[pt] A demanda global por soluções sustentáveis para geração de energia elétrica cresceu rapidamente nas últimas décadas, sendo impulsionada por incentivos fiscais dos governos e investimentos em pesquisa e desenvolvimento de tecnologias. Isso provocou uma crescente inserção de fontes renováveis nas redes elétricas ao redor do mundo, criando novos desafios críticos para as avaliações de desempenho dos sistemas que são potencializados pela intermitência desses recursos energéticos combinada às falhas dos equipamentos de rede. Motivado por esse cenário, esta dissertação aborda a estimativa de risco de inadequação de grandezas elétricas, como ocorrências de sobrecarga em ramos elétricos ou subtensão em barramentos, através do uso do fluxo de potência probabilístico, baseado na simulação Monte Carlo e no método de entropia cruzada. O objetivo é determinar o risco do sistema não atender a critérios operativos, de forma precisa e com eficiência computacional, considerando as incertezas de carga, geração e transmissão. O método é aplicado aos sistemas testes IEEE RTS 79 e IEEE 118 barras, considerando também versões modificadas com a inclusão de uma usina eólica, e os resultados são amplamente discutidos. / [en] The global demand for sustainable solutions for electricity generation has grown rapidly in recent decades, driven by government tax incentives and investments in technology research and development. This caused a growing insertion of renewable sources in power networks around the world, creating new critical challenges for systems performance assessments that are enhanced by the intermittency of these energy resources combined with the failures of network equipment. Motivated by this scenario, this dissertation addresses the estimation of risk of inadequacy of electrical quantities, such as overload occurrences in electrical branches or undervoltage in buses, through the use of probabilistic power flow, based on Monte Carlo simulation and the cross-entropy method. The objective is to determine the risk of the system not meeting operational criteria, precisely and with computational efficiency, considering load, generation and transmission uncertainties. The method is applied to IEEE RTS 79 and IEEE 118 bus test systems, also considering modified versions with the inclusion of a wind power plant, and the results are widely discussed.

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<p dir="ltr">Distributed energy resources (DERs), such as rooftop solar generation and energy storage systems, are becoming more prevalent in distribution systems. DERs are connected to the distribution system via power electronic converters, introducing faster dynamics in the system. Understanding the system dynamics under a high penetration of inverter-based DERs is critical for power system researchers and practitioners, driving the development of modeling techniques and simulation software. Aiming to reduce computational complexity, existing tools and techniques often employ various approximations. Meanwhile, modern advancements in computational hardware capabilities provide opportunities to include the faster time-scale dynamics. To address this, the primary objective of this thesis is to develop an open-source Python simulation package, Dynamic Simulation using Sparse Tableau Approach in Python, DynaSTPy (pronounced “dynasty”), capable of capturing the dynamics of all components in a distribution feeder. The distribution feeder is modeled as a system of Differential-Algebraic Equations (DAEs). Further, each component in the feeder is modeled based on the Sparse Tableau Approach (STA), which involves the representation of component model equations using sparse matrices, facilitating a systematic procedure to model the components and construct the system DAEs. In sinusoidal steady state, the DAEs can be represented in phasor form, extending the approach to perform power flow analysis of distribution feeders.</p>

<p>U disertaciji je obrađen problem proračuna nesimetričnih tokova<br />snaga neuravnoteženih prenosnih i aktivnih distributivnih mreža<br />velikih dimenzija, naročito onih sa energetskim resursima<br />zasnovanim na uređajima energetske elektronike. Pri tome je dat dokaz<br />da tradicionalna klasifikacija čvorova nije dovoljna da se precizno<br />modeluju i rešavaju nesimetrični tokovi snaga navedenih mreža.<br />Zatim je predložena nova klasifikacija čvorova sa odgovarajućim<br />metodima tokova snaga. Time je omogućena vrlo precizna formulacija<br />i proračun modela nesimetričnih tokova snaga navedenih mreža. Ta<br />preciznost metoda tokova snaga je rezultat toga što su novom<br />klasifikacijom čvorova obuhvaćene sve praktično primenjene<br />upravljačke strategije tradicionalnih naizmeničnih mašina, a<br />naročito energetskih resursa koji su zasnovani na energetskoj<br />elektronici.</p> / <p>This thesis deals with power flow calculations of unbalanced large scale<br />transmission networks and active distributive networks, especially ones<br />with electronically interfaced resources. The proof that the traditional bus<br />classification is not sufficient for precise modeling and calculation of power<br />flow of these networks is given first. Then, a new bus classification and<br />corresponding very precise power flow model and calculation of<br />aforementioned networks are proposed. This precision of power flow<br />calculation is the result of encompassing of all control strategies of modern<br />energy resources by the new bus classification.</p>

Oregon's ocean waters are a potential source of wind, wave, and tidal energy; of interest to renewable energy entrepreneurs and to the U.S. government as it seeks to bolster energy security. In order to install technology to capture this energy, however, it may be necessary to mitigate conflict with existing ocean space users. The objective of this research was to construct a conflict analysis model in a GIS to answer the following research questions: (1) Within the study area off the coast of Oregon, where are stakeholders currently using ocean space and how many uses overlap? (2) To what extent might existing ocean space use present potential for conflict with renewable energy development? (3) How do various types of uncertainty affect analysis results? (4) What are the implications of these findings for ecosystem based management of the ocean? All available spatial information on ocean space usage by commercial fishing, commercial non-fishing, recreational, Native American, and scientific communities was gathered. Stakeholder outreach with these communities was used to vet the collected data and allow each to contribute knowledge not previously available through GIS data clearinghouses maintained by government or interest groups. The resulting data were used as inputs to a conflict visualization model written in Python and imported to an ArcGIS tool. Results showed extensive coverage and overlap of existing ocean space uses; specifically that 99.7% of the 1-nm² grid cells of the study area are occupied by at least 6 different categories of ocean space use. The six uses with the greatest coverage were: Fishing – Trolling, Habitat, Military, Fishing - Closure Areas, Protected, and Marine Transportation - Low Intensity. An uncertainty analysis was also completed to illustrate the margin for error and therefore the necessity of appropriate stakeholder outreach during the renewable energy siting process, as opposed to relying only on a GIS. Ranking of each category by its potential for conflict with renewable energy development demonstrated which areas of the ocean may be particularly contentious. Because rankings are subjective, a tool was created to allow users to input their own rankings. For the purpose of this report, default rankings were assigned to each as justified by the literature. Results under these assumptions showed that space use and potential for conflict were highest between the coast and approximately 30 nm at sea. This is likely because certain space use is limited by depth (e.g., recreational use); there is increased shipping density as vessels approach and depart major ports; and increased fuel costs associated with traveling further from shore. Two potential applications of model results were demonstrated. First, comparison with existing wave energy permit sites highlighted relative potential for conflict among the sites and the input data detailed the specific uses present. Second, comparison with areas determined most suitable for development by the wave energy industry illustrated that areas of high suitability often also had high rankings for potential for conflict. It appeared that the factors that determined development suitability were often the same factors that drew current ocean space users to those locations. Current support at the state, regional and federal level under the National Ocean Policy for the use of marine spatial planning as a tool to implement ecosystem based management of the oceans requires that tools such as the one developed in this research are used, to ensure that all components of the marine ecosystem are considered prior to implementation of a management plan. The addition of renewable energy to the current social landscape of the ocean will reduce the resource base for many categories of ocean space use. Model results demonstrated that mitigation of conflict between development and existing space use is not merely a best practice supported by current policy, but a necessity. Results presented a visualization of the social landscape of the ocean that could help managers determine which stakeholders to engage during the initial stage of choosing a site for development. / Graduation date: 2012

Wind power presently plays a minor role in Western Canada as compared to hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation facilities and the increasing costs of conventional power generation, particularly if the cost to the environment is included, suggest that assessment of the present and future wind field in Western Canada is of some importance. To assess present wind power, raw hourly wind speeds and homogenized monthly mean wind speeds from 30 stations in Western Canada were analyzed over the period 1971-2000 (past). The hourly data were adjusted using the homogenized monthly means to attempt to compensate for differences in anemometer height from the standard height of 10m and changes in observing equipment at stations. A regional reanalysis product, the North American Regional Reanalysis (NARR), and simulations conducted with the Canadian Regional Climate Model (CRCM) driven with global reanalysis boundary forcing, were compared to the adjusted station wind-speed time-series and probability distributions. The NARR had a better temporal correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional topography in NARR. While the CRCM was run at both standard (45 km) and fine (15 km) resolution, the fine grid spacing does not always provide better results: the character of the surrounding topography appears to be an important factor for determining the level of agreement. Multiple simulations of the CRCM at the 45 km resolution were also driven by two global climate models (GCMs) over the periods 1971-2000 (using only historic emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and 25 projected wind speed distributions for the 2031-2060 period (future) at the station locations. Both bias correction and change factor techniques were used for calibration. At most station locations modest increases in mean wind speed were found for most of the projected distributions, but with a large variance. Estimates of wind power density for the projected speed distributions were made using a relationship between wind speed and power from a CRCM simulation for both time periods using the 15km grid. As would be expected from the wind speed results and the proportionality of wind power to the cube of wind speed, wind power at the station locations is more likely than not to increase in the 2031-2060 period from the 1971-2000 period. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and choice of calibration technique, suggesting that we estimate relative change at all 45km grid points using all pairs of past/future mean wind speeds from the CRCM simulations. Overall, our results suggest that wind energy resources in Western Canada are reasonably likely to increase at least modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca

The economic level of the individual states, the community and the global economy depends on reliable activity and the results of individual economic sectors and subsectors, including all participants in this process. From the entire spectrum of economic sectors the energy sector has been selected as the most important and critical infrastructure in the Czech Republic, the EU, and in the world. The selected energy sector subdivides into other subsectors: electricity, natural gas and oil. The work deals with the analysis of the above mentioned sectors, their fundamentals, stocks, consumption, equipment, resources, entities, price developments and potential risks. The aim of the work is to analyse the state of the energy resources in the Czech Republic, the EU, and in the world, including current and potential threats, to which the key infrastructures have to face.

This master’s thesis named “The Life Cycle of Solar Power, Efficiency and Return” is divided into seven chapters and focuses on the utilization of solar radiation in photovoltaic power stations and solar thermal power stations. The first chapter of this thesis familiarizes the reader with issues concerning renewable resources of energy and presents an overview of the focus of each chapter. The following second chapter is occupied with a topical research of renewable resources of energy utilization in Europe. Further the author presents a brief glance back at the past of solar energy utilization and also a prediction of future solar energy utilization in the Czech Republic. The chapter named “Specification and parameterization of individual technologies” contains an overview of today’s most utilized photovoltaic cells and panels together with an overview of utilized solar collectors and solar thermal power stations. In the following chapter named “Concretization of typical applications and realizations of photovoltaic and solar thermal power stations and determination of all related parameters” the author describes further components of photovoltaic and solar thermal systems. The economical aspect of photovoltaic component production together with an overview of utilized photovoltaic technologies is presented in this chapter. The problem of recycling photovoltaic applications and the current legislative situation regarding this issue in the Czech Republic is also outlined within this chapter. In the fifth chapter of this master’s thesis the author presents mathematical models of a photovoltaic and a solar thermal power station with the focus on economic aspects of investment efficiency assessment. Within this master’s thesis a simulation program in the computational software program Mathematica was created by the author. This program allows a calculation of economic efficiency and return of photovoltaic power station investments. The results of executed simulations are presented in the sixth chapter of this thesis. The last chapter contains an appraisal and summary of results achieved by the author of this thesis.

This thesis deals with designing a small hydraulic power plant, where a swirl turbine is conected to a unique synchronous working, which will offer a reliable and easy installation of the hydraulic power plant. As a result a wider potential of energy could be produced from renewable resources. The use of a narrow rottor as a holder of the permanent magnets is the biggest difficulties of this design.

MSc (Statistics) / Department of Statistics / Wind offers an environmentally sustainable energy resource that has seen increasing global adoption in recent years. However, its intermittent, unstable and stochastic nature hampers its representation among other renewable energy sources. This work addresses the forecasting of wind speed, a primary input needed for wind energy generation, using data obtained from the South African Wind Atlas Project. Forecasting is carried out on a two days ahead time horizon. We investigate the predictive performance of artificial neural networks (ANN) trained with Bayesian regularisation, decision trees based stochastic gradient boosting (SGB) and generalised additive models (GAMs). The results of the comparative analysis suggest that ANN displays superior predictive performance based on root mean square error (RMSE). In contrast, SGB shows outperformance in terms of mean average error (MAE) and the related mean average percentage error (MAPE). A further comparison of two forecast combination methods involving the linear and additive quantile regression averaging show the latter forecast combination method as yielding lower prediction accuracy. The additive quantile regression averaging based prediction intervals also show outperformance in terms of validity, reliability, quality and accuracy. Interval combination methods show the median method as better than its pure average counterpart. Point forecasts combination and interval forecasting methods are found to improve forecast performance. / NRF