Your energy connection

Your energy connection is a South Carolina Energy Office publication on topics related to energy conservation and renewable energy in the state.

On roof geometry for urban wind energy exploitation in high-rise buildings

The European program HORIZON2020 aims to have 20% of electricity produced by renewable sources. The building sector represents 40% of the European Union energy consumption. Reducing energy consumption in buildings is therefore a priority for energy efficiency. The present investigation explores the most adequate roof shapes compatible with the placement of different types of small wind energy generators on high-rise buildings for urban wind energy exploitation. The wind flow around traditional state-of-the-art roof shapes is considered. In addition, the influence of the roof edge on the wind flow on high-rise buildings is analyzed. These geometries are investigated, both qualitatively and quantitatively, and the turbulence intensity threshold for horizontal axis wind turbines is considered. The most adequate shapes for wind energy exploitation are identified, studying vertical profiles of velocity, turbulent kinetic energy and turbulence intensity. Curved shapes are the most interesting building roof shapes from the wind energy exploitation point of view, leading to the highest speed-up and the lowest turbulence intensity.

Compliance in food consumption of young and long-lived elderly of a city in southern Brazil

Introduction: Life expectancy is increasing and becoming a characteristic phenomenon of developed countries and, increasingly, of developing countries, such as Brazil. The aging process causes changes of some physiological functions such as loss of smell, taste, loss of appetite, among other things that end up changing the food intake of these individuals. Objectives: This study aimed to assess food consumption of the young and long-lived elderly in a city in southern Brazil. Methods: A cross-sectional survey conducted through home visits in Palmeira das Missões - RS, Brazil. The sociodemographic, anthropometrical and dietary data were collected through questionnaires and 24-hour recall. The adequacy of nutrients was assessed according to the Dietary Reference Intakes. Data were analyzed using SPSS 18.0 software. Results: The study included 424 older adults, 84,4% (n = 358) aged less than 80 years old and 15,6% (n = 66) older than 80. The intake of energy and protein was insufficient for both young elderly and the oldest. The consumption of vitamins and minerals has been insufficient in all seniors except for iron, which presented an excessive intake. There was a statistically significant difference between the elderly and oldest only for the consumption of lipids and vitamin B12. Conclusion: The majority of studies with elderly corroborate the results found in this article. An inadequate intake of nutrients can develop nutritional deficiencies, and consequently it can result in physiological and pathological changes which would compromise the functional capacity of the elderly. Energy consumption was insufficient and macronutrients were inadequate, both for the young elderly as for the oldest. Additionally, the consumption of vitamins and minerals was insufficient to everyone except the iron, which presented excessive intake for young and oldest elderly.

Holistic Design In High-Speed Optical Interconnects

Integrated circuit scaling has enabled a huge growth in processing capability, which necessitates a corresponding increase in inter-chip communication bandwidth. As bandwidth requirements for chip-to-chip interconnection scale, deficiencies of electrical channels become more apparent. Optical links present a viable alternative due to their low frequency-dependent loss and higher bandwidth density in the form of wavelength division multiplexing. As integrated photonics and bonding technologies are maturing, commercialization of hybrid-integrated optical links are becoming a reality. Increasing silicon integration leads to better performance in optical links but necessitates a corresponding co-design strategy in both electronics and photonics. In this light, holistic design of high-speed optical links with an in-depth understanding of photonics and state-of-the-art electronics brings their performance to unprecedented levels. This thesis presents developments in high-speed optical links by co-designing and co-integrating the primary elements of an optical link: receiver, transmitter, and clocking.

In the first part of this thesis a 3D-integrated CMOS/Silicon-photonic receiver will be presented. The electronic chip features a novel design that employs a low-bandwidth TIA front-end, double-sampling and equalization through dynamic offset modulation. Measured results show -14.9dBm of sensitivity and energy efficiency of 170fJ/b at 25Gb/s. The same receiver front-end is also used to implement source-synchronous 4-channel WDM-based parallel optical receiver. Quadrature ILO-based clocking is employed for synchronization and a novel frequency-tracking method that exploits the dynamics of IL in a quadrature ring oscillator to increase the effective locking range. An adaptive body-biasing circuit is designed to maintain the per-bit-energy consumption constant across wide data-rates. The prototype measurements indicate a record-low power consumption of 153fJ/b at 32Gb/s. The receiver sensitivity is measured to be -8.8dBm at 32Gb/s.

Next, on the optical transmitter side, three new techniques will be presented. First one is a differential ring modulator that breaks the optical bandwidth/quality factor trade-off known to limit the speed of high-Q ring modulators. This structure maintains a constant energy in the ring to avoid pattern-dependent power droop. As a first proof of concept, a prototype has been fabricated and measured up to 10Gb/s. The second technique is thermal stabilization of micro-ring resonator modulators through direct measurement of temperature using a monolithic PTAT temperature sensor. The measured temperature is used in a feedback loop to adjust the thermal tuner of the ring. A prototype is fabricated and a closed-loop feedback system is demonstrated to operate at 20Gb/s in the presence of temperature fluctuations. The third technique is a switched-capacitor based pre-emphasis technique designed to extend the inherently low bandwidth of carrier injection micro-ring modulators. A measured prototype of the optical transmitter achieves energy efficiency of 342fJ/bit at 10Gb/s and the wavelength stabilization circuit based on the monolithic PTAT sensor consumes 0.29mW.

Lastly, a first-order frequency synthesizer that is suitable for high-speed on-chip clock generation will be discussed. The proposed design features an architecture combining an LC quadrature VCO, two sample-and-holds, a PI, digital coarse-tuning, and rotational frequency detection for fine-tuning. In addition to an electrical reference clock, as an extra feature, the prototype chip is capable of receiving a low jitter optical reference clock generated by a high-repetition-rate mode-locked laser. The output clock at 8GHz has an integrated RMS jitter of 490fs, peak-to-peak periodic jitter of 2.06ps, and total RMS jitter of 680fs. The reference spurs are measured to be –64.3dB below the carrier frequency. At 8GHz the system consumes 2.49mW from a 1V supply.

Nano-Engineering of Densely Packed Electrochemical Energy Storage Architectures by Atomic Layer Deposition

Nanostructures are highly attractive for future electrical energy storage devices because they enable large surface area and short ion transport time through thin electrode layers for high power devices. Significant enhancement in power density of batteries has been achieved by nano-engineered structures, particularly anode and cathode nanostructures spatially separated far apart by a porous membrane and/or a defined electrolyte region. A self-aligned nanostructured battery fully confined within a single nanopore presents a powerful platform to determine the rate performance and cyclability limits of nanostructured storage devices. Atomic layer deposition (ALD) has enabled us to create and evaluate such structures, comprised of nanotubular electrodes and electrolyte confined within anodic aluminum oxide (AAO) nanopores. The V2O5- V2O5 symmetric nanopore battery displays exceptional power-energy performance and cyclability when tested as a massively parallel device (~2billion/cm2), each with ~1m3 volume (~1fL). Cycled between 0.2V and 1.8V, this full cell has capacity retention of 95% at 5C rate and 46% at 150C, with more than 1000 charge/discharge cycles. These results demonstrate the promise of ultrasmall, self-aligned/regular, densely packed nanobattery structures as a testbed to study ionics and electrodics at the nanoscale with various geometrical modifications and as a building block for high performance energy storage systems[1, 2]. Further increase of full cell output potential is also demonstrated in asymmetric full cell configurations with various low voltage anode materials. The asymmetric full cell nanopore batteries, comprised of V2O5 as cathode and prelithiated SnO2 or anatase phase TiO2 as anode, with integrated nanotubular metal current collectors underneath each nanotubular storage electrode, also enabled by ALD. By controlling the amount of lithium ion prelithiated into SnO2 anode, we can tune full cell output voltage in the range of 0.3V and 3V. This asymmetric nanopore battery array displays exceptional rate performance and cyclability. When cycled between 1V and 3V, it has capacity retention of approximately 73% at 200C rate compared to 1C, with only 2% capacity loss after more than 500 charge/discharge cycles. With increased full cell output potential, the asymmetric V2O5-SnO2 nanopore battery shows significantly improved energy and power density. This configuration presents a more realistic test - through its asymmetric (vs symmetric) configuration – of performance and cyclability in nanoconfined environment. This dissertation covers (1) Ultra small electrochemical storage platform design and fabrication, (2) Electron and ion transport in nanostructured electrodes inside a half cell configuration, (3) Ion transport between anode and cathode in confined nanochannels in symmetric full cells, (4) Scale up energy and power density with geometry optimization and low voltage anode materials in asymmetric full cell configurations. As a supplement, selective growth of ALD to improve graphene conductance will also be discussed[3]. References: 1. Liu, C., et al., (Invited) A Rational Design for Batteries at Nanoscale by Atomic Layer Deposition. ECS Transactions, 2015. 69(7): p. 23-30. 2. Liu, C.Y., et al., An all-in-one nanopore battery array. Nature Nanotechnology, 2014. 9(12): p. 1031-1039. 3. Liu, C., et al., Improving Graphene Conductivity through Selective Atomic Layer Deposition. ECS Transactions, 2015. 69(7): p. 133-138.

Estudo de reatores eletroquímicos para remoção de Cu2+ , Zn2+, Fenol e BTEX em água produzida

The production of water has become one of the most important wastes in the petroleum industry, specifically in the up stream segment. The treatment of this kind of effluents is complex and normally requires high costs. In this context, the electrochemical treatment emerges as an alternative methodology for treating the wastewaters. It employs electrochemical reactions to increase the capability and efficiency of the traditional chemical treatments for associated produced water. The use of electrochemical reactors can be effective with small changes in traditional treatments, generally not representing a significant additional surface area for new equipments (due to the high cost of square meter on offshore platforms) and also it can use almost the same equipments, in continuous or batch flow, without others high costs investments. Electrochemical treatment causes low environmental impact, because the process uses electrons as reagent and generates small amount of wastes. In this work, it was studied two types of electrochemical reactors: eletroflocculation and eletroflotation, with the aim of removing of Cu2+, Zn2+, phenol and BTEX mixture of produced water. In eletroflocculation, an electrical potential was applied to an aqueous solution containing NaCl. For this, it was used iron electrodes, which promote the dissolution of metal ions, generating Fe2+ and gases which, in appropriate pH, promote also clotting-flocculation reactions, removing Cu2+ and Zn2+. In eletroflotation, a carbon steel cathode and a DSA type anode (Ti/TiO2-RuO2-SnO2) were used in a NaCl solution. It was applied an electrical current, producing strong oxidant agents as Cl2 and HOCl, increasing the degradation rate of BTEX and phenol. Under different flow rates, the Zn2+ was removed by electrodeposition or by ZnOH formation, due the increasing of pH during the reaction. To better understand the electrochemical process, a statistical protocol factor (22) with central point was conducted to analyze the sensitivity of operating parameters on removing Zn2+ by eletroflotation, confirming that the current density affected the process negatively and the flow rate positively. For economical viability of these two electrochemical treatments, the energy consumption was calculated, taking in account the kWh given by ANEEL. The treatment cost obtained were quite attractive in comparison with the current treatments used in Rio Grande do Norte state. In addition, it could still be reduced for the case of using other alternative energy source such as solar, wind or gas generated directly from the Petrochemical Plant or offshore platforms

Estudo paramétrico da recuperação de petróleo pesado por aquecimento eletromagnético resistivo

Electrical resistive heating (ERH) is a thermal method used to improve oil recovery. It can increase oil rate and oil recovery due to temperature increase caused by electrical current passage through oil zone. ERH has some advantage compared with well-known thermal methods such as continuous steam flood, presenting low-water production. This method can be applied to reservoirs with different characteristics and initial reservoir conditions. Commercial software was used to test several cases using a semi-synthetic homogeneous reservoir with some characteristics as found in northeast Brazilian basins. It was realized a sensitivity analysis of some reservoir parameters, such as: oil zone, aquifer presence, gas cap presence and oil saturation on oil recovery and energy consumption. Then it was tested several cases studying the electrical variables considered more important in the process, such as: voltage, electrical configurations and electrodes positions. Energy optimization by electrodes voltage levels changes and electrical settings modify the intensity and the electrical current distribution in oil zone and, consequently, their influences in reservoir temperature reached at some regions. Results show which reservoir parameters were significant in order to improve oil recovery and energy requirement in for each reservoir. Most significant parameters on oil recovery and electrical energy delivered were oil thickness, presence of aquifer, presence of gas cap, voltage, electrical configuration and electrodes positions. Factors such as: connate water, water salinity and relative permeability to water at irreducible oil saturation had low influence on oil recovery but had some influence in energy requirements. It was possible to optimize energy consumption and oil recovery by electrical variables. Energy requirements can decrease by changing electrodes voltages during the process. This application can be extended to heavy oil reservoirs of high depth, such as offshore fields, where nowadays it is not applicable any conventional thermal process such as steam flooding

Energy Efficiency of Software Transactional Memory in a Heterogeneous Architecture

Hardware vendors make an important effort creating low-power CPUs that keep battery duration and durability above acceptable levels. In order to achieve this goal and provide good performance-energy for a wide variety of applications, ARM designed the big.LITTLE architecture. This heterogeneous multi-core architecture features two different types of cores: big cores oriented to performance and little cores, slower and aimed to save energy consumption. As all the cores have access to the same memory, multi-threaded applications must resort to some mutual exclusion mechanism to coordinate the access to shared data by the concurrent threads. Transactional Memory (TM) represents an optimistic approach for shared-memory synchronization. To take full advantage of the features offered by software TM, but also benefit from the characteristics of the heterogeneous big.LITTLE architectures, our focus is to propose TM solutions that take into account the power/performance requirements of the application and what it is offered by the architecture. In order to understand the current state-of-the-art and obtain useful information for future power-aware software TM solutions, we have performed an analysis of a popular TM library running on top of an ARM big.LITTLE processor. Experiments show, in general, better scalability for the LITTLE cores for most of the applications except for one, which requires the computing performance that the big cores offer.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization

Catering to society’s demand for high performance computing, billions of transistors are now integrated on IC chips to deliver unprecedented performances. With increasing transistor density, the power consumption/density is growing exponentially. The increasing power consumption directly translates to the high chip temperature, which not only raises the packaging/cooling costs, but also degrades the performance/reliability and life span of the computing systems. Moreover, high chip temperature also greatly increases the leakage power consumption, which is becoming more and more significant with the continuous scaling of the transistor size. As the semiconductor industry continues to evolve, power and thermal challenges have become the most critical challenges in the design of new generations of computing systems. In this dissertation, we addressed the power/thermal issues from the system-level perspective. Specifically, we sought to employ real-time scheduling methods to optimize the power/thermal efficiency of the real-time computing systems, with leakage/ temperature dependency taken into consideration. In our research, we first explored the fundamental principles on how to employ dynamic voltage scaling (DVS) techniques to reduce the peak operating temperature when running a real-time application on a single core platform. We further proposed a novel real-time scheduling method, “M-Oscillations” to reduce the peak temperature when scheduling a hard real-time periodic task set. We also developed three checking methods to guarantee the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research from single core platform to multi-core platform. We investigated the energy estimation problem on the multi-core platforms and developed a light weight and accurate method to calculate the energy consumption for a given voltage schedule on a multi-core platform. Finally, we concluded the dissertation with elaborated discussions of future extensions of our research.

System-on-a-Chip (SoC) based Hardware Acceleration in Register Transfer Level (RTL) Design

Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.

Frequency adjustable MEMS vibration energy harvester

Ambient mechanical vibrations offer an attractive solution for powering the wireless sensor nodes of the emerging "Internet-of-Things". However, the wide-ranging variability of the ambient vibration frequencies pose a significant challenge to the efficient transduction of vibration into usable electrical energy. This work reports the development of a MEMS electromagnetic vibration energy harvester where the resonance frequency of the oscillator can be adjusted or tuned to adapt to the ambient vibrational frequency. Micro-fabricated silicon spring and double layer planar micro-coils along with sintered NdFeB micro-magnets are used to construct the electromagnetic transduction mechanism. Furthermore, another NdFeB magnet is adjustably assembled to induce variable magnetic interaction with the transducing magnet, leading to significant change in the spring stiffness and resonance frequency. Finite element analysis and numerical simulations exhibit substantial frequency tuning range (25% of natural resonance frequency) by appropriate adjustment of the repulsive magnetic interaction between the tuning and transducing magnet pair. This demonstrated method of frequency adjustment or tuning have potential applications in other MEMS vibration energy harvesters and micromechanical oscillators.

An empirical investigation of the impact of global energy transition on Nigerian oil and gas exports

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