Browsing by Author "Zimmerle, Daniel, committee member"
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Item Open Access A model of the effects of automatic generation control signal characteristics on energy storage system reliability(Colorado State University. Libraries, 2012) Campbell, Timothy M., author; Bradley, Thomas H., advisor; Zimmerle, Daniel, committee member; Young, Peter M., committee memberNo electrochemical batteries constructed to date have the storage capacities necessary for integration into conventional energy markets; aggregation will be required to meet industry-standard metrics for reliability and availability. This aggregation of individual energy storage devices into a distributed energy storage (DES) system will be useful not only to allow standard connection to the grid, but to provide higher-quality fast-response grid services with low-cost technologies. These smaller installations will have lower capital costs than traditional energy storage facilities. Ancillary services, and more specifically frequency regulation services, are understood to be the most technically viable and economically valuable market available to DES. Accordingly, this study is based on the properties of the frequency regulation market. This study presents a simplified model of a DES resource, its frequency regulation actuation signal, and its mode of market participation. The inputs to the model are scaling parameters of the DES system and of the actuation signal. The outputs from the model are the individual and aggregated reliability of the DES system. An analytical calculation of reliability is performed and analytical results are compared to numerical simulation solutions. Results show that the reliability of the energy storage device can be characterized using a set of non-dimensional parameters. These device-level reliability results are then translated into system-level reliability through several different models of ancillary services contracting and dispatch. Previous studies of DES systems have assumed that the energy storage system has no energy storage limitations and that the actuation signal has no net or instantaneous energy content. This model includes these conditions so as to capture the interaction between the energy content of the Automatic Generation Control (AGC) signal and the device-level and system-level reliability of DES systems. These results are novel in that they can guide the independent system operator/balancing authority in constructing an AGC signal specific to the needs of DES system resources.Item Open Access Analysis and characterization of wireless smart power meter(Colorado State University. Libraries, 2014) Soman, Sachin, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Pasricha, Sudeep, committee memberRecent increases in the demand for and price of electricity has stimulated interest in monitoring energy usage and improving efficiency. This research work supports development of a low-cost wireless smart power meter capable of measuring RMS Values of voltage and current, real power, and reactive power. The proposed smart power meter features include matching by-device rate of consumption and usage patterns to assist users in monitoring the connected devices. The meter also includes condition monitoring to detect harmonics of interest in the connected circuits which can give vital clues about the defects in machines connected to the circuits. This research work focuses on estimating communicational and computational requirements of the smart power meter and optimization of the system based on the estimated communication and computational requirements. The wireless communication capabilities investigated here are limited to existing wireless technologies in the environment where the power meters will be deployed. Field tests are performed to measure the performance of selected wireless standard in the deployment environment. The test results are used to understand the distance over which the smart power meters can communicate and where it is necessary to utilize repeaters or range extenders to reduce the data loss. Computational requirements included analysis of smart meter front-end sampling of analog data from both current and voltage sensors. Digitized samples stored in a buffer which is further processed by a microcontroller for all the desired results from the power meter. The various stages for processing the data require computational bandwidth and memory dependent on the size of the data stream and calculations involved in the particular stage. A Simulink-based system model of the power meter was developed to report a statistic of computational bandwidth demanded by each stage of data processing. The developed smart meter works in an environment with other wireless devices which include Wi-Fi and Bluetooth. The data loss caused when the smart power meter transmits the data depends on the architecture of the wireless network and also pre-existing wireless technology working in the same environment and while operating in the same frequency band. The best approach in developing a wireless network should reduce the hardware cost of the network and to reduce the data loss in the wireless network. A wireless sensor network is simulated in OMNET++ platform to measure the performance of wireless standard used in smart power meters. Scenarios involving the number of routers in the network and varying throughput between devices are considered to measure the performance of wireless power meters. Supplementary documents provided with the electronic version of this thesis contain program codes which were developed in Simulink and OMNET++.Item Open Access Control design for generator of nonlinear high frequency plasma system(Colorado State University. Libraries, 2021) Vora, Prajay, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Cale, James, committee memberThis document aims to develop control systems for a generator of a nonlinear high frequency plasma system. Initial modelling was done by Advanced Energy Industries, Inc. (AE) which was passed on to Colorado State University environment for further research into developing controllers for this special model. This thesis documents all the work done by Colorado State University till Summer of 2020. The first phase of the collaboration included finding metrics for the feedback system with the nonlinear load modelled by AE. The metrics serve for better understanding of the modelling and also to generate effective control criteria suited to AE requirements. AE required for the user defined wave-forms to be tracked in an average sense without significantly changing the real time tracking criteria. This tradeoff was also addressed while developing metrics. A preliminary approach for control design was a PID controller to study its effects in a nonlinear environment. A robust control approach called H∞ loop-shaping is the primary control design developed by CSU for this specific application. The nonlinear system was approximated with a transfer function and the controller developed for that approximation. The purpose of the approximation is to generate a controller that is highly robust considering the uncertainties in high frequency plasma loads. The metrics discussed above are used for confirming the efficiency of the controllers. Controller design was the second phase of the project. Finally, in phase three, Nelder-Mead optimization was used to generalize the H∞ controller for various generator and set-point specifications. A system identification processes was also developed consisting of curve fit models for the nonlinear load. This was done with a view to the future for classifying different loads and plasma to develop customised controllers.Item Open Access Customer and system impacts of grid support functions for voltage management strategies(Colorado State University. Libraries, 2020) Giraldez Miner, Julieta, author; Suryanarayanan, Siddharth, advisor; Atadero, Rebecca, committee member; Yang, Liuqing, committee member; Young, Peter, committee member; Zimmerle, Daniel, committee memberThis document describes modeling techniques and methods to study the impacts to the utility and to the customer of using DERs such as advanced inverters to provide voltage support in order to maintain voltage within the recommended voltage limits. For this, a method for accurately representing secondary circuits in distribution feeders is proposed and quasi-static-time series (QSTS) simulation techniques are used to study the impact of advance inverter functions to the utility for managing voltage and to the customer in terms of possible generation curtailment. This dissertation looks at factors in medium and low-voltage circuit topology that drive customer voltages with DERs, and investigates where along the distribution feeder are voltage based advance inverter grid support function most effective. The described modeling techniques and methods have informed policy and regulatory type decisions such as updating DER interconnection tariffs and standards.Item Open Access Design and construction of electric motor dynamometer and grid attached storage laboratory(Colorado State University. Libraries, 2011) Lutz, Markus, author; Bradley, Thomas, advisor; Zimmerle, Daniel, committee member; Young, Peter, committee memberThe purpose of this thesis is to describe the design and development of a laboratory facility to both educate students on electric vehicle components as well as allow researchers to gain experimental results of grid-attached-storage testing. With the anticipated roll out of millions of electric vehicles, manufacturers of such vehicles need educated hires with field experience. Through instruction with this lab, Colorado State University plans to be a major resource in equipping the future electric vehicle work force with necessary training and hands-on experience using real world, full-scale, automotive grade electric vehicle components. The lab also supports research into grid-attached-storage. This thesis explains the design objectives, challenges, selections, construction and initial testing of the lab, and also provides context for the types of education and research which can be performed utilizing the laboratory.Item Open Access Design of control tools for use in microgrid simulations(Colorado State University. Libraries, 2018) Othee, Avpreet Singh, author; Young, Peter M., advisor; Zimmerle, Daniel, committee member; Collins, George, committee memberNew technologies are transforming the way electricity is delivered and consumed. In the past two decades, a large amount of research has been done on smart grids and microgrids. This can be attributed to two factors. First is the poliferation of internet. Internet today is as ubiquitous as electricity. This has spawned a new area of technology called the internet of things (IoT). It gives us the ability to connect almost any device to the internet and harness the data. IoT finds use in smart grids that allow utiliy companies to deliver electricity efficiently. The other factor is the advancement in renewable sources of electricty and high power semiconductors coupled with their decreasing cost. These new sources disrupt the traditional way of electicity production and delivery, putting an increased focus on distributed power generation and microgrids. A microgrid is different from a utility grid. The difference is in the size of the grid, power level, a variety of possible sources and the way these are tied together. These characteristics lead to some unique control challenges. Today's appliances and consumer goods are powered using a standardized AC power. Thus a microrid must deliver uninterrupted and high quality power while at the same time taking into account the vastly different nature of the microsurces that produce the power. This work describes control system tools for different power converters that will be used in simulating microgrids.\ Simulations are important tool for any researcher. It allows researchers to test their research and theories at a greatly reduced cost. The process of design, testing and verification is an iterative process. Simulations allow a cost effective method of doing research, substituting the actual process of building experimental systems. This greatly reduces the amount of manpower and capital investment. A microgrid consists of several building blocks. These building blocks can be categorized into microsources, energy stores, converters and the loads. Microsources are devices that produce electric power. For example, a photovoltaic panel is a mirosource that produces DC power. Converters act as an interface between microsources and the grid. The constituent chapters in the document describe microsources and converters. The chapters describe the underlying control system and the simulation model of the system designed in Simulink. Some of the tools described are derived from the MATLAB/Simulink Examples library. Original authors of the simulation models and systems have been duly credited. Colorado State University has a vibrant research community. The tools described in this thesis are geared to be used for research into microgrids. The tools are developed in a simulation software called Simulink. The tools would allow future researchers to rapidly build microgrid simulations and test new control system implementations etc. The research described in the thesis builds upon the research by Han on natural gas engine based microgrid. The control tools described here are used to construct a microgrid simulation. The microgrid is built around a natural gas engine. Due to the transport lag in delivering fuel, a natural gas engine exhibits significant deviation in the AC grid frequency when subjected to step load. The microgrid setup along with the control system described here, minimizes the frequency deviation, thus stabilizing the microgrid. Simulation results verify the working of the tools.Item Open Access Design, construction and commissioning of an organic Rankine cycle waste heat recovery system with a Tesla-hybrid turbine expander(Colorado State University. Libraries, 2011) Cirincione, Nicholas, author; Olsen, Daniel, advisor; Zimmerle, Daniel, committee member; Dandy, David, committee memberIssues surrounding energy are some of the most compelling subjects in the world today. With human's ever increasing need for energy, production must increase or consumption must be reduced to avoid an unsustainable long-term energy balance. One part of the energy solution is low-temperature Organic Rankine Cycles (ORCs). ORCs can be utilized to produce power in mass quantity from a dedicated heat source such as a geothermal well. ORCs may also be utilized as a waste heat recovery system to generate power from a heat stream that is typically rejected to the environment. Low-temperature waste heat streams are ubiquitous as every internal combustion engine generates 55-75% of its total fuel energy as waste heat. Efficiency of a waste heat recovery ORC system is strongly dependent on condensing temperature and expander efficiency. Condensing temperatures are typically kept low with an evaporative condensing unit. However, water consumption to increase energy production is becoming less tolerated. To provide a means to conduct research around these issues, a waste heat recovery ORC test bed was designed and constructed. This thesis contains information on construction and operation of the test bed with these features: R245fa working fluid, direct dry cooled condensing and a Tesla-hybrid turbine expander.Item Open Access Device characterization on energy design and scoping tool for DC distribution systems and a study on harmonics in AC/DC converters in low voltage distribution(Colorado State University. Libraries, 2020) Santos, Arthur FelÃcio Barbaro dos, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Suryanarayanan, Siddharth, committee memberDC appliances have resurged with the evolution of power electronics and their massive application in Miscellaneous Electric Loads. The increase of DC distributed generation and battery storage has also helped boost the scientific community's attention to this other alternative. This work collects consumption data from appliances and converters connected to an AC distribution. The appliances that are focused on in this study are called Miscellaneous Electric Loads (MELs), which comprise all electronic loads in a building that are not related to lighting, heating, and air conditioning. The harmonics of these devices are analyzed in this paper as part of a relevant project funded by the Department of Energy of the United States: the Energy Design and Scoping Tool for DC Distribution Systems. This work also presents results from another study, still within the scope of the same project, which aims to collect power consumption data on appliances commonly found in an office environment (laptop, screens, desktops, phone chargers, and network devices) over a period of approximately two months. This data will give a real estimate of these appliances' AC/DC converter operating range regarding their rated power and will allow a more complete analysis of the emission of harmonics in the power system and a comparison of harmonic cancellation in low voltage distribution systems versus the total cancellation potential.Item Open Access Disaggregation of net-metered advanced metering infrastructure data to estimate photovoltaic generation(Colorado State University. Libraries, 2019) Stainsby, Wendell Jay, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Aloise-Young, Patricia, committee memberAdvanced metering infrastructure (AMI) is a system of smart meters and data management systems that enables communication between a utility and a customer's premise, and can provide real time information about a solar array's production. Due to residential solar systems typically being configured behind-the-meter, utilities often have very little information about their energy generation. In these instances, net-metered AMI data does not provide clear insight into PV system performance. This work presents a methodology for modeling individual array and system-wide PV generation using only weather data, premise AMI data, and the approximate date of PV installation. Nearly 850 homes with installed solar in Fort Collins, Colorado, USA were modeled for up to 36 months. By matching comparable periods of time to factor out sources of variability in a building's electrical load, algorithms are used to estimate the building's consumption, allowing the previously invisible solar generation to be calculated. These modeled outputs are then compared to previously developed white-box physical models. Using this new AMI method, individual premises can be modeled to agreement with physical models within ±20%. When modeling portfolio-wide aggregation, the AMI method operates most effectively in summer months when solar generation is highest. Over 75% of all days within three years modeled are estimated to within ±20% with established methods. Advantages of the AMI model with regard to snow coverage, shading, and difficult to model factors are discussed, and next-day PV prediction using forecasted weather data is also explored. This work provides a foundation for disaggregating solar generation from AMI data, without knowing specific physical parameters of the array or using known generation for computational training.Item Open Access Energy management of a university campus utilizing short-term load forecasting with an artificial neural network(Colorado State University. Libraries, 2012) Palchak, David, author; Bradley, Thomas, advisor; Suryanarayanan, Siddharth, advisor; Zimmerle, Daniel, committee member; Young, Peter, committee memberElectrical load forecasting is a tool that has been utilized by distribution designers and operators as a means for resource planning and generation dispatch. The techniques employed in these predictions are proving useful in the growing market of consumer, or end-user, participation in electrical energy consumption. These predictions are based on exogenous variables, such as weather, and time variables, such as day of week and time of day as well as prior energy consumption patterns. The participation of the end-user is a cornerstone of the Smart Grid initiative presented in the Energy Independence and Security Act of 2007, and is being made possible by the emergence of enabling technologies such as advanced metering infrastructure. The optimal application of the data provided by an advanced metering infrastructure is the primary motivation for the work done in this thesis. The methodology for using this data in an energy management scheme that utilizes a short-term load forecast is presented. The objective of this research is to quantify opportunities for a range of energy management and operation cost savings of a university campus through the use of a forecasted daily electrical load profile. The proposed algorithm for short-term load forecasting is optimized for Colorado State University's main campus, and utilizes an artificial neural network that accepts weather and time variables as inputs. The performance of the predicted daily electrical load is evaluated using a number of error measurements that seek to quantify the best application of the forecast. The energy management presented utilizes historical electrical load data from the local service provider to optimize the time of day that electrical loads are being managed. Finally, the utilization of forecasts in the presented energy management scenario is evaluated based on cost and energy savings.Item Open Access Evaluation of distributed energy storage for ancillary service provision(Colorado State University. Libraries, 2011) Quinn, Casey W., author; Bradley, Thomas H., advisor; Zimmerle, Daniel, committee member; Young, Peter M., committee memberResearchers have proposed that distributed energy storage devices could be used to perform ancillary services for the electric grid. This work focuses on vehicle-to-grid and battery-to-grid distributed energy storage devices. In conceptual studies, distributed energy storage devices were shown to be able to accrue revenue for performing these grid stabilization services, and these revenues were used to show that the use of vehicle-to-grid and battery-to-grid can help to offset the initial increased capital cost of electric vehicles. These conceptual studies have assumed a command architecture that allows for a direct and deterministic communication between the grid system operator and the distributed energy storage devices. The first part of this thesis compares this direct, deterministic command architecture to an aggregative command architecture on the basis of the availability, reliability and value of the vehicle-to-grid provided ancillary services. This research incorporates a new level of detail into the modeling of vehicle-to-grid ancillary services by incorporating probabilistic vehicle travel models, time series ancillary services pricing, a consideration of ancillary services reliability. Results show that including an aggregating entity in the command and contracting architecture can improve the scale and reliability of vehicle-to-grid ancillary services, thereby making vehicle-to-grid ancillary services more compatible with the current ancillary services market. However, the aggregative architecture has the deleterious effect of reducing the revenue accrued by plug-in vehicle owners relative to the default architectures. The second part of this work investigates the effects of introducing battery state of charge and time series generation control signals. Results show that in order to integrate a vehicle-to-grid system into the existing markets and power grid the distributed energy storage system will require: 1) an aggregative architecture to meet current industry reliability standards, 2) the construction of low net energy automatic generation control signals, 3) a lower percent call for distributive energy storage systems even if the pool of contracted ancillary service resources gets smaller, 4) a consideration of vehicle performance degradation due to the potential loss of electrically driven miles, and 5) the incorporation of power-to-energy ratios. The third part of this work adapts the vehicle-to-grid model to a battery-to-grid system. Results show that if the automatic generation control signals contain low energy content, battery-to-grid has higher revenue potential than vehicle-to-grid due not having to account for vehicle driving behavior. Additionally, the third portion of this work proposed and performed high level analyses of operational options for battery-to-grid systems receiving automatic generation control signals with high energy content.Item Open Access Reducing carbon dioxide emissions in the electricity sector using demand side management(Colorado State University. Libraries, 2019) Almohaimeed, Sulaiman, author; Suryanarayanan, Siddharth, advisor; Collins, George J., committee member; Zimmerle, Daniel, committee member; Aloise-Young, Patricia, committee member; O’Neill, Peter, committee memberIncreasing demand for energy consumption leads to concerns of global Greenhouse Gas (GHG) emissions. Most of the supplied energy comes from dirty generating units. Since there are no regulations to limit emissions of CO2 from electricity generation, power plants can emit unlimited amount of CO2. This dissertation, first, aims to explain some government directed plans to reduce GHG emissions. It gives an overview about the Clean Power Plan (CPP) and its benefits and challenges. Further, it explains several options of CPP in reducing emissions and its repeal. Further, this dissertation, discusses the Climate Action Plan (CAP) corresponding to Fort Collins, Colorado, U.S. and its timeline targets. Demand side management (DSM) is discussed as a solution from engineering practices to affect GHG. Several options from DSM are investigated to reduce emissions. In fact, reducing energy consumption through DSM leads to a reduction in harmful emissions to the environment. This dissertation aims to identify the best available DSM options that will make the biggest difference for GHG reductions. A framework is created to examine several options of DSM in reducing carbon footprints. The framework states that affecting GHG in electric power system is the main goal. The goal can be achieved by implementing DSM technologies in distribution systems. The framework proposes criteria such as cost, power quality, reliability, environmental collateral, and socioeconomic equity to examine the effectiveness of several alternatives: energy management, communication and intelligence, electrification of heating and transportation, and distributed generation. Multi-Criteria Decision Making (MCDM) algorithms have been proposed to prioritize alternatives and select the ones that achieve suitable emissions reduction. Analytic Hierarchy Process (AHP) is one of the most common tools to perform decision-making analysis. The findings from AHP show that the "communication and intelligence" option is the potential optimal alternative in achieving the goal. Analytic Network Process (ANP) is another method for making decisions. It provides feedback and interdependence relationships between all nodes of the problem. It is more realistic and accurate than AHP. The results obtained from ANP suggest that "communication and intelligence" is the optimum technology to reach the target. By using ANP, the overall priority ranking has changed and the difference in priorities has reduced. Institute of Electrical and Electronics Engineers (IEEE) 13-node test feeder is used, through Open Distribution System Simulator (OpenDSS), to perform power flow analysis on yearly load profile corresponding to Fort Collins, Colorado, U.S. The analysis includes simulation for several scenarios from the MCDM alternatives, either individual alternatives or mixed alternatives. The obtained results for the base case show the emissions decreased by 16.26% from 2005 level which comply with the results from emissions indicator released by the city. Integrating the MCDM alternatives indicates CO2 emissions change as a result of variation in supply and demand curve. The findings for 2017 load profile demonstrated that "electric stationary storage" is the best option, environmentally, since it contributes in more than 18% emissions reduction from 2005 level. The second alternative is "energy conservation" by achieving a 20.39% reduction in emissions, merging both alternatives in one scenario could increase the emissions mitigation up to 22.17%. By simulation the residential sector, "communication and intelligence" shows about 14% reduction in emissions from 2005 level. A scenario that combines "electric stationary storage" with "communication and intelligence" diminishes the emissions by more than 15%. Indeed, combining "communication and intelligence" with "energy conservation" can decrease the environmental footprint by 18.04%. Last scenario examined combining all MCDM alternatives in one option. The result finds that this option can reach 19.72% emissions reduction. Since the simulation part investigates the system from environmental perspective, this work deploys a Cost Benefit Analysis (CBA) to assess economic, technical, and environmental cost and benefits associated with each alternative. The economic evaluation shows that "electric stationary storage" is the potential best option. This is reasonable since ESS charges during lower electricity price and discharge during peaking demand. Thus, the customers can avoid the high electricity charges, and the utility is not required to run more generating units. "communication and intelligence" combined with "electric stationary storage" is the second option due to its flexibility in shifting the loads to off-peak periods is. The scenario that includes all MCDM options came in the third place since it provides almost 20% emissions reduction and its economic evaluation is beneficial. While "energy conservation" project and "electric stationary storage" with "energy conservation" project provide less economic impact than "communication and intelligence", those alternatives hold the fourth and fifth place, respectively, due to their environmental impact. The penultimate alternative is "communication and intelligence" because the Demand Response (DR) is designed to shift the peak load, and it has socioeconomic cost. Last alternative is combining "communication and intelligence" with "energy conservation". Although "energy conservation" performs environmentally better than "communication and intelligence", its socioeconomic cost plays a major role in selecting such alternative. However, the ranking might change according to the participants' choice. One can prefer environmental impact over economic output and vice versa. Therefore, this work presents a trade-off chart, so the decision maker can select the alternative based on their preference. All analysis, simulation, and results in this work are particularly based on Fort Collins distribution system data and is not a general assessment. There are several factors might affect the result such as the location, the data, or the distribution system structure.Item Open Access Reliability quantification and visualization for electric microgrids(Colorado State University. Libraries, 2012) Panwar, Mayank, author; Suryanarayanan, Siddharth, advisor; Zimmerle, Daniel, committee member; Yang, Liuqing, committee memberThe electric grid in the United States is undergoing modernization from the state of an aging infrastructure of the past to a more robust and reliable power system of the future. The primary efforts in this direction have come from the federal government through the American Recovery and Reinvestment Act of 2009 (Recovery Act). This has provided the U.S. Department of Energy (DOE) with $4.5 billion to develop and implement programs through DOE's Office of Electricity Delivery and Energy Reliability (OE) over the a period of 5 years (2008-2012). This was initially a part of Title XIII of the Energy Independence and Security Act of 2007 (EISA) which was later modified by Recovery Act. As a part of DOE's Smart Grid Programs, Smart Grid Investment Grants (SGIG), and Smart Grid Demonstration Projects (SGDP) were developed as two of the largest programs with federal grants of $3.4 billion and $600 million respectively. The Renewable and Distributed Systems Integration (RDSI) demonstration projects were launched in 2008 with the aim of reducing peak electricity demand by 15 percent at distribution feeders. Nine such projects were competitively selected located around the nation. The City of Fort Collins in co-operative partnership with other federal and commercial entities was identified to research, develop and demonstrate a 3.5MW integrated mix of heterogeneous distributed energy resources (DER) to reduce peak load on two feeders by 20-30 percent. This project was called FortZED RDSI and provided an opportunity to demonstrate integrated operation of group of assets including demand response (DR), as a single controllable entity which is often called a microgrid. As per IEEE Standard 1547.4-2011 (IEEE Guide for Design, Operation, and Integration of Distributed Resource Island Systems with Electric Power Systems), a microgrid can be defined as an electric power system which has following characteristics: (1) DR and load are present, (2) has the ability to disconnect from and parallel with the area Electric Power Systems (EPS), (3) includes the local EPS and may include portions of the area EPS, and (4) is intentionally planned. A more reliable electric power grid requires microgrids to operate in tandem with the EPS. The reliability can be quantified through various metrics for performance measure. This is done through North American Electric Reliability Corporation (NERC) metrics in North America. The microgrid differs significantly from the traditional EPS, especially at asset level due to heterogeneity in assets. Thus, the performance cannot be quantified by the same metrics as used for EPS. Some of the NERC metrics are calculated and interpreted in this work to quantify performance for a single asset and group of assets in a microgrid. Two more metrics are introduced for system level performance quantification. The next step is a better representation of the large amount of data generated by the microgrid. Visualization is one such form of representation which is explored in detail and a graphical user interface (GUI) is developed as a deliverable tool to the operator for informative decision making and planning. Electronic appendices-I and II contain data and MATLAB© program codes for analysis and visualization for this work.Item Open Access Sediment management alternatives analysis in the Louisiana deltaic plain(Colorado State University. Libraries, 2023) Heap, David A., author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Grigg, Neil, committee member; Ross, Matthew, committee memberWhile coastal communities around the world are under threat from rising sea levels, those of Southeast Louisiana are some of the most threatened. Including subsidence, the region could potentially see rates of net sea level rise up to ten times the global mean. There is no shortage of causes for how this situation has come to pass. A Systems Engineering solution needs to be multi-faceted, similar to how the problem was created:- Climate change: like any coastal area, the region has to make hard decisions on how to handle a changing climate, but those choices have significant ramifications for the entire U.S. population, as significant commerce passes through the regional ports in the form of agriculture, oil/gas, petrochemicals, and the fishing industry. - Engineered factors: by controlling the flow of the Mississippi River with the intent of flood protection through the use of levees, floodwalls, and spillways, humans have inhibited the natural processes that could rebuild the wetlands and natural protection barriers. - River navigation: similarly, the locks and dams that allow maritime traffic have trapped the sediment that historically would have flowed down to the delta and built more land buffers against the sea. - Industrial infrastructure: with thousands of miles of navigation channels and pipelines, the wetlands have been cut up into non-natural bodies of water, allowing hurricanes and saltwater intrusion unabated access to delicate ecosystems. - Environmental damage: over 100 years of industrial development, combined with numerous environmental disasters, has compromised the health of the ecosystem. - Invasive species: whether intentionally introduced or not, non-native species, both flora and fauna alike, have wreaked havoc on native populations and weakened deltaic processes. - Stakeholder coordination: with dozens of local, state, and federal government agencies and nonprofit organizations, it is nearly impossible to make everyone happy. - Limited resources: there is a funding gap between the budget needed to implement a successful strategy and what is expected to be available if the status quo is maintained. While there are multiple methods employed to improve coastal resilience, a core strategy as defined by Louisiana's 2023 Coastal Master Plan is the introduction of sediment. The plan suggests two main alternatives of sediment management, that of the Major Diversions and Dredged Sediment. In this work, these two traditional alternatives are considered, and a new proposed approach is introduced, that of Micro Diversions, a concept developed in prior work by the author. All three approaches are described, analyzed, modeled, and compared against each other to determine which would be the most cost effective and appropriate for investment by coastal stakeholders. The compared metric is Cost Benefit over a 50-year time horizon, calculated using the Life Cycle Cost and Net Benefit variables from each alternative. Inherent in the Systems Engineering approach is that the cost variables consider the time value of money. The Major Diversion variables were taken from the stated goals in the Master Plan. The Dredged Sediment variables were forecasted from historical trends on recently completed and/or approved projects. The Micro Diversion variables were formulated from hydrologic software modeling of a limited system and expanded to compare in size to the other alternatives. At a Cost Benefit of $61,773 per acre, the Major Diversion alternative was evaluated to be a better investment than Dredged Sediment or Micro Diversions ($67,300 and $88,206 respectively). Because coastal conditions can change over time, and that the inputs to these alternatives can likewise change, it is suggested to view solutions with a systems-level approach, with the potential to implement complementary alternatives.Item Open Access State-based engine models for transient applications with a scalable approach to turbocharging(Colorado State University. Libraries, 2015) Bell, Clay S., author; Bradley, Thomas, advisor; Zimmerle, Daniel, committee member; Olsen, Daniel, committee member; Young, Peter, committee memberMicrogrids have the potential to improve energy surety, increase the penetration of renewable energy, and provide electrical power in remote areas; however, reduced system inertia contributes to challenges in maintaining power quality during operation. In this dissertation a state-based mean-value turbocharged diesel engine model is developed for applications in microgrid. The model is validated against transient data collected during step load testing at Colorado State University’s Engines and Energy Conversion Laboratory. A controller with an air-fuel ratio based smoke limit and load based gain schedule is implemented to improve agreement with experimental data when compared to a simplified model frequently used in microgrid control studies. The state-based model is capable of variable speed operation, extending the utility to transient applications beyond micro-grid. Due to the uncertainty around transient performance, lean burn gas engines typically are employed in steady load applications such as distributed generation or industrial systems such as natural gas compression in order to take advantage of the low cost of the fuel, improved efficiency, and reduced emissions. There is significant interest in natural gas engines for microgrids due to the low fuel cost and indications that natural gas supplies would be secure during an interruption of the national electric grid. In addition, replacing diesel engines with gas engines has been identified as a method to reduce cost and emissions associated with drilling and well stimulation. However; both of these applications involve transients which may exceed the capabilities of lean-burn natural gas engines. In this dissertation a state based mean-value turbocharged lean-burn natural gas model is developed to study transient control strategies. Transient data was unavailable; however the model exhibits the expected characteristics during transient loading, namely limited load acceptance capability due to turbocharger lag and narrow air-fuel ratio limits. Collecting and processing turbocharger performance data to a form appropriate for simulation is one of the more difficult and effort intensive steps when implementing state based engine models. A method is developed to implement non-dimensional performance maps thereby allowing a range of turbochargers to be modeled from the same performance data, reducing the effort required to implement models of different sizes. The non-dimensional maps seek to model the performance of compressor and turbine families in which the geometry of the rotor and housing are similar, and allow the turbocharger to be scaled for simulation in much the same way used to design customized sizes of turbochargers. A method to match the non-dimensional compressor map to engine performance targets by selecting the compressor diameter is presented, as well as a method to match the turbine to the compressor.Item Open Access Steady-state analysis of the impact of climate change on distribution transformer(Colorado State University. Libraries, 2016) Almohaimeed, Sulaiman, author; Suryanarayanan, Siddharth, advisor; Collins, George, committee member; Zimmerle, Daniel, committee memberClimate change could cause several issues such as decreasing water availability, increasing intensity of storm events, flooding and sea level rise, increasing air, and water temperatures. One aspect of climate change is the increase in ambient temperature. According to, the average global surface temperature is expected to increase around 1.8°C to 4°C, while the average increase of global ambient temperature is predicted from 1.4°C to 5.8°C, in the periods of 1990 to 2100. Climate change can also affect distribution systems in terms of reliability and loadability. A 1°C rise in global temperature increases peak demand by 4.6%. In 2013, U.S. weather–related power outages may have reached 180 events per year. Further, climate change leads to high temperature, and many factors might change. An increase in ambient temperature leads to increase in transformer loading, which leads to a reduction of lifetime of transformers and low insulation value due to degradation of degree of polymerization. As ambient temperature and operation temperature increase can cause thermal aging of transformers, it is important to control a loaded transformer to mitigate aging effect. Thus, demand response is an important and effective feature of thermal management of a transformer. Multiple models are discussed and explained to obtain accurate results and a good prediction for the three factors: ambient temperature, operation temperature, and demand response. Therefore, IEEE standard C57.91-2011 is used for calculating thermal characteristics and the loss of life of distribution transformers. It also provides an example using rated parameters of a 25 MVA distribution transformer, real data of temperature, load available in the public domain for Fort Collins, Colorado, USA. Moreover, demand response is considered in this calculation in order to study the effect of changing load levels on the transformer insulation life and aging acceleration factor. Four scenarios of load levels will be applied as follow: pre-DR, 3%, 6% and 9% peak load reduction.Item Open Access Synchronized real-time simulation of distributed networked controls for a power system case study(Colorado State University. Libraries, 2013) Jain, Abhishek, author; Young, Peter, advisor; Zimmerle, Daniel, committee member; Suryanarayanan, Siddharth, committee memberThe purpose of this study is to develop and implement a distributed networked control framework for a power system simulation. The study addresses and improves upon speed and accuracy of simulation for computationally intensive power system dynamic simulations and distributed control utilizing Hardware-In-Loop (HIL) simulations. A dynamic four bus test-case microgrid simulation is constructed using SimPowerSystemsâ„¢ toolbox of Matlabâ„¢ with renewable energy penetration. Parallel processing is achieved using a discrete real-time simulator Opal-RT by distributing the computation among its various processors and thus achieving real-time performance. Maximum power point tracking (MPPT) controls for various photo-voltaic (PV) systems are distributed among external simulation platforms with the use of a client-server communication architecture and application layer messaging network protocols. The various networked platforms implementing control algorithms include general purpose and data-flow graphical programming languages. The solar irradiance profile for various PV systems is generated from an external spreadsheet data source as another networked module. Also included in the communication network is a commercial off-the-shelf (COTS) controller - a substation automation platform OrionLX which is used for supervisory control of the various relays in the microgrid feeder simulation. Finally, a case study is presented which involves all of the above mentioned components - MPPT control and irradiance profile generation for PV systems as well as fault isolation in a microgrid using HIL supervisory relay control - as distributed elements of a communication network with the real-time server. Modbus TCP/IP is used as the networking protocol while the networked control platforms are developed in C# and Simulinkâ„¢ programming languages. Performance and bandwidth of the interdisciplinary system are analyzed. From the results of this study, it is concluded that the combination of a parallel processing and distributed control approach can be an effective strategy for improving dynamic power system simulations.Item Open Access Understanding the effects and infrastrcuture needs of plug-in electric vehicle (PEV) charging(Colorado State University. Libraries, 2010) Davis, Barbara Morgan, author; Bradley, Thomas H., advisor; Keske, Catherine M., committee member; Zimmerle, Daniel, committee memberPlug-in electric vehicles (PEV) are any vehicle that uses electricity to propel the vehicle, potentially in combination with other fuels like gasoline, diesel or hydrogen. PEV offer the benefits of reduced dependence on foreign oil and decreased greenhouse gas emissions. While the benefits are numerous for this new technology, the drawbacks are not fully understood. The largest concern for the utility company is to understand the necessary infrastructure requirements to minimize their impacts on the electric grid. This study focuses on the infrastructure needs and effects and how to best control PEV charging. The results of these analyses show the fundamental disconnect between the consumer and the utility company.