Supply Current Modeling and Analysis of Deep Sub-Micron Cmos Circuits

Continued technology scaling has introduced many new challenges in VLSI design. Instantaneous switching of the gates yields high current flow through them that causes large voltage drop at the supply lines. Such high instantaneous currents and voltage drop cause reliability and performance degradation. Reliability is an issue as high magnitude of current can cause electromigration, whereas, voltage drop can slow down the circuit performance. Therefore, designing power supply lines emphasizes the need of computing maximum current through them. However, the development of digital integrated circuits in short design cycle requires accurate and fast timing and power simulation. Unfortunately, simulators that employ device modeling methods, such as HSPICE are prohibitively slow for large designs. Therefore, methods which can produce good maximum current estimates in short times are critical. In this work a compact model has been developed for maximum current estimation that speeds up the computation by orders of magnitude over the commercial tools

Test and Diagnosis of Integrated Circuits

The ever-increasing growth of the semiconductor market results in an increasing complexity of digital circuits. Smaller, faster, cheaper and low-power consumption are the main challenges in semiconductor industry. The reduction of transistor size and the latest packaging technology (i.e., System-On-a-Chip, System-In-Package, Trough Silicon Via 3D Integrated Circuits) allows the semiconductor industry to satisfy the latest challenges. Although producing such advanced circuits can benefit users, the manufacturing process is becoming finer and denser, making chips more prone to defects.The work presented in the HDR manuscript addresses the challenges of test and diagnosis of integrated circuits. It covers:- Power aware test;- Test of Low Power Devices;- Fault Diagnosis of digital circuits

Loodussäästliku tuumkütuse tsükli modelleerimine ja analüüs optimaalseks tooraine kasutuseks ja radioloogilise mõju vähendamiseks

Väitekirja elektrooniline versioon ei sisalda publikatsioonePaljud riigid püüavad piirata kasvuhoonegaaside heitkoguseid ja püüavad keskenduda süsinikuvabadele energiaallikatele, mistõttu on tuumaenergia jätkuva arutelu teema, et laiendada kogu maailma energiatootmise segmenti ja katta baaskoormuse nõudeid. On vaja hinnangut turul pakutavatele uraanitarnetele ja vastavat ressursside optimeerimise konteksti, tegemaks otsuseid, mis mõjutavad tuumaenergia pikaajalist arengut, ning hoiatab poliitikakujundajaid võimalikest uraaniturul toimuvatest muutustest, et aidata teha tehnoloogilisi valikuid. Käesoleva töö eesmärgiks on demonstreerida ja katsetada arenenud simulatsioonimeetodeid ja kontseptsioone, et luua realistlikumaid kütusetsüklite simulaatoreid ja seeläbi luua otsusetegijatele vajalik abivahend. Lisaks lahendab töö optimeerimisparadigma, leidmaks soodsaima tuumakütusetsükli tehnoloogia, mis aitab säästa loodusvarasid, suudab minimiseerida kõrgetasemelist radioaktiivsete jäätmete mõju loodusele ja vähendades tuumamaterjalide levikust tulenevatMany countries are struggling to limit greenhouse gas emissions and focus on carbon-free energy sources, and therefore nuclear energy is a subject of continuing debate to enhance the worldwide energy production mix and cover the base load requirements. Evaluation of uranium supply in a market and resource optimization context is needed to inform decisions impacting the long-term development of nuclear power and warn policy makers about possible uranium market supply-side volatilities and to help choose the technology mix. The aim of this work is to demonstrate and test advanced simulation methods and conceptual ideas to enable realistic fuel cycle simulators and develop a supporting tool for decision makers. Additionally, this work facilitates the selection of the most favorable nuclear fuel cycle, using optimization with respect to multiple criteria save natural resources, minimize the impact of high level radioactive waste on nature, to and decrease nuclear material proliferation risks

Techno-Economic modelling of hybrid renewable mini-grids for rural electrification planning in Sub-Saharan Africa

Access to clean, modern energy services is a necessity for sustainable development. The UN Sustainable Development Goals and SE4ALL program commit to the provision of universal access to modern energy services by 2030. However, the latest available figures estimate that 1.1 billion people are living without access to electricity, with over 55% living in Sub-Saharan Africa. Furthermore, 85% live in rural areas, often with challenging terrain, low income and population density; or in countries with severe underinvestment in electricity infrastructure making grid extension unrealistic. Recently, improvements in technology, cost efficiency and new business models have made mini-grids which combine multiple energy technologies in hybrid systems one of the most promising alternatives for electrification off the grid. The International Energy Agency has estimated that up to 350,000 new mini-grids will be required to reach universal access goals by 2030. Given the intermittent and location-dependent nature of renewable energy sources, the evolving costs and performance characteristics of individual technologies, and the characteristics of interacting technologies, detailed system simulation and demand modelling is required to determine the cost optimal combinations of technologies for each-and-every potential mini-grid site. Adding to this are the practical details on the ground such as community electricity demand profiles and distances to the grid or fuel sources, as well asthe social and political contexts,such as unknown energy demand uptake or technology acceptance, national electricity system expansion plans and subsidies or taxes, among others. These can all have significant impacts in deciding the applicability of a mini-grid within that context. The scope of the research and modelling framework presented focuses primarily on meeting the specific energy needs in the sub-Saharan African context. Thus, in being transparent, utilizing freely available software and data as well as aiming to be reproducible, scalable and customizable; the model aims to be fully flexible, staying relevant to other unique contexts and useful in answering unknown future research questions. The techno-economic model implementation presented in this paper simulates hourly mini-grid operation using meteorological data, demand profiles, technology capabilities, and costing data to determine the optimal component sizing of hybrid mini-grids appropriate for rural electrification. The results demonstrate the location, renewable resource, technology cost and performance dependencies on system sizing. The model is applied for the investigation of 15 hypothetical mini-grids sites in different regions of South Africa to validate and demonstrate the model’s capabilities. The effect of technology hybridization and future technology cost reductions on the expected cost of energy and the optimal technology configurations are demonstrated. The modelling results also showed that the combination of hydrogen fuel cell and electrolysers was not an economical energy storage with present day technology costs and performance. Thereafter, the model was used to determine an approximate fuel cell and electrolyser cost target curve up to the year 2030. Ultimately, any research efforts through the application of the model, building on the presented framework, are intended to bridge the science-policy boundary and give credible insight for energy and electrification policies, as well as identifying high impact focus areas for ongoing further research

Multi-energy retail market simulation with autonomous intelligent agents

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2005. Faculdade de Engenharia. Universidade do Port

Modeling, Simulation and Optimization of Wind Farms and Hybrid Systems

The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems

Modeling, Simulation and Optimization of Wind Farms and Hybrid Systems

The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems

Modeling, Simulation and Optimization of Wind Farms and Hybrid Systems

The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems

Optimal integration of wind energy with a renewable based microgrid for industrial applications.

Wind energy in urban environments is a rapidly developing technology influenced by the terrain specifications, local wind characteristics and urban environments such as buildings architecture. The urban terrain is more complex than for open spaces and has a critical influence on wind flow at the studied site. This approach proposes an integration of the surrounding buildings in the studied site and then simulating the wind flow, considering both simple and advanced turbulence models to quantify and simulate the wind flow fields in an urban environment and evaluate the potential wind energy. These simulations are conducted with an accessible computational fluid dynamic tool (Windsim) implementing available commercial wind turbines and performed on a case study at Agder county in the southern part of Norway for an industrial facility specialized in food production. Several simulations were considered and repeated to achieve a convergence after adding the buildings to the domain, which mainly simulates the wind flow patterns, power density, and annual energy production. These simulations will be compared with previous results, which adapted different manipulation techniques applied on the same site where the elevation and roughness data were manipulated to mimic the actual conditions in the studied urban site. The current approach (adding the buildings) showed a reduction in the average wind speed and annual energy production for certain levels with increased turbulence intensity surrounding the buildings. Moreover, a feasibility study is conducted to analyze the techno-economic of the facility's hybrid system, including the planned installation of a wind energy system using commercial software (HOMER). The simulation results indicated that HOMER is conservative in estimating the annual energy production of both wind and solar power systems. Nevertheless, the analysis showed that integrating a wind turbine of 600 kW would significantly reduce the dependence on the grid and transform the facility into a prosumer with more than 1.6 GWh traded with the grid annually. However, the proposed system's net present cost would be 1.43 M USD based on installation, maintenance, and trading with the grid, without including self-consumption, which counts for approximately 1.5 GWh annually. Moreover, the proposed system has a low levelized cost of energy of 0.039$ per kWh, which is slightly above the levelized cost of wind energy but 2 to 4 times less than the installed solar panels