9,421 research outputs found
A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1
A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system
Energy Management of Prosumer Communities
The penetration of distributed generation, energy storages and smart loads has resulted in the emergence of prosumers: entities capable of adjusting their electricity production and consumption in order to meet environmental goals and to participate profitably in the available electricity markets. Significant untapped potential remains in the exploitation and coordination of small and medium-sized distributed energy resources. However, such resources usually have a primary purpose, which imposes constraints on the exploitation of the resource; for example, the primary purpose of an electric vehicle battery is for driving, so the battery could be used as temporary storage for excess photovoltaic energy only if the vehicle is available for driving when the owner expects it to be. The aggregation of several distributed energy resources is a solution for coping with the unavailability of one resource. Solutions are needed for managing the electricity production and consumption characteristics of diverse distributed energy resources in order to obtain prosumers with more generic capabilities and services for electricity production, storage, and consumption. This collection of articles studies such prosumers and the emergence of prosumer communities. Demand response-capable smart loads, battery storages and photovoltaic generation resources are forecasted and optimized to ensure energy-efficient and, in some cases, profitable operation of the resources
Contributions to sustainable urban transport : decision support for alternative mobility and logistics concepts
Increasing transport activities in cities are a substantial driver for congestion and pollution, influencing urban populations’ health and quality of life. These effects are consequences of ongoing urbanization in combination with rising individual demand for mobility, goods, and services. With the goal of increased environmental sustainability in urban areas, city authorities and politics aim for reduced traffic and minimized transport emissions.
To support more efficient and sustainable urban transport, this cumulative dissertation focuses on alternative transport concepts. For this purpose, scientific methods and models of the interdisciplinary information systems domain combined with elements of operations research, transportation, and logistics are developed and investigated in multiple research contributions. Different transport concepts are examined in terms of optimization and acceptance to provide decision support for relevant stakeholders. In more detail, the overarching topic of urban transport in this dissertation is divided into the complexes urban mobility (part A) in terms of passenger transport and urban logistics (part B) with a focus on the delivery of goods and services. Within part A, approaches to carsharing optimization are presented at various planning levels. Furthermore, the user acceptance of ridepooling is investigated. Part B outlines several optimization models for alternative urban parcel and e-grocery delivery concepts by proposing different network structures and transport vehicles. Conducted surveys on intentional use of urban logistics concepts give valuable hints to providers and decision makers.
The introduced approaches with their corresponding results provide target-oriented support to facilitate decision making based on quantitative data. Due to the continuous growth of urban transport, the relevance of decision support in this regard, but also the understanding of the key drivers for people to use certain services will further increase in the future. By providing decision support for urban mobility as well as urban logistics concepts, this dissertation contributes to enhanced economic, social, and environmental sustainability in urban areas
On the Variance of Electricity Prices in Deregulated Markets
Since 1990 many countries have started a deregulation process in the electricity wholesale market with a view to gaining in efficiency, lowering prices and encouraging investments. In most of the markets these objectives have been accomplished, but at the same time, prices have shown high volatility. This is mainly due to certain unique characteristics of electricity as a commodity: it cannot be easily stored; and the flow across lines is dependent on the laws of physics. Electricity must be delivered on the spot to the load.Electricity price variance has been studied very little. Variance is important for constructing prediction intervals for the price. And it is a key factor in pricing derivatives, which are used for energy risk management purposes.A fundamental bid-based stochastic model is presented to predict electricity hourly prices and average price in a given period. The model captures both the economic and physical aspects of the pricing process, considering two sources of uncertainty: availability of theunits and demand. This work is based on three oligopoly models -Bertrand, Cournot and Supply Function Equilibrium (SFE) - and obtains closed form expressions for expected value and variance of electricity hourly prices and average price.Sensitivity analysis is performed on the number of firms, anticipated peak demand and price elasticity of demand. It turns out that as the number of firms in the market decreases, the expected values increase by a significant amount, especially for the Cournot model. Variances for Cournot model also increase. But the variances for SFE model decrease, taking even smaller values than Bertrand's.Price elasticity of demand severely affects expected values and variances in the Cournot model. So does the firms' anticipated peak demand with respect to full installed capacity in the SFE model. Market design and market rules should take these two parameters into account.Finally, a refinement of the models is used to investigate to what extent prices can be more accurately predicted when temperature forecast is at hand. It has been demonstrated that an accurate temperature forecast can reduce significantly the prediction error of the electricity prices
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
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