Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Anisotropic Mechanical Properties of ABS Parts Fabricated by Fused Deposition Modelling

In recent years, layered manufacturing (LM) processes have begun to progress from rapid prototyping techniques towards rapid manufacturing methods, where the objective is now to produce finished components for potential end use in a product (Caulfield et al., 2007). LM is especially promising for the fabrication of specific need, low volume products such as replacement parts for larger systems. This trend accentuates the need for a thorough understanding of the associated mechanical properties and the resulting behavior of parts produced by layered methods. Not only must the base material be durable, but the mechanical properties of the layered components must be sufficient to meet in-service loading and operational requirements, and be reasonably comparable to parts produced by more traditional manufacturing techniques. This chapter presents the details of a study completed to quantitatively analyze the potential of fused deposition modelling to fully evolve into a rapid manufacturing tool. The project objective is to develop an understanding of the dependence of the mechanical properties of FDM parts on raster orientation and to assess whether these parts are capable of maintaining their integrity while under service loading. The study examines the effect of fiber orientation, i.e. the direction of the polymer beads relative to the loading direction of the part, on a variety of important mechanical properties of ABS components fabricated by fused deposition modeling. Tensile, compressive, flexural, impact, and fatigue strength properties of FDM specimens are examined, evaluated, and placed in context in comparison with the properties of injection molded ABS parts.