Analysis of a controversial decision process: the case of the pumped hydro storage power plant Atdorf in Germany

Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

Compositional Time Series: An Application

The composition of the labour force is an important economic factor for a country.Often the changes in proportions of different groups are of interest.I this paper we study a monthly compositional time series from the Swedish LabourForce Survey from 1994 to 2005. Three models are studied: the ILR-transformed series,the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformationof the compositional differenced series of order 12. For each of thethree models a VAR-model is fitted based on the data 1994-2003. We predict the timeseries 15 steps ahead and calculate 95 % prediction regions. The predictions of thethree models are compared with actual values using MAD and MSE and the predictionregions are compared graphically in a ternary time series plot.We conclude that the first, and simplest, model possesses the best predictive power ofthe three models

Lag-one autocorrelation in short series: Estimation and hypothesis testing

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.

Short-term forecasting of power demand in the Nord Pool market

Sähkönkulutuksen lyhyen aikavälin ennustamista on tutkittu jo pitkään. Pohjoismaisien sähkömarkkinoiden vapautuminen on vaikuttanut sähkönkulutuksen ennustamiseen. Aluksi työssä perehdyttiin aiheeseen liittyvään kirjallisuuteen. Sähkönkulutuksen käyttäytymistä tutkittiin eri aikoina. Lämpötila tilastojen käyttökelpoisuutta arvioitiin sähkönkulutusennustetta ajatellen. Kulutus ennusteet tehtiin tunneittain ja ennustejaksona käytettiin yhtä viikkoa. Työssä tutkittiin sähkönkulutuksen- ja lämpötiladatan saatavuutta ja laatua Nord Poolin markkina-alueelta. Syötettävien tietojen ominaisuudet vaikuttavat tunnittaiseen sähkönkulutuksen ennustamiseen. Sähkönkulutuksen ennustamista varten mallinnettiin kaksi lähestymistapaa. Testattavina malleina käytettiin regressiomallia ja autoregressiivistä mallia (autoregressive model, ARX). Mallien parametrit estimoitiin pienimmän neliösumman menetelmällä. Tulokset osoittavat että kulutus- ja lämpötiladata on tarkastettava jälkikäteen koska reaaliaikaisen syötetietojen laatu on huonoa. Lämpötila vaikuttaa kulutukseen talvella, mutta se voidaan jättää huomiotta kesäkaudella. Regressiomalli on vakaampi kuin ARX malli. Regressiomallin virhetermi voidaan mallintaa aikasarjamallia hyväksikäyttäen.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Distributed ControlArchitecture of Power Electronics Building-Block-Based Frequency Converters

The increasing power demand and emerging applications drive the design of electrical power converters into modularization. Despite the wide use of modularized power stage structures, the control schemes that are used are often traditional, in other words, centralized. The flexibility and re-usability of these controllers are typically poor. With a dedicated distributed control scheme, the flexibility and re-usability of the system parts, building blocks, can be increased. Only a few distributed control schemes have been introduced for this purpose, but their breakthrough has not yet taken place. A demand for the further development offlexible control schemes for building-block-based applications clearly exists. The control topology, communication, synchronization, and functionality allocationaspects of building-block-based converters are studied in this doctoral thesis. A distributed control scheme that can be easily adapted to building-block-based power converter designs is developed. The example applications are a parallel and series connection of building blocks. The building block that is used in the implementations of both the applications is a commercial off-the-shelf two-level three-phase frequency converter with a custom-designed controller card. The major challenge with the parallel connection of power stages is the synchronization of the building blocks. The effect of synchronization accuracy on the system performance is studied. The functionality allocation and control scheme design are challenging in the seriesconnected multilevel converters, mainly because of the large number of modules. Various multilevel modulation schemes are analyzed with respect to the implementation, and this information is used to develop a flexible control scheme for modular multilevel inverters.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

Colossal thermoelectric power in Gd-Sr manganites

Manganites belonging to the series Gd1−xSrxMnO3 (x=0.3, 0.4 and 0.5) were prepared by wet solid-state reaction and their thermoelectric power was evaluated. Thermoelectric power measurements revealed a peak value at ∼40 K. All the samples exhibited a colossal thermopower at ∼40K and in that Gd0.5Sr0.5MnO3 exhibited a maximum value of ∼35mV/K, which is the largest reported for these class of materials at this temperature. Temperaturedependent magnetisation measurements showed that the samples exhibit a phase transition from paramagnetic to spin-glass–like state at these temperatures. Plausible mechanisms responsible for the observed colossal thermoelectric power in Gd-Sr manganites are discussed

Compositional Time Series: An Application

The composition of the labour force is an important economic factor for a country. Often the changes in proportions of different groups are of interest. I this paper we study a monthly compositional time series from the Swedish Labour Force Survey from 1994 to 2005. Three models are studied: the ILR-transformed series, the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformation of the compositional differenced series of order 12. For each of the three models a VAR-model is fitted based on the data 1994-2003. We predict the time series 15 steps ahead and calculate 95 % prediction regions. The predictions of the three models are compared with actual values using MAD and MSE and the prediction regions are compared graphically in a ternary time series plot. We conclude that the first, and simplest, model possesses the best predictive power of the three models

La proyección de imagen a partir de Soft Power, mediante Nation Branding y Diplomacia Pública en el caso de Japón, durante el periodo 2002 – 2010

En el actual contexto de globalización y con el comienzo de la era de la información, cada vez más Estados han buscado proyectar una imagen favorable con el objetivo de atraer atención y crear una reputación que permitan cumplir objetivos de política exterior y fomentar el desarrollo económico, logrando de esta manera un posicionamiento en el sistema internacional mediante estrategias novedosas, que incluyen elementos tanto diplomáticos, políticos, económicos, como comerciales y culturales. Para Japón, Nation Branding y la diplomacia pública han sido dos de las principales herramientas para lograr este reposicionamiento internacional, resaltando atractivos como las tradiciones culturales, el turismo, los incentivos para negocios, y trabajando en conjunto entre el gobierno nacional, el sector privado y la sociedad civil para crear relaciones entre el país y gobiernos y sociedades a nivel internacional.

Performance and efficiency in Colombia's power utilities: an assessment of the 1994 reform

El artículo describe las características centrales de la reforma regulatoria al sector eléctrico en 1994 y evalúa el desempeño y la eficiencia de las empresas públicas antes y después de la reforma. El análisis de desempeño evalúa los cambios en medias y medianas en ganancias, eficiencia, inversión y ventas de las empresas privatizadas en el sector. La eficiencia técnica es estimada mediante la técnica DEA en una muestra de 33 plantas térmicas de energía, que representan el 85% del parque térmico; y 12 empresas distribuidoras de energía. La muestra de plantas generadoras está compuesta por plantas que estaban activas antes de la reforma y plantas nuevas que entraron en operación después de la reforma. Los principales resultados muestran que la eficiencia mejoro después de la reforma y que la política regulatoria ha tenido un efecto positivo en la eficiencia de la generación térmica de energía. Por el contrario, las distribuidoras de energía menos eficientes empeoraron después de la reforma y no llevaron a cabo una reestructuración para alcanzar la eficiencia productiva respecto a las empresas que conforman la frontera de eficiencia en distribución de energía.

La política exterior turca en el marco del Complejo de Seguridad Regional de Medio Oriente. Del soft power al smart power. (2002 - 2013)

Dada la confluencia de Turquía en Asia, Medio Oriente, los Balcanes y Europa, el gobierno está en la necesidad de responder a los desafíos de ser un Estado pivote. Es en este punto donde su política exterior se convierte en la mayor herramienta para sobresalir y sobrevivir en un ambiente heterogéneo. El objetivo de esta monografía de grado es analizar la política exterior turca en el marco del Complejo de Seguridad Regional de Medio Oriente a partir de los aportes de la Escuela de Copenhague y su Teoría de los Complejos de Seguridad Regional, para comprender sus estrategias de soft y hard power en su política exterior a fin de analizar si se consolidó un smart power que permita posicionar a Turquía en una potencia regional.

Comparing meta-analysis and ecological-longitudinal analysis in time-series studies: a case study of the effects of air pollution on mortality in three Spanish cities

The objective of this paper is to introduce a diVerent approach, called the ecological-longitudinal, to carrying out pooled analysis in time series ecological studies. Because it gives a larger number of data points and, hence, increases the statistical power of the analysis, this approach, unlike conventional ones, allows the complementation of aspects such as accommodation of random effect models, of lags, of interaction between pollutants and between pollutants and meteorological variables, that are hardly implemented in conventional approaches. Design—The approach is illustrated by providing quantitative estimates of the short-termeVects of air pollution on mortality in three Spanish cities, Barcelona,Valencia and Vigo, for the period 1992–1994. Because the dependent variable was a count, a Poisson generalised linear model was first specified. Several modelling issues are worth mentioning. Firstly, because the relations between mortality and explanatory variables were nonlinear, cubic splines were used for covariate control, leading to a generalised additive model, GAM. Secondly, the effects of the predictors on the response were allowed to occur with some lag. Thirdly, the residual autocorrelation, because of imperfect control, was controlled for by means of an autoregressive Poisson GAM. Finally, the longitudinal design demanded the consideration of the existence of individual heterogeneity, requiring the consideration of mixed models. Main results—The estimates of the relative risks obtained from the individual analyses varied across cities, particularly those associated with sulphur dioxide. The highest relative risks corresponded to black smoke in Valencia. These estimates were higher than those obtained from the ecological-longitudinal analysis. Relative risks estimated from this latter analysis were practically identical across cities, 1.00638 (95% confidence intervals 1.0002, 1.0011) for a black smoke increase of 10 μg/m3 and 1.00415 (95% CI 1.0001, 1.0007) for a increase of 10 μg/m3 of sulphur dioxide. Because the statistical power is higher than in the individual analysis more interactions were statistically significant,especially those among air pollutants and meteorological variables. Conclusions—Air pollutant levels were related to mortality in the three cities of the study, Barcelona, Valencia and Vigo. These results were consistent with similar studies in other cities, with other multicentric studies and coherent with both, previous individual, for each city, and multicentric studies for all three cities