Trade-off Curves and Elasticity Analysis in Multi Fuel Options System and Combined Problem

Recent environmental concerns and policies have reformulated the traditional economic dispatch problem by including the emission impacts in the mathematical model.  The combined economic and emission dispatch problem is a multi-objective non-linear optimization problem. This paper presents a method to consider the fuel costs and environmental emissions simultaneously. The -constraint method for bi-objective optimization has been used to generate Pareto front. Furthermore, trade-off curves have been developed for different types of emission. The elasticity of cost with respect to the emission (say, emission elasticity) has been estimated for all Pareto optimal points and different types of emissions that provides invaluable information for the system operator to run the system with sufficient flexibility subject to technical constraints while the operator has multi fuel options. Moreover, the emission elasticity is effective tool for competition in the electricity market. The Iranian Electricity Market is considered as empirical evidence. Keywords: Combined economic-emission dispatch, Emission elasticity, Iranian electricity market, Multi objective optimization model, ε-Constraint. JEL Classifications:  C6, F64, P48,

多目的最適設計におけるトレードオフ分析法

金沢大学理工研究域機械工学系The aims of the multi-objective design optimization are to find the pareto optimal solutions, and are also to analyze the trade-off between the objectives. The interactive multi-objective design optimization based on the Satisficing Trade-Off Method (STOM) is used in this paper. Especially, the trade-off matrix to analyze the trade-off between objectives quantitatively is introduced. Each element of trade-off matrix consists of the projection matrix of active constraints and the gradient of objective functions. Additionally, it is possible to determine the new aspiration level by using the trade-off matrix. To obtain the new aspiration level, the compromise point and solution are defined by using the trade-off ratio. To obtain the compromise point, the designer input the trade-off ratio between objectives and can obtain the new aspiration level. It is also possible to apply the trade-off matrix to the automatic trade-off method, which is a method to determine the new aspiration level. Through basic numerical examples, the validity is examined

A Novel Analysis Framework for Evaluating Predisposition of Design Solutions through the Creation of Hereditary-Amelioration Networks Derived from the Dynamics within an Evolutionary Optimizer

In early-stage design, critical decisions are made within a limited information environment. Designers conduct and interpret analyses, while considering any associated risks, so that meaningful design trade-offs can be investigated. To aid in this, design tools are utilized to generate solutions in the hopes of characterizing a design space. However, while it is known that solutions are prescribed by the tools used to generate them, there seems to be little concern toward how these predisposed biases affect the quality of solutions relative to the desired outcome. Without the ability to determine a tool's biases, one cannot understand their effects on decision-making. This inability can promote inaccurate perspectives of the desired design space, can negatively impact the ultimate success of the design, and poses a currently unquantified risk within the design process. To make truly informed decisions, designers must be able to assess a tool's inherent biases, its intended applications, and its contextual appropriateness to the design questions it is being used to answer. To provide these capabilities, this thesis presents a framework for evaluating a model's underlying biases. Within this thesis, new and novel aspects of quality have been developed, namely solution-centric quality and generative quality. Novel quality metrics have been created and are used to evaluate a model as it is subjected to biases. A modified Genetic Algorithm (GA) has been developed so that an ensemble of biased solutions can be generated over time. Thereby, this GA provides a dynamic environment of the solution generation process associated with a model. Additionally, newly created and novel Hereditary-Amelioration Networks (HANs) are derived from the dynamics within this modified GA. The HANs capture the implied-causality behind solution dynamics and represent temporal, causal relationships between solutions. This newly developed approach is used to establish the comparative context necessary for a model's biases to be analyzed and understood by creating reference and biasing cases. Utilizing the developed framework, a variety of solution-centric and generative analyses are developed to evaluate a model's inherent tendencies. A comprehensive case study is conducted to demonstrate how the framework and the various analyses are implemented and interpreted. The case study's results demonstrate that the framework can successfully identify a model's biases, providing designers with the contextual information necessary to make truly informed decisions.PHDNaval Architecture & Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153389/1/mjsyp_1.pd

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs

Virginia Commonwealth University Graduate and Professional Programs Bulletin Courses

Listing of professional and graduate courses for 2013-2014

Virginia Commonwealth University Graduate Bulletin

Graduate bulletin for Virginia Commonwealth University for the academic year 2016-2017. It includes information on academic regulations, degree requirements, course offerings, faculty, academic calendar, and tuition and expenses for graduate programs

Virginia Commonwealth University Bulletin All Courses

Listing of undergraduate, professional, and graduate courses for 2005-200