A Fuzzy-PSO Based Controller for a Grid Independent Photovoltaic System

This paper presents a particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for a photovoltaic (PV) grid independent system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). PSO is used to optimize both the membership functions and the rule set in the design of the FLC. Optimizing the PV system controller yields improved performance, allowing the system to meet more of the loads and keep a higher average state of battery charge. Potential benefits of an optimized controller include lower costs through smaller system sizing and a longer battery lif

Comparison of Two Optimal Control Strategies for a Grid Independent Photovoltaic System

This paper presents two optimal control strategies for a grid independent photovoltaic system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). The first strategy is based on Action Dependent Heuristic Dynamic Programming (ADHDP), a model-free adaptive critic design (ACD) technique which optimizes the control performance based on a utility function. ADHDP critic network is used in a PV system simulation study to train an action neural network (optimal neurocontroller) to provide optimal control for varying PV system output energy and loadings. The second optimal control strategy is based on a fuzzy logic controller with its membership functions optimized using the particle swarm optimization. The emphasis of the optimal controllers is primarily to supply the critical base load at all times, thus requiring sufficient stored energy during times of less or no solar insolation. Simulation results are presented to compare the performance of the proposed optimal controllers with the conventional priority control scheme. Results show that the ADHDP based controller performs better than the optimized fuzzy controller, and the optimized fuzzy controller performs better than the standard PV-priority controller

HDP Based Optimal Control of a Grid Independent PV System

This paper presents an adaptive optimal control scheme for a grid independent photovoltaic (PV) system consisting of a PV collector array, a storage battery, and loads (critical and non-critical loads). The optimal control algorithm is based on the model-free heuristic dynamic programming (HDP), an adaptive critic design (ACD) technique which optimizes the control performance based on a utility function. The HDP critic network is used in a PV system simulation study to train a neurocontroller to provide optimal control for varying PV system output energy and load demands. The emphasis of the optimal controller is primarily to supply the critical base load demand at all times. Simulation results are presented to compare the performance of the proposed optimal scheme with the conventional priority control scheme. Results show that HDP based control scheme performs better than a conventional priority control scheme

Optimal Control of a Photovoltaic Solar Energy System with Adaptive Critics

This paper presents an optimal energy control scheme for a grid independent photovoltaic (PV) solar system consisting of a PV array, battery energy storage, and time varying loads (a small critical load and a larger variable non-critical load). The optimal controller design is based on a class of adaptive critic designs (ACDs) called the action dependant heuristic dynamic programming (ADHDP). The ADHDP class of ACDs uses two neural networks, an action network (which actually dispenses the control signals) and a critic network (which critics the action network performance). An optimal control policy is evolved by the action network over a period of time using the feedback signals provided by the critic network. The objectives of the optimal controller in order of decreasing importance is to first fully dispatch the required energy to the critical loads at all times; secondly to dispatch energy to the battery whenever necessary so as to be able to dispatch energy to the critical loads in any absence of energy from the PV array; and lastly to dispatch energy to the non-critical loads while not interfering with the first two objectives. Results on three different US cities show that the ADHDP based optimal control scheme outperforms the conventional PV-priority control scheme in maintaining the stated objectives almost all the time

On the Interpretation of Supernova Light Echo Profiles and Spectra

The light echo systems of historical supernovae in the Milky Way and local group galaxies provide an unprecedented opportunity to reveal the effects of asymmetry on observables, particularly optical spectra. Scattering dust at different locations on the light echo ellipsoid witnesses the supernova from different perspectives and the light consequently scattered towards Earth preserves the shape of line profile variations introduced by asymmetries in the supernova photosphere. However, the interpretation of supernova light echo spectra to date has not involved a detailed consideration of the effects of outburst duration and geometrical scattering modifications due to finite scattering dust filament dimension, inclination, and image point-spread function and spectrograph slit width. In this paper, we explore the implications of these factors and present a framework for future resolved supernova light echo spectra interpretation, and test it against Cas A and SN 1987A light echo spectra. We conclude that the full modeling of the dimensions and orientation of the scattering dust using the observed light echoes at two or more epochs is critical for the correct interpretation of light echo spectra. Indeed, without doing so one might falsely conclude that differences exist when none are actually present.Comment: 18 pages, 22 figures, accepted for publication in Ap

DYNAMICS OF THE GALACTIC GLOBULAR CLUSTER NGC 3201

B,V CCD frames have been used to derive surface brightness profiles for NGC 3201 out to ~18 arcmin. A total of 857 radial velocities with median precision ~1 km/s for 399 member giants have been used to trace the velocity dispersion profile out to 32' (the approximate tidal radius from fits of single-mass, isotropic King-Michie models to the cluster surface brightness profiles). The median difference in radial velocity for stars on either side of an imaginary axis moved through the cluster in 1 degree steps shows a significant maximum amplitude of 1.22+/-0.25 km/s. We discuss possible explanations of this result, including: (1) cluster rotation; (2) preferential stripping of stars on prograde orbits near the limiting radius; (3) the projection of the cluster space velocity onto the plane of the sky and (4) a slight drift in the velocity zero point. It is difficult to identify the primary cause of the observed velocity field structure unambiguously, and we suspect that all of the above processes may play a role. The B,V surface brightness profiles and radial velocities have been modeled with single- & multi-mass King-Michie models and nonparametric techniques. The density and M/L profiles show good agreement over 1.5<R<10 pc, and both approaches suggest a steady rise in M/L with distance from the cluster center. Due to the low cluster luminosity, we are unable to place useful constraints on the anisotropy of the velocity dispersion profile, though the global mass-to-light ratio is well-constrained by the models as ~2.0 +/-0.2 for the multi-mass and nonparametric models, compared to ~ 1.65 +/-0.15 for models having equal-mass stars. Our best-fit, multi-mass models have mass function slopes of x~0.75 +/-0.25, consistent with findings that mass function depends on the position relative to the potential of the Galaxy.Comment: uuencoded compressed Postscript, 59 pages including 10 figures. Also available at http://www.dao.nrc.ca/DAO/SCIENCE/science.htm

Comparison of Feedforward and Feedback Neural Network Architectures for Short Term Wind Speed Prediction

This paper compares three types of neural networks trained using particle swarm optimization (PSO) for use in the short term prediction of wind speed. The three types of neural networks compared are the multi-layer perceptron (MLP) neural network, Elman recurrent neural network, and simultaneous recurrent neural network (SRN). Each network is trained and tested using meteorological data of one week measured at the National Renewable Energy Laboratory National Wind Technology Center near Boulder, CO. Results show that while the recurrent neural networks outperform the MLP in the best and average case with a lower overall mean squared error, the MLP performance is comparable. The better performance of the feedback architectures is also shown using the mean absolute relative error. While the SRN performance is superior, the increase in required training time for the SRN over the other networks may be a constraint, depending on the application

Primary Beam Shape Calibration from Mosaicked, Interferometric Observations

Image quality in mosaicked observations from interferometric radio telescopes is strongly dependent on the accuracy with which the antenna primary beam is calibrated. The next generation of radio telescope arrays such as the Allen Telescope Array (ATA) and the Square Kilometer Array (SKA) have key science goals that involve making large mosaicked observations filled with bright point sources. We present a new method for calibrating the shape of the telescope's mean primary beam that uses the multiple redundant observations of these bright sources in the mosaic. The method has an analytical solution for simple Gaussian beam shapes but can also be applied to more complex beam shapes through $\chi^2$ minimization. One major benefit of this simple, conceptually clean method is that it makes use of the science data for calibration purposes, thus saving telescope time and improving accuracy through simultaneous calibration and observation. We apply the method both to 1.43 GHz data taken during the ATA Twenty Centimeter Survey (ATATS) and to 3.14 GHz data taken during the ATA's Pi Gigahertz Sky Survey (PiGSS). We find that the beam's calculated full width at half maximum (FWHM) values are consistent with the theoretical values, the values measured by several independent methods, and the values from the simulation we use to demonstrate the effectiveness of our method on data from future telescopes such as the expanded ATA and the SKA. These results are preliminary, and can be expanded upon by fitting more complex beam shapes. We also investigate, by way of a simulation, the dependence of the accuracy of the telescope's FWHM on antenna number. We find that the uncertainty returned by our fitting method is inversely proportional to the number of antennas in the array.Comment: Accepted by PASP. 8 pages, 8 figure