Fuel performance codes are used to demonstrate with confidencethat nuclear fuel rods will sustain normal operation and transientevents without being damaged. However, the execution time of a typ-ical fuel rod simulation ranges from tens of seconds to minutes which can be impractical in certain applications. In the scope of this work,at least two such applications are identified; code-calibration and fuelcore evaluations. In both of these cases, possible improvements can be obtainedby creating neural network surrogate models. For code calibration,a Deep Neural Network is enough since calibration is performed onmodel constants. But for full-core evaluations, a surrogate model mustbe able to predict a time-dependent target as a function of a time-dependent input. In this work, Temporal Convolutional Networks are investigated for the second application. In both applications, targetdata are generated with a Cladding Oxidation Model. The result of the study shows that both models succeeded in their respective tasks with good performance metrics. However, furtherwork is needed to increase the number of input and target variablesthat the Deep Neural Network can handle, verify the flexibility ofinput data files for the TCN, try out the TCN on a real code, and combine the two models and achieve a broader set of use-cases. / <p>Kursnamn: Fördjupande projektarbete i energisystem</p><p>Kurskod: 1FA394</p>

How people perceive risk or threats is important to many disciplines that seek to assist policy makers in developing policies, regulations and laws. Using the previous work of Slovic et al. (Fischhoff, Slovic, Lichtenstein, Read and Combs, 2000; Slovic P., 1992; Slovic, Fischhoff, and Lichtenstein, 2000) in development of the psychometric paradigm, a sample of residents (n=600) from a region with a large number of nuclear reactors was surveyed. The question set was expanded to include demographic questions to determine if they impact risk perception. Two aspects of risk perception were examined, perception of overall risk and perception of riskiness along specific dimensions of concern identified previously in the literature. For both risk and riskiness, respondents’ perceptions of nuclear power were compared to three other perceptions of technologies including use of modern farming methods using chemicals, railroad transportation and coal-generated electricity. The recent increase in public concern about nuclear power following the meltdowns at the Fukushima Dai-ichi nuclear power plant led to the expectation that nuclear power would be rated higher in overall risk and riskiness than the other three technologies consistent with Slovic’s earlier work on risk perception. This expectation was generally supported although respondents tended to perceive modern farming methods using chemical as similar in overall risk and riskiness to nuclear power. The research specifically tested five hypotheses concerning the impact of five demographic factors: gender, race, income, education and political orientation on the overall perception of risk and riskiness. Subsequent analysis using analysis of variance and linear regression found that select demographics only explained 2% of the risk perception for nuclear power generation.

The aim of this diploma work has been to work up a first study dealing with possibilities of enlargement of Slavětice substation with the new sources of Dukovany power-plant (EDU). In this work I am mentioning the linking of 400 kV Slavětice substation into the electricity system in Czech Republic and its coupling into the west-European UCTE system and I am also itemizing the basic data of neighbouring substations. Further I am describing the current state of 400 kV and 110 kV substations in Slavětice, their parameters and scheme. In this work I am mentioning basic information of nuclear reactor piles, coming into consideration for the prospective new pile construction in the premises of Dukovany substation and also reflections about possibilities of bringing out power of this new pile. In the following part of my diploma work there are stated proposals of different versions for enlarging the Slavětice 400 kV substation by a new outlet of new EDU source and the eventual overhead-line construction. I am mentioning the necessary substation arrangements for each proposed version, the scheme, eventually the proposal how to lay-out the new lines. Further there is stated here a proposal of outgoing feeder switchgear accessories for the new EDU pile and also the proposal for an entirely new substation, its description and scheme. An evaluation of all proposed versions of Slavětice substation enlargement for connecting new nuclear piles is stated in the outcome of the work.

The entire diploma thesis analyses causes, consequences and repercussions of an electricity grid network blackout and its impact to the respective consumers. Remarkable blackouts recorded since 1965 are briefly described and basic available information is considered. The grid standard fixing measures and electricity delivery priorities are characterized. The thesis also pays attention to entire Czech Republic grid availability and its blackout endurance as well as to its robustness within last several years. Indirect Fukushima event influence to the Czech Republic electricity system is mentioned. The main part of the thesis comprises of four big European grid blackouts causes and consequences, their comparison to each other and to the Dukovany nuclear power plant grid blackout drill scenario. The preventive and standard corrective measures against blackouts are pointed out.

This thesis' objective is to analyse local environmental impact of NPP. For impact determination, it is necessary to monitor the locality for a long period. For biomonitoring method, gamma-spectrometers might be used. It should be calibrated before the measurement. Within the thesis investigation, spectrometer of the faculty was calibrated in the laboratory of ionizing radiation and three samples of Czech nuclear facilities outlet were analysed.

This diploma thesis deals with a pressure suppression system containment during the loss of coolant accidents. It is focused on the containment systems of the nuclear power plants with VVER-440/V-213 reactors. There is described the process of loss of coolant accident. There was designed input model which consists of the zones representing the areas which are connected with junctions and heat structures. Were then selected input parameters for the model calculations. And finally, there have been several calculations for the selected parameters.

This thesis deals with the determination of 14C activity in liquid discharges from the Czech nuclear power plants and with the estimation of their radiological impacts on the vicinity of nuclear power plants. This work summarizes the issue of 14C liquid discharges of several nuclear power plants in the world and Czech nuclear power plants are compared to them. The sewage routs of liquid discharges from control tanks to waste water station are described in this thesis for both power plants - Dukovany and Temelín. Measured values of the 14C activity in liquid discharges from nuclear power plants Temelín and Dukovany are presented in this work. The procedure for calculating the exposure of representative persons as a result of liquid discharge of 14C activity is described in this thesis. The resulting values of annual commited effective dose for each age category of representative persons are presented in this work.

The Great East Japan earthquake and the resulting tsunami struck Japan east coast on March 11th 2011. All nuclear power plants on the east coast were automatically shut down, and several thermal plants were damaged: Japan was left with only 19% of its nuclear capacity available (i.e. 9 GW). The Fukushima-Daiichi nuclear power plant underwent major incidents, with a fusion of the nuclear core and radioactivity leakage, the most important nuclear accident since Chernobyl. During the summer 2011, the Japanese government undertook emergency measures to offset the expected 20% capacity shortage in Tokyo and Tohoku areas. On the supply side, capacity was recovered by restarting and restoring fossil-fuelled power generation, and importing power from neighboring areas. On the demand side, stringent demand restriction measures led to a summer peak demand 10 GW lower in the Tokyo area and 3.1 GW lower in the Tohoku area, compared to 2010. In early 2012, only 2 reactors were still in operation, after further nuclear shutdowns. Market-driven electricity conservation reforms and subsidy-driven supply capacity additions aim to avoid emergency measures in the summer 2012 similar to those of summer 2011, and offset the expected 9% power deficit in the country. For the longer term, Japan government has launched various initiatives to review the 2010 Basic Energy Plan, which envisaged a nuclear expansion. In this study, a model was developed to assess the economic and environmental impacts of three contrasted scenarios, reflecting different options for Japan’s electricity mix by 2050. The results show that a nuclear phase-out would induce additional costs of the order of €850bn to the power system over the period 2010-50, compared to the Basic Energy Plan, while also preventing Japan to reach its CO2 emissions’ reduction targets by 2050. A sensitivity analysis shows that a reduced renewables development would lower the cost of the power system, but put aside climate change mitigation and energy security of supply. On the other hand, a reduced electricity demand through energy efficiency measures would have a positive impact on both CO2 emissions and the security of supply. / <p>-</p> / -

Electrical production in Sweden today is mainly from nuclear and hydro power. However, there is large increase in renewable energy like wind power and the installed new capacity goals are large. Several electrical production sources are important for the sustainability of the energy system. Maintenance is an approach for keeping a system sustainable. The importance of structured maintenance for reliable electrical production systems triggers the development of qualitative and quantitative maintenance management methods. Examples of these methods are Reliability-Centered Maintenance (RCM) which is a structured qualitative approach that focuses on reliability when planning maintenance, and Reliability Centered Asset Management (RCAM) which is a development of RCM into a quantitative approach with the aim to relate preventive maintenance to total maintenance cost and system reliability. This thesis presents models, as applications of RCAM, based on the methods of Life Cycle Cost (LCC) and mathematical optimization, applied to wind and nuclear power plants. Both deterministic and stochastic approaches have been used and the proposed models are based on the Total Cost model, which summarizes costs for maintenance and production loss, and the Aircraft model, which is an opportunistic maintenance optimization model. Opportunistic maintenance is preventive maintenance performed at opportunities. The wind power applications in this study show on different ways to cover costs of condition monitoring systems (CMS) and further on economic benefits of these when uncertainties of times to failure are included in the model. The nuclear power applications show on that the optimization model is dependent on the discount rate and that a high discount rate gives more motivation for opportunistic replacements. When put into a stochastic framework and compared to other maintenance strategies it is shown that an extended opportunistic maintenance optimization model has a good overall performance, and that it, for high values of the constant cost of performing maintenance, is preferable to perform opportunistic maintenance. The proposed models, applied to wind and nuclear power plants, could be extended and adapted to fit other components and systems. / Reliability and cost centered maintenance methods

The power output at the Forsmark nuclear power plant sometimes deviates from the expected value. The causes of these deviations are sometimes known and sometimes unknown. Three types of machine learning methods (k-nearest neighbors, support vector machines and linear regression) were trained to predict whether or not the power deviation would be outside an expected interval. The data used to train the models was gathered from points in the power production process and the data signals consisted mostly of temperatures, pressures and flows. A large part of the project was dedicated to preparing the data before using it to train the models. Temperature signals were shown to be the best predictors of deviation in power, followed by pressure and flow. The model type that performed the best was k-nearest neighbors, followed by support vector machines and linear regression. Principal component analysis was performed to reduce the size of the training datasets and was found to perform equally well in the prediction task as when principal component analysis was not used.