Matching Items (2)
Description
A pressurized water reactor (PWR) nuclear power plant (NPP) model is introduced into Positive Sequence Load Flow (PSLF) software by General Electric in order to evaluate the load-following capability of NPPs. The nuclear steam supply system (NSSS) consists of a reactor core, hot and cold legs, plenums, and a U-tube steam generator. The physical systems listed above are represented by mathematical models utilizing a state variable lumped parameter approach. A steady-state control program for the reactor, and simple turbine and governor models are also developed. Adequacy of the isolated reactor core, the isolated steam generator, and the complete PWR models are tested in Matlab/Simulink and dynamic responses are compared with the test results obtained from the H. B. Robinson NPP. Test results illustrate that the developed models represents the dynamic features of real-physical systems and are capable of predicting responses due to small perturbations of external reactivity and steam valve opening. Subsequently, the NSSS representation is incorporated into PSLF and coupled with built-in excitation system and generator models. Different simulation cases are run when sudden loss of generation occurs in a small power system which includes hydroelectric and natural gas power plants besides the developed PWR NPP. The conclusion is that the NPP can respond to a disturbance in the power system without exceeding any design and safety limits if appropriate operational conditions, such as achieving the NPP turbine control by adjusting the speed of the steam valve, are met. In other words, the NPP can participate in the control of system frequency and improve the overall power system performance.
ContributorsArda, Samet Egemen (Author) / Holbert, Keith E. (Thesis advisor) / Undrill, John (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study explores the potential risks associated with the 65 U.S.-based commercial nuclear power plants (NPPs) and the distribution of those risks among the populations of both their respective host communities and of the communities located in outlying areas. First, I examine the relevant environmental justice issues. I start by examining the racial/ethnic composition of the host community populations, as well as the disparities in socio-economic status that exist, if any, between the host communities and communities located in outlying areas. Second, I estimate the statistical associations that exist, if any, between a population's distance from a NPP and several independent variables. I conduct multivariate ordinary least square (OLS) regression analyses and spatial autocorrelation regression (SAR) analyses at the national, regional and individual-NPP levels. Third, I construct a NPP potential risk index (NPP PRI) that defines four discrete risk categories--namely, very high risk, high risk, moderate risk, and low risk. The NPP PRI allows me then to estimate the demographic characteristics of the populations exposed to each so-defined level of risk. Fourth, using the Palo Verde NPP as the subject, I simulate a scenario in which a NPP experiences a core-damage accident. I use the RASCAL 4.3 software to simulate the path of dispersion of the resultant radioactive plume, and to investigate the statistical associations that exist, if any, between the dispersed radioactive plume and the demographic characteristics of the populations located within the plume's footprint. This study utilizes distributive justice theories to understand the distribution of the potential risks associated with NPPs, many of which are unpredictable, irreversible and inescapable. I employ an approach that takes into account multiple stakeholders in order to provide avenues for all parties to express concerns, and to ensure the relevance and actionability of any resulting policy recommendations.
ContributorsKyne, Dean (Author) / Bolin, Bob (Thesis advisor) / Boone, Christopher (Committee member) / Pijawka, David (Committee member) / Arizona State University (Publisher)
Created2014