Comparing Measured and Satellite-Derived Surface Irradiance

The purpose of this study is two-fold: 1) To examine the performance of the Global Solar Insolation Project (GSIP) physics-based model in characterizing global horizontal solar radiation across the United States by comparing to the ground measured data, and 2) to examine improvements of the GSIP data to address temporal and spatial variations. The study enumerates and examines the spatial and temporal limitations of the GSIP model. Most comparisons demonstrate relatively good statistical agreement. However, the methodology used in the satellite model to distinguish microclimate conditions presents significant challenges, and the model requires refinement in addressing aerosol estimates, water vapor estimates, and clear sky optical properties. Satellite derived datasets are only available at half-hour intervals. Surface measurement can easily be made at temporal resolution in the order of seconds. Therefore intra-hour variability, an important quantity for understanding how power production in power plants will vary, cannot be directly derived from satellites. This paper illustrates how intra-hour variability in ground measurements cannot be captured by the satellite based datasets. We also discuss the potential for improved next-generation geostationary satellite data to improve the accuracy of surface radiation estimates.

Generative Textiles for Non-Rotary Power Production From Wind

The U.S. Army Engineer Research and Development Center, Construction Engineering Research Laboratory (ERDC-CERL) is developing a new class of flexible, generative textile as a novel means of sustainable wind energy generation. Flexible, generative carbon nanotube (CNT)-based textiles may have excellent potential for electrical capacitive storage and reuse in conjunction with small-scale energy-harvesting systems, both from wind for fixed applications and from human locomotion. This paper describes the design and optimization of a three-layer generative textile composed of discrete layers for generation, distribution, and storage. Initial results suggest that improvement in the generation layer will provide the highest increase in overall performance. The output of the electromagnetic tests shows a power density of 0.17 mW/cm3. However, the efficiency can be significantly improved through increasing the voltage output of the generation layer from 20 mV to around 1V. In an analysis of the operational envelope, wind data collected locally at ERDC-CERL and at other sites around the world reveal close similarity in the probability distributions, which could allow for a practical engineering approach capable of harvesting the steady “ram” component in addition to a variable energy component of the wind. To further study the textile-wind interactions, a wind simulation environment is being developed and has been able to obtain reproducible wind speed data thus far.

Numerical Analysis of Latent Thermal Energy Storage System With Embedded Thermosyphons

Latent thermal energy storage (LTES) system offers high energy storage density and nearly isothermal operation for concentrating solar power generation. However, the low thermal conductivity possessed by the phase change material (PCM) used in LTES system limits the heat transfer rates. Utilizing thermosyphons to charge or discharge a LTES system offers a promising engineering solution to compensate for the low thermal conductivity of the PCM. The present work numerically investigates the enhancement in the thermal performance of charging and discharging process of LTES system by embedding thermosyphons. A transient, computational analysis of the LTES system with embedded thermosyphons is performed for both charging and discharging cycles. The influence of the design configuration of the system and the arrangement of the thermosyphons on the charge and discharge performance of the LTES installed in a concentrating solar power plant (CSP) is analyzed to identify configurations that lead to improved effectiveness.

Geometric and Material Optimization of Vortex-Induced Vibration Micro Energy Harvesters for Localized Wind Environments

Wind energy capture in today’s environment is often focused on producing large amounts of power through massive turbines operating at high wind speeds. The device presented by the authors performs on the extreme opposite scale of these large wind turbines. Utilizing vortex induced vibration combined with developed and demonstrated piezoelectric energy harvesting techniques, the device produces power consistent with peer technologies in the rapidly growing field of micro-energy harvesting. Vortex-induced vibrations in the Karman vortex street are the catalyst for energy production of the device. To optimize power output, resonant frequency of the harvester is matched to vortex shedding frequency at a given wind speed, producing a lock-on effect that results in the greatest amplitude of oscillation. The frequency of oscillation is varied by altering the effective spring constant of the device, thereby allowing for “tuning” of the device to specific wind environments. While localized wind conditions are never able to be predicted with absolute certainty, patterns can be established through thorough data collection. Sampling of local wind conditions led to the design and testing of harvesters operating within a range of wind velocities between approximately 4 mph and 25 mph. For the extremities of this range, devices were constructed with resonant frequencies of approximately 17 and 163 Hz. Frequency variation was achieved through altering the material composition and geometry of the energy harvester. Experimentation was performed on harvesters to determine power output at optimized fluid velocity, as well as above and below. Analysis was also conducted on shedding characteristics of the device over the tested range of wind velocities. Computational modeling of the device is performed and compared to experimentally produced data.

Numerical Simulation and Optimization of CO2 Sequestration in Saline Aquifers

With recent concerns on CO2 emissions from coal fired electricity generation plants; there has been major emphasis on the development of safe and economical Carbon Dioxide Capture and Sequestration (CCS) technology worldwide. Saline reservoirs are attractive geological sites for CO2 sequestration because of their huge capacity for sequestration. Over the last decade, numerical simulation codes have been developed in U.S, Europe and Japan to determine a priori the CO2 storage capacity of a saline aquifer and provide risk assessment with reasonable confidence before the actual deployment of CO2 sequestration can proceed with enormous investment. In U.S, TOUGH2 numerical simulator has been widely used for this purpose. However at present it does not have the capability to determine optimal parameters such as injection rate, injection pressure, injection depth for vertical and horizontal wells etc. for optimization of the CO2 storage capacity and for minimizing the leakage potential by confining the plume migration. This paper describes the development of a “Genetic Algorithm (GA)” based optimizer for TOUGH2 that can be used by the industry with good confidence to optimize the CO2 storage capacity in a saline aquifer of interest. This new code including the TOUGH2 and the GA optimizer is designated as “GATOUGH2”. It has been validated by conducting simulations of three widely used benchmark problems by the CCS researchers worldwide: (a) Study of CO2 plume evolution and leakage through an abandoned well, (b) Study of enhanced CH4 recovery in combination with CO2 storage in depleted gas reservoirs, and (c) Study of CO2 injection into a heterogeneous geological formation. Our results of these simulations are in excellent agreement with those of other researchers obtained with different codes. The validated code has been employed to optimize the proposed water-alternating-gas (WAG) injection scheme for (a) a vertical CO2 injection well and (b) a horizontal CO2 injection well, for optimizing the CO2 sequestration capacity of an aquifer. These optimized calculations are compared with the brute force nearly optimized results obtained by performing a large number of calculations. These comparisons demonstrate the significant efficiency and accuracy of GATOUGH2 as an optimizer for TOUGH2. This capability holds a great promise in studying a host of other problems in CO2 sequestration such as how to optimally accelerate the capillary trapping, accelerate the dissolution of CO2 in water or brine, and immobilize the CO2 plume.

A Direct-Steam Linear Fresnel Performance Model for NREL’S System Advisor Model

This paper presents the technical formulation and demonstrated model performance results of a new direct-steam-generation (DSG) model in NREL’s System Advisor Model (SAM). The model predicts the annual electricity production of a wide range of system configurations within the DSG Linear Fresnel technology by modeling hourly performance of the plant in detail. The quasi-steady-state formulation allows users to investigate energy and mass flows, operating temperatures, and pressure drops for geometries and solar field configurations of interest. The model includes tools for heat loss calculation using either empirical polynomial heat loss curves as a function of steam temperature, ambient temperature, and wind velocity, or a detailed evacuated tube receiver heat loss model. Thermal losses are evaluated using a computationally efficient nodal approach, where the solar field and headers are discretized into multiple nodes where heat losses, thermal inertia, steam conditions (including pressure, temperature, enthalpy, etc.) are individually evaluated during each time step of the simulation. This paper discusses the mathematical formulation for the solar field model and describes how the solar field is integrated with the other subsystem models, including the power cycle and optional auxiliary fossil system. Model results are also presented to demonstrate plant behavior in the various operating modes.

Distributed Generation for Village of Hope

The Village of Hope is an orphan community located in rural Zambia. The community is made up of several buildings of a variety of uses and schedules. They are currently tied to the grid, which is unreliable due to rolling blackouts for 2 to 4 hours per day. The community is looking for a financially beneficial solution to their electrical needs. A system optimization and sensitivity analysis was performed to determine system recommendations for the community. It was found that wind turbine systems supplementing a grid connection is the most realistic solution for the Village of Hope. However, there were many other factors identified that require further analysis to be able to truly optimize the system.

Maximum Power From Fluid Flow: Results From the First and Second Laws of Thermodynamics

The heat transfer principle of power maximization in power plants with heat transfer irreversibilities was cleverly extended by Bejan [1] to fluid flow, by obtaining that the energy conversion efficiency at maximum power is ηmax = 1/2(1 − P2/P1). This result is analog to the efficiency at maximum power for power plants, ηmax = 1 − (T2/T1)1/2 which was deduced by Curzon and Ahlborn [2]. In this paper, the analysis to obtain maximum power output delivered from a piston between two pressure reservoir across linear flow resistance is generalized by considering the piston cylinder friction, by obtaining relations of maximum power output and optimal speed of the piston in terms of first law efficiency. Expressions to relate the power output, cross sectional area of the chamber and first law efficiency, were deduced in order to evaluate the influence of the overall size constraints and fluid regime in the performance of the piston cylinder system. Flow in circular ducts and developed laminar flow between parallel plates, are considered to demonstrate that when two pressure reservoirs oriented in counterflow, with different and arbitrary cross sectional area, must have the same area in order to maximize the power output of the system. These results introduce some modifications to the results obtained by Bejan [1] and Chen [3]. This paper extends the Bejan and Chen’s work by estimating under turbulent regime the lost available work rate associated with the degree of irreversibilities caused by the flow resistances of the system. This analysis is equivalent to evaluate the irreversibilities in an endoirreversible Carnot heat engine model caused by the heat resistance loss between the engine and its surrounding heat reservoirs. This paper concludes with an application to illustrate the practical applications by estimating the lost available work of an actual steady-flow turbine and the layout pipes upstream and downstream of the same device.

Absorber Alignment Measurement Tool for Solar Parabolic Trough Collectors

As we pursue efforts to lower the capital and installation costs of parabolic trough solar collectors, it is essential to maintain high optical performance. While there are many optical tools available to measure the reflector slope errors of parabolic trough solar collectors, there are few tools to measure the absorber alignment. A new method is presented here to measure the absorber alignment in two dimensions to within 0.5 cm. The absorber alignment is measured using a digital camera and four photogrammetric targets. Physical contact with the receiver absorber or glass is not necessary. The alignment of the absorber is measured along its full length so that sagging of the absorber can be quantified with this technique. The resulting absorber alignment measurement provides critical information required to accurately determine the intercept factor of a collector.

Optimization Under Uncertainty: A Case Study of a Solar Absorption Cooling and Heating System for a Medium-Sized Office Building in Atlanta

Solar absorption cooling and heating (SACH) systems currently still stay at development and demonstration stage due to the nature of the complex system. It is critical for practitioners and engineers to have a correct and complete performance analyses and evaluation for SACH systems with respects of energy, economics, and environment. Optimization is necessarily involved to find the optimal system design by considering these three aspects. However, many assumptions made in the optimization are sensitive to the energy, economic, and environmental variations, and thus the optimization results will be affected. Therefore, the sensitivity and uncertainty analysis is important and necessary to make optimization robust. This paper uses a case study to explore the influence of the uncertainties on the SACH system optimization results. The case is a SACH system for a medium size office building in Atlanta. The one parameter at a time (OAT) sensitivity analysis method was applied firstly to determine the most sensitive inputs. Monte Carlo statistical method was utilized to generate the data sets for uncertainty analysis. The optimization problem under uncertainty was then formulated and solved. Due to the uncertainty associated with system inputs, the optimization solutions were found with certain types of the distributions. In addition, the scenario analysis on electricity price does not show large sensitivity to the objectives.