<p> A smart grid is an electricity network that accommodates two-way power flows, and utilizes two-way communications and increased measurement, in order to provide more information to customers and aid in the development of a more efficient electricity market. The current electrical network is outdated and has many shortcomings relating to power flows, inefficient electricity markets, generation/supply balance, a lack of information for the consumer and insufficient consumer interaction with electricity markets. Many of these challenges can be addressed with a smart grid, but there remain significant barriers to the implementation of a smart grid. </p><p> This paper proposes a novel method for the development of a smart grid utilizing a bottom up approach (starting with smart buildings/campuses) with the goal of providing the framework and infrastructure necessary for a smart grid instead of the more traditional approach (installing many smart meters and hoping a smart grid emerges). This novel approach involves combining deterministic and statistical methods in order to accurately estimate building electricity use down to the device level. It provides model users with a cheaper alternative to energy audits and extensive sensor networks (the current methods of quantifying electrical use at this level) which increases their ability to modify energy consumption and respond to price signals </p><p> The results of this method are promising, but they are still preliminary. As a result, there is still room for improvement. On days when there were no missing or inaccurate data, this approach has R² of about 0.84, sometimes as high as 0.94 when compared to measured results. However, there were many days where missing data brought overall accuracy down significantly. In addition, the development and implementation of the calibration process is still underway and some functional additions must be made in order to maximize accuracy. The calibration process must be completed before a reliable accuracy can be determined. </p><p> While this work shows that a combination of a deterministic and statistical methods can accurately forecast building energy usage, the ability to produce accurate results is heavily dependent upon software availability, accurate data and the proper calibration of the model. Creating the software required for a smart building model is time consuming and expensive. Bad or missing data have significant negative impacts on the accuracy of the results and can be caused by a hodgepodge of equipment and communication protocols. Proper calibration of the model is essential to ensure that the device level estimations are sufficiently accurate. Any building model which is to be successful at creating a smart building must be able to overcome these challenges.</p>

<p>In the operation of an air pitted gaseous sensors, the microhotplate (&micro;HP) consumes almost all the power used by the sensor. The required area to micromachine the air pit for the &micro;HP of a single sensor is several times more than the actual area required by the sensor itself. The feasibility of implementing low power and ultra-dense gaseous sensor array is investigated by developing a new &micro;HP structure using recessed silica aerogel. In comparison with the conventional &micro;HP structure, the recessed aerogel not only has decreased the utilized area of the chip almost tenfold (181 &times; 181 &micro;m² vs. 573 &times; 573 &micro;m²) but also has decreased the power consumed by each &micro;HP more than two fold (54 nW vs. 30 nW) to maintain the temperature of 360&ordm;C. Using the new structure, as the number of sensors increases in a sensor array, the saved area of the chip increases quadratic. Moreover, the power consumed by the new designed structure reduces drastically. </p>

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. / Source: Dissertation Abstracts International, Volume: 69-11, Section: B, page: 7045. Adviser: Peter W. Sauer. Includes bibliographical references (leaves 128-134) Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3987. Adviser: Thomas J. Overbye. Includes bibliographical references (leaves 152-158) Available on microfilm from Pro Quest Information and Learning.

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In the transition from traditional power plants to more environmentally friendly alternatives will generate a need for more flexibility in production, transmission and consumption. Energy storage can be provide the flexibility that are required to continue to have a robust and stable electrical system. The purpose of this report is to give an overview of the electrical energy storage technologies. The classification of energy storage technologies used in this report is mechanical, chemical and electrical. In these three categories were ten different technologies presented with function, advantages, disadvantages, degree of maturity and research area for each technology. The distribution between the globally operational energy storage technologies were presented. Also the framework and regulations for actors to own and operate an energy storage in Sweden. This review was complemented with a case study about connecting a lithium ion battery system to a wind farm. The case investigated the profitability for 20 MW wind farm with a 12 MW and 18 MWh energy storage system for a five and ten-year period. The utilization of the storage was optimized with \textit{What's best} for three different investment cost. The review were done in order to answer: what is the futures energy storage technology?, what applications can be replaced by energy storage for an electricity producer? and what will the effects be of the new actor Aggregator? The result from comparing three different prices for lithium ion batteries resulted in a non-profit scenario for all the cases in a five-year period. There were a maximum, minimum and predicted futuristic price, which generated a loss of 731, 220 and 76.6 MSEK for respective case. Only the futuristic price for a ten-year period indicated an profit. The conclusion that can be drawn from this case study is that energy storage is too expensive and the extra income from utilization of the energy storage is not enough to motivate an energy storage investment. There are not a single technology that possesses all of the required properties for the applications. In the future there will be a combination of technologies to cover all the applications. For the seasonal storage pumped hydro and compressed air are most promising technologies. The flywheels and supercapacitors can contribute with short powerful burst of energy that are needed for power quality and operating reserves. For the more wide range application such as power fleet optimization and integrate the renewable energy production, batteries in form of lithium ion battery and sodium-sulfur battery will most probably be used. For electricity producers energy storage can replace existing solutions. Instead of using diesel generators for black start services, an battery can be used. Also the power quality could be enhanced with batteries acting as filters. The process can be more utilized in a more efficient way with an energy storage. The aggregator actor gathers small variable load from e.g several houses and participate on the electricity market. This actor will level out the differences in power demand during the day. It will reduce the losses and reduce the need for grid investments in both the transmission and distribution networks. It would also generate more available frequency reserves and probably change how the market is paying for the generated benefits.

Rising energy costs should be a concern to contractors, designers, and owners. It is difficult to make a quantity takeoff for energy usage because these costs are imbedded in the materials, equipment, or overhead costs. This research examines energy consumption during the construction process, sets forth methods for recording this energy consumption and establishes a program for the recording and analysis of this data. An energy study of electricity, gasoline, and diesel consumption was made for the construction of three buildings to determine what data was available. After available data was evaluated, and the Energy Data Analysis program developed, three other construction sites were visited to determine how readily energy data can be recorded using the program. Four construction energy phases were identified from this research. The four phases are: 1) site clearing and preparation, 2) building structure, 3) interior finishes, and 4) commissioning. The main type of energy consumption during Phase 1 is diesel fuel for earth moving equipment. The energy uses for Phases 2 and 3 varied considerably among the projects studied and were difficult to quantify. However, the energy use during these phases was low compared to other phases and for many projects may not be economical to evaluate. During Phase 4, electrical energy demand was high due to Heating, Ventilation and Air Conditioning (HVAC) commissioning requirements and power up of all electrical power uses including lighting. These few construction projects are not enough to make definitive conclusions about what percentage of the total project cost is spent on energy. This research found that construction energy costs vary during different phases of the building process and can be a significant part of that phase (as high as 5.7% of the cost). The Visual Basic program developed during this research will facilitate future energy studies on construction sites. When the program is applied to a project, it identifies and quantifies the energy use, and makes predictions as to which project tasks warrant further energy studies.

<p> Various environmental and economic factors have lead to increased global investment in alternative energy technologies such as solar and wind power. Although methodologies for synchronous generator control are well researched, wind turbines present control systems challenges not presented by traditional generation. The varying nature of wind makes achieving synchronism with the existing electrical power grid a greater challenge. Departing from early use of induction machines, permanent magnet synchronous generators have become the focus of power systems and control systems research into wind energy systems. This is due to their self excited nature, along with their high power density. The problem of grid synchronism is alleviated through the use of high performance power electronic converters. In achievement of the optimal levels of efficiency, advanced control systems techniques oer promise over more traditional approaches. Research into sliding mode control, and linear matrix inequalities with nite time boundedness and H&infin; performance criteria, when applied to the dynamical models of the system, demonstrate the potential of these control methodologies as future avenues for achieving higher levels of performance and eciency in wind energy.</p>

Abstract- This paper will investigate the use of a three-to-one Matrix converter to synchronize the electrical energy and condition the output of the wind generator. A Matrix converter is a direct ACAC solution, removing the need for large smoothing capacitors in a typical rectifier/inverter solution. This paper will briefly review the Matrix converter operational theory. A simulation and the practical results of a three-to-one phase matrix converter for varying input frequencies are also presented. The conclusion shows that the proposal is a viable solution for small power wind harvesting.

<p> The percentage of electricity supplied by photovoltaic (PV) generators is steadily rising in power systems worldwide. This rise in PV penetration may lead to larger fluctuations in power system frequency due to variability in PV generator output at time scales that fall between the inertial damping and automatic generation control (AGC) responses of power systems. To reduce PV generator variability, active power controls can be implemented in the power electronic inverters that interface PV generators to the power system. Although various types of active power controls have been developed, no standard methodology exists for evaluating the effectiveness of these controls at improving power system frequency regulation. This dissertation presents a method for predicting the effects of short-term PV variability on power system frequency for a PV generator with active power control provided by integrated energy storage. A custom model of a PV generator with integrated energy storage is implemented in a power system dynamic simulator and validated through experiments with a grid emulator. The model is used to predict the effects of short-term PV variability on the frequency of the IEEE 9-bus test power system modified to include a PV generator with integrated energy storage. In addition, this dissertation utilizes linear analysis of power system frequency control to predict worst-case frequency deviations as a function of the amount of energy storage integrated into PV generators. Through simulation and emulation on a scaled experimental prototype, the maximum frequency deviation caused by the PV generator with a small amount of integrated energy storage is found to be approximately 33% lower than the maximum frequency deviation caused by the PV generator alone. Through linear analysis it is shown that by adding only 36.7 kWh of integrated energy storage to a 1.2 MW PV system, the worst-case frequency deviation on the IEEE 9-bus test system can be reduced 65% from 0.45 Hz to 0.16 Hz. The techniques presented enable estimation of the maximum PV penetration or minimum integrated energy storage requirement to meet a frequency regulation target for a particular power system. Integrated energy storage can then be compared to other active power controls in order to choose a method that meets frequency control requirements at minimum cost.</p>