Search results for: Brandon Foggo
3 A Comprehensive Evaluation of Supervised Machine Learning for the Phase Identification Problem
Authors: Brandon Foggo, Nanpeng Yu
Abstract:
Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10752 Enhanced Performance of an All-Vanadium Redox Flow Battery Employing Graphene Modified Carbon Paper Electrodes
Authors: Barun Chakrabarti, Dan Nir, Vladimir Yufit, P. V. Aravind, Nigel Brandon
Abstract:
Fuel cell grade gas-diffusion layer carbon paper (CP) electrodes are subjected to electrophoresis in N,N’-dimethylformamide (DMF) consisting of reduced graphene oxide (rGO). The rGO modified electrodes are compared with CP in a single asymmetric all-vanadium redox battery system (employing a double serpentine flow channel for each half-cell). Peak power densities improved by 4% when the rGO deposits were facing the ion-exchange membrane (cell performance was poorer when the rGO was facing the flow field). Cycling of the cells showed least degradation of the CP electrodes that were coated with rGO in comparison to pristine samples.Keywords: All-vanadium redox flow batteries, carbon paper electrodes, electrophoretic deposition, reduced graphene oxide.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17441 Economic effects and Energy Use Efficiency of Incorporating Alfalfa and Fertilizer into Grass- Based Pasture Systems
Authors: M. Khakbazan, S. L. Scott, H. C. Block, C. D. Robins, W. P. McCaughey
Abstract:
A ten-year grazing study was conducted at the Agriculture and Agri-Food Canada Brandon Research Centre in Manitoba to study the effect of alfalfa inclusion and fertilizer (N, P, K, and S) addition on economics and efficiency of non-renewable energy use in meadow brome grass-based pasture systems for beef production. Fertilizing grass-only or alfalfa-grass pastures to full soil test recommendations improved pasture productivity, but did not improve profitability compared to unfertilized pastures. Fertilizing grass-only pastures resulted in the highest net loss of any pasture management strategy in this study. Adding alfalfa at the time of seeding, with no added fertilizer, was economically the best pasture improvement strategy in this study. Because of moisture limitations, adding commercial fertilizer to full soil test recommendations is probably not economically justifiable in most years, especially with the rising cost of fertilizer. Improving grass-only pastures by adding fertilizer and/or alfalfa required additional non-renewable energy inputs; however, the additional energy required for unfertilized alfalfa-grass pastures was minimal compared to the fertilized pastures. Of the four pasture management strategies, adding alfalfa to grass pastures without adding fertilizer had the highest efficiency of energy use. Based on energy use and economic performance, the unfertilized alfalfa-grass pasture was the most efficient and sustainable pasture system.Keywords: Alfalfa, grass, fertilizer, pasture systems, economics, energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1676