Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Processes controlling atmospheric dispersion through city centres

We develop a process-based model for the dispersion of a passive scalar in the turbulent flow around the buildings of a city centre. The street network model is based on dividing the airspace of the streets and intersections into boxes, within which the turbulence renders the air well mixed. Mean flow advection through the network of street and intersection boxes then mediates further lateral dispersion. At the same time turbulent mixing in the vertical detrains scalar from the streets and intersections into the turbulent boundary layer above the buildings. When the geometry is regular, the street network model has an analytical solution that describes the variation in concentration in a near-field downwind of a single source, where the majority of scalar lies below roof level. The power of the analytical solution is that it demonstrates how the concentration is determined by only three parameters. The plume direction parameter describes the branching of scalar at the street intersections and hence determines the direction of the plume centreline, which may be very different from the above-roof wind direction. The transmission parameter determines the distance travelled before the majority of scalar is detrained into the atmospheric boundary layer above roof level and conventional atmospheric turbulence takes over as the dominant mixing process. Finally, a normalised source strength multiplies this pattern of concentration. This analytical solution converges to a Gaussian plume after a large number of intersections have been traversed, providing theoretical justification for previous studies that have developed empirical fits to Gaussian plume models. The analytical solution is shown to compare well with very high-resolution simulations and with wind tunnel experiments, although re-entrainment of scalar previously detrained into the boundary layer above roofs, which is not accounted for in the analytical solution, is shown to become an important process further downwind from the source.

Effects of strength and power training on neuromuscular adaptations and jumping movement pattern and performance

Effects of strength and power training on neuromuscular adaptations and jumping movement pattern and performance. J Strength Cond Res 26(12): 3335-3344, 2012-This study aimed at comparing the effects of strength and power training (ST and PT) regimens on neuromuscular adaptations and changes on vertical jump performance, kinetics, and kinematics parameters. Forty physically active men (178.2 +/- 7.0 cm; 75.1 +/- 8.6 kg; 23.6 +/- 3.5 years) with at least 2 years of ST experience were assigned to an ST (n = 14), a PT (n = 14), or a control group (C; n = 12). The training programs were performed during 8 weeks, 3 times per week. Dynamic and isometric maximum strength, cross-sectional area, and muscle activation were assessed before and after the experimental period. Squat jump (SJ) and countermovement jump (CMJ) performance, kinetics, and kinematics parameters were also assessed. Dynamic maximum strength increased similarly (p < 0.05) for the ST (22.8%) and PT (16.6%) groups. The maximum voluntary isometric contraction increased for the ST and PT groups (p < 0.05) in the posttraining assessments. There was a main time effect for muscle fiber cross-sectional area (p < 0.05), but there were no changes in muscle activation. The SJ height increased, after ST and PT, because of a faster concentric phase and a higher rate of force development (p < 0.05). The CMJ height increased only after PT (p < 0.05), but there were no significant changes in its kinetics and kinematics parameters. In conclusion, neuromuscular adaptations were similar between the training groups. The PT seemed more effective than the ST in increasing jumping performance, but neither the ST nor the PT was able to affect the SJ and the CMJ movement pattern (e.g., timing and sequencing of joint extension initiation).

Investigation of factors driving the costs of operating the 2020 Irish power system with large-scale wind generation

The main goal of this work is to determine the true cost incurred by the Republic of Ireland and Northern Ireland in order to meet their EU renewable electricity targets. The primary all-island of Ireland policy goal is that 40% of electricity will come from renewable sources in 2020. From this it is expected that wind generation on the Irish electricity system will be in the region of 32-37% of total generation. This leads to issues resulting from wind energy being a non-synchronous, unpredictable and variable source of energy use on a scale never seen before for a single synchronous system. If changes are not made to traditional operational practices, the efficient running of the electricity system will be directly affected by these issues in the coming years. Using models of the electricity system for the all-island grid of Ireland, the effects of high wind energy penetration expected to be present in 2020 are examined. These models were developed using a unit commitment, economic dispatch tool called PLEXOS which allows for a detailed representation of the electricity system to be achieved down to individual generator level. These models replicate the true running of the electricity system through use of day-ahead scheduling and semi-relaxed use of these schedules that reflects the Transmission System Operator's of real time decision making on dispatch. In addition, it carefully considers other non-wind priority dispatch generation technologies that have an effect on the overall system. In the models developed, three main issues associated with wind energy integration were selected to be examined in detail to determine the sensitivity of assumptions presented in other studies. These three issues include wind energy's non-synchronous nature, its variability and spatial correlation, and its unpredictability. This leads to an examination of the effects in three areas: the need for system operation constraints required for system security; different onshore to offshore ratios of installed wind energy; and the degrees of accuracy in wind energy forecasting. Each of these areas directly impact the way in which the electricity system is run as they address each of the three issues associated with wind energy stated above, respectively. It is shown that assumptions in these three areas have a large effect on the results in terms of total generation costs, wind curtailment and generator technology type dispatch. In particular accounting for these issues has resulted in wind curtailment being predicted in much larger quantities than had been previously reported. This would have a large effect on wind energy companies because it is already a very low profit margin industry. Results from this work have shown that the relaxation of system operation constraints is crucial to the economic running of the electricity system with large improvements shown in the reduction of wind curtailment and system generation costs. There are clear benefits in having a proportion of the wind installed offshore in Ireland which would help to reduce variability of wind energy generation on the system and therefore reduce wind curtailment. With envisaged future improvements in day-ahead wind forecasting from 8% to 4% mean absolute error, there are potential reductions in wind curtailment system costs and open cycle gas turbine usage. This work illustrates the consequences of assumptions in the areas of system operation constraints, onshore/offshore installed wind capacities and accuracy in wind forecasting to better inform the true costs associated with running Ireland's changing electricity system as it continues to decarbonise into the near future. This work also proposes to illustrate, through the use of Ireland as a case study, the effects that will become ever more prevalent in other synchronous systems as they pursue a path of increasing renewable energy generation.

Sustainability of protein production by bioreactor processes using wind and solar power as energy sources

Food production account for significant share of global environmental impacts. Impacts are global warming, fresh water use, land use and some non-renewable substance consumption like phosphorous fertilizers. Because of non-sustainable food production, the world is heading to different crises. Both food- and freshwater crises and also land area and phosphorous fertilizer shortages are one of many challenges to overcome in near future. The major protein sources production amounts, their impacts on environment and uses are show in this thesis. In this thesis, a more sustainable than conventional way of biomass production for food use is introduced. These alternative production methods are photobioreactor process and syngas-based bioreactor process. The processes’ energy consumption and major inputs are viewed. Their environmental impacts are estimated. These estimations are the compared to conventional protein production’s impacts. The outcome of the research is that, the alternative methods can be more sustainable solutions for food production than conventional production. However, more research is needed to verify the exact impacts. Photobioreactor is more sustainable process than syngas-based bioreactor process, but it is more location depended and uses more land area than syngas-based process. In addition, the technology behind syngas-based application is still developing and it can be more efficient in the future.

Role of kinin B1 and B2 receptors in memory consolidation during the aging process of mice

Under physiological conditions, elderly people present memory deficit associated with neuronal loss. This pattern is also associated with Alzheimer`s disease but, in this case, in a dramatically intensified level. Kinin receptors have been involved in neurodegeneration and increase of amyloid-beta concentration, associated with Alzheimer`s disease (AD). Considering these findings, this work evaluated the role of kinin receptors in memory consolidation during the aging process. Male C57BI/6 (wt), knock-out B1 (koB1) or B2 (koB2) mice (3, 6, 12 and 18-month-old - mo; n = 10 per group) were submitted to an acquisition session, reinforcement to learning (24 h later: test 1) and final test (7 days later: test 2), in an active avoidance apparatus, to evaluate memory. Conditioned avoidance responses (CAR, % of 50 trials) were registered. In acquisition sessions, similar CAR were obtained among age matched animals from all strains. However, a significant decrease in CAR was observed throughout the aging process (3mo: 8.8 +/- 2.3%; 6mo: 4.1 +/- 0.6%; 12mo: 2.2 +/- 0.6%, 18mo: 3.6 +/- 0.6%, P < 0.01), indicating a reduction in the learning process. In test 1, as expected, memory retention increased significantly (P < 0.05) in all 3- and 6-month-old animals as well as in 12-month-old-wt and 12-month-old-koB1 (P < 0.01), compared to the training session. However, 12-month-old-koB2 and all 18-month-old animals did not show an increase in memory retention. In test 2, 3- and 6-month-old wt and koB1 mice of all ages showed a significant improvement in memory (P < 0.05) compared to test 1. However, 12-month-old wt and koB2 mice of all ages showed no difference in memory retention. We suggest that, during the aging process, the B1 receptor could be involved in neurodegeneration and memory loss. Nevertheless, the B2 receptor is apparently acting as a neuroprotective factor. (C) 2009 Elsevier Ltd. All rights reserved.

Electric Power Forecasting Methodologies of Some South American Countries: A Comparative Analysis

In this paper, a comparative analysis of the long-term electric power forecasting methodologies used in some South American countries, is presented. The purpose of this study is to compare and observe if such methodologies have some similarities, and also examine the behavior of the results when they are applied to the Brazilian electric market. The abovementioned power forecasts were performed regarding the main four consumption classes (residential, industrial, commercial and rural) which are responsible for approximately 90% of the national consumption. The tool used in this analysis was the SAS (c) program. The outcome of this study allowed identifying various methodological similarities, mainly those related to the econometric variables used by these methods. This fact strongly conditioned the comparative results obtained.

Hybrid Method to Assess Sensitive Process Interruption Costs Due to Faults in Electric Power Distribution Networks

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices.

Digital control and integration of a 192 MW wind farm with doubly fed induction generator into the Brazilian power system

This paper reports on design of digital control for wind turbines and its relation to the quality of power fed into the Brazilian grid on connecting to it a 192 MW wind farm equipped with doubly fed induction generators. PWM converters are deployed as vector controlled regulated current voltage sources for their rotors, for independent control of both active and reactive power of those generators. Both speed control and active power control strategies are analyzed, in the search for maximum efficiency of conversion of wind kinetic energy into electric power and enhanced quality of delivered power. (C) 2009 Elsevier B.V. All rights reserved.

SELF-SIMILARITY AND LAMPERTI CONVERGENCE FOR FAMILIES OF STOCHASTIC PROCESSES

We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Quantitative three-dimensional power Doppler angiography: a flow-free phantom experiment to evaluate the relationship between color gain, depth and signal artifact

Objectives To evaluate the presence of false flow three-dimensional (3D) power Doppler signals in `flow-free` models. Methods 3D power Doppler datasets were acquired from three different flow-free phantoms (muscle, air and water) with two different transducers and Virtual Organ Computer-aided AnaLysis was used to generate a sphere that was serially applied through the 3D dataset. The vascularization flow index was used to compare artifactual signals at different depths (from 0 to 6 cm) within the different phantoms and at different gain and pulse repetition frequency (PR F) settings. Results Artifactual Doppler signals were seen in all phantoms despite these being flow-free. The pattern was very similar and the degree of artifact appeared to be dependent on the gain and distance from the transducer. False signals were more evident in the far field and increased as the gain was increased, with false signals first appearing with a gain of 1 dB in the air and muscle phantoms. False signals were seen at a lower gain with the water phantom (-15 dB) and these were associated with vertical lines of Doppler artifact that were related to PRF, and disappeared when reflections were attenuated. Conclusions Artifactual Doppler signals are seen in flow-free phantoms and are related to the gain settings and the distance from the transducer. In the in-vivo situation, the lowest gain settings that allow the detection of blood flow and adequate definition of vessel architecture should be used, which invariably means using a setting near or below the middle of the range available. Additionally, observers should be aware of vertical lines when evaluating cystic or liquid-containing structures. Copyright (C) 2010 ISUOC. Published by John Wiley & Sons, Ltd.

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Modeling, control and simulation of full-power converter wind turbines equipped with permanent magnet synchronous generator

In this paper, two wind turbines equipped with a permanent magnet synchronous generator (PMSG) and respectively with a two-level or a multilevel converter are simulated in order to access the malfunction transient performance. Three different drive train mass models, respectively, one, two and three mass models, are considered in order to model the bending flexibility of the blades. Moreover, a fractional-order control strategy is studied comparatively to a classical integer-order control strategy. Computer simulations are carried out, and conclusions about the total harmonic distortion (THD) of the electric current injected into the electric grid are in favor of the fractional-order control strategy.

A Pitch Control Malfunction Analysis for Wind Turbines with Permanent Magnet Synchronous Generator and Full-power Converters: Proportional Integral Versus Fractional-order Controllers

A transient analysis for two full-power converter wind turbines equipped with a permanent magnet synchronous generator is studied in this article, taking into consideration, as a new contribution to earlier studies, a pitch control malfunction. The two full-power converters considered are, respectively, a two-level and a multi-level converter. Moreover, a novel control strategy based on fractional-order controllers for wind turbines is studied. Simulation results are presented; conclusions are in favor of the novel control strategy, improving the quality of the energy injected into the electric grid.