant outcomes achieved by the optimized FLC-based EMS.

Hierarchical and hybrid energy storage devices in data centers: Architecture, control and provisioning.

Recently, a new approach has been introduced that leverages and over-provisions energy storage devices (ESDs) in data centers for performing power capping and facilitating capex/opex reductions, without performance overhead. To fully realize the potential benefits of the hierarchical ESD structure, we propose a comprehensive design, control, and provisioning framework including (i) designing power delivery architecture supporting hierarchical ESD structure and hybrid ESDs for some levels, as well as (ii) control and provisioning of the hierarchical ESD structure including run-time ESD charging/discharging control and design-time determination of ESD types, homogeneous/hybrid options, ESD provisioning at each level. Experiments have been conducted using real Google data center workloads based on realistic data center specifications.

A data‐driven approach to modeling power consumption for a hybrid supercomputer

SummaryPower consumption of current High Performance Computing systems has to be reduced by at least one order of magnitude before they can be scaled up towards ExaFLOP performance. While we can expect novel hardware technologies and architectures to contribute towards this goal, significant advances have to come also from software technologies such as proactive and power‐aware scheduling, resource allocation, and fault‐tolerant computing. Development of these software technologies in turn relies heavily on our ability to model and accurately predict power consumption in large computing systems. In this paper, we present a data‐driven model of power consumption for a hybrid supercomputer (which held the top spot in the Green500 ranking in June 2013) that combines CPU, GPU, and MIC technologies to achieve high levels of energy efficiency. Our model takes as input workload characteristics—the number and location of resources that are used by each job at a certain time—and calculates a predicted power consumption at the system level. The model is application‐code‐agnostic and is based solely on a data‐driven predictive approach, where log data describing the past jobs in the system are employed to estimate future power consumption. For this, three different model components are developed and integrated. The first employs support vector regression to predict power usage for jobs before these are started. The second uses a simple heuristic to predict the length of jobs, again before they start. The two predictions are then combined to estimate power consumption due to the job at all computational elements in the system. The third component is a linear model that takes as input the power consumption at the computing units and predicts system‐wide power consumption. Our method achieves highly‐accurate predictions starting solely from workload information and user histories. The model can be applied to power‐aware scheduling and power capping: alternative workload dispatching configurations can be evaluated from a power perspective and more efficient ones can be selected. The methodology outlined here can be easily adapted to other HPC systems where the same types of log data are available.

Fibrinogen Motif Discriminates Platelet and Cell Capture in Peptide-Modified Gold Micropore Arrays.

Human blood platelets and SK-N-AS neuroblastoma cancer-cell capture at spontaneously adsorbed monolayers of fibrinogen-binding motifs, GRGDS (generic integrin adhesion), HHLGGAKQAGDV (exclusive to platelet integrin αIIbβ3), or octanethiol (adhesion inhibitor) at planar gold and ordered 1.6 μm diameter spherical cap gold cavity arrays were compared. In all cases, arginine/glycine/aspartic acid (RGD) promoted capture, whereas alkanethiol monolayers inhibited adhesion. Conversely only platelets adhered to alanine/glycine/aspartic acid (AGD)-modified surfaces, indicating that the AGD motif is recognized preferentially by the platelet-specific integrin, αIIbβ3. Microstructuring of the surface effectively eliminated nonspecific platelet/cell adsorption and dramatically enhanced capture compared to RGD/AGD-modified planar surfaces. In all cases, adhesion was reversible. Platelets and cells underwent morphological change on capture, the extent of which depended on the topography of the underlying substrate. This work demonstrates that both the nature of the modified interface and its underlying topography influence the capture of cancer cells and platelets. These insights may be useful in developing cell-based cancer diagnostics as well as in identifying strategies for the disruption of platelet cloaks around circulating tumor cells.

Frequency Division Based Coordinated Control of Three-Port Converter Interfaced Hybrid Energy Storage Systems in Autonomous DC Microgrids

DC microgrids (MGs) feature remarkable advantages of integrating renewable energy sources and loads with DC coupling. In order to improve the operation performance of a dc MG in both steady and transient states, in this paper a hybrid energy storage system (HESS) interfaced by a three-port converter (TPC) is studied. Particularly, a battery and an ultra-capacitor (UC), which form the HESS, are connected at the source side of the TPC, respectively. Aiming at a phase-shifting controlled full-bridge isolated TPC, in addition to conventional droop control loop, a frequency division-based control method is proposed to achieve rational power sharing between the battery and UC. Due to the characteristics of TPC, virtual inductance and virtual capacitance loops are implemented using the input currents at the battery and UC ports. The frequency division between the battery and UC in the HESS is quantitatively analyzed by using the frequency domain small-signal analysis considering the characteristics of power exchange in the phase-shifting controlled TPC. A simulation model built in MATLAB/Simulink and a prototype comprised of a battery, a UC, a programmable dc load, and auxiliary components are implemented to validate the proposed TPC-interfaced HESS under different operation scenarios.

Implementation of an Energy Management in DSPACE for a Fuel Cell -Ultracapacitor Vehicle

This article presents an energy management of an electric hybrid vehicle using a fuel cell (FC) as the primary energy source and an ultracapacitor (UC) as the auxiliary source. Both energy sources are characterized by a low voltage which is generally not sufficient to be exploited on electrical vehicle. Consequently, using a power converter is required to interface the energy source to the DC bus. For the energy management strategy, it is used to determine the converter current of each source so as to share accurately the power between the two electrical sources, according to the requested power (Traction or braking) and the state of charge of supercapacitor. The proposed method has the capability to minimize the hydrogen consumption and increase the fuel cell time. The suggested algorithm is applied to for the New European Driving Cycle (NEDC) and. implemented in dspace controller. Simulation and experimental results prove the significant reduction of the hydrogen.

Fuel Economy Optimisation by Utilising Hybrid Energy Storage Systems

The onboard energy-storage system (ESS) of hybrid electric vehicles (HEVs) has a significant impact on their fuel efficiency and all-electric range (AER). Energy-storage Devices charge when there is little demand for electricity and discharge when high power requirements that operate as catalysts to boost energy. In ground vehicles, batteries serve as the main energy storage mechanism. Vehicles with an AER of 15% or more almost twice the added expense of the ESS. As the result ESS requires more peak power while maintaining high energy density of HEVs. In comparison to batteries, ultracapacitors (UCs) are the solutions with better power densities. For more advanced hybrid vehicular ESSs, a hybrid ESS made of batteries, UCs, and/or fuel cells (FCs) would be a better choice. Modern energy-storage architectures for HEVs and plug-in HEVs are presented in this work (PHEVs). In this paper, battery, UC, and FC technologies are examined and contrasted. Additionally, different hybrid Also discussed are different hybrid ESSs that integrate two or more storage devices.