83 resultados para normalized energy


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The threat of global warming and its consequences are widely recognized, and the question of how to proceed with the long transition towards fossil fuel -neutral economies concerns many nations and people. At the same time the world’s primary energy use is predicted to increase significantly during the next decades as a result of global population and welfare increase. Improved energy efficiency and increased use of renewable energy sources in the world’s energy mix play important roles in the future energy production and consumption. The objective of this thesis is to study how novel renewable energy technologies, such as distributed small-scale bio-fueled combined heat and power production and wind power technologies could be commercialized efficiently. A wide array of attributes may contribute to the diffusion of new products. In general, the bioenergy and wind power technologies are in emerging phases, and the diffusion stage varies from country to country. The effects of firms’ technology choices, collaboration and alliances are studied in this thesis. Furthermore, the roles of national energy infrastructure and energy support schemes in the commercialization of new renewable energy products are explored. The empirical data is based on energy expert interviews, financial and patent data, and literature reviews of different case studies. The thesis comprises two parts. The first part provides an overview of the study, and the second part includes six research publications. The results reveal that small-scale bio-fueled combined heat and power production and wind power technologies are still in emerging phases in their life cycles, and energy support schemes are crucial in the market diffusion. The study contributes to earlier findings in the literature and industry by confirming that adequate energy policies and energy infrastructure are fundamental in the commercialization of novel renewable energy technologies. Firm-specific issues, including business relationships and new business models, and market-related issues will have a more significant role in the market penetration in the future, when the technologies mature and become competitive without political support schemes.

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Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

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RENSOL (Regional Energy Solutions) project deals with the use of energy efficiency and renewable energy solutions in Kaliningrad Oblast to tackle climate change. Overall objective of the RENSOL work package 1 is to build awareness and knowledge on solutions for energy efficient buildings and street lightning applications. The project report describes available solutions to improve housing energy efficiency.

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The purpose of this thesis is to identify the Performance Determinants (PD) of Renewable Energy (RE) companies. It analyzes the background of the RE industry while reflecting simultaneous developments in the fossil based industries. I divided the determinants into two groups: market level and firm level and established hypotheses based on the existing literature. Data from public companies was gathered to construct a Panel Data structure. This is then tested by using a Linear Regression with Fixed Effects model. The model specification was efficient at reflecting the analyzed phenomena. My results showed that both market level and firm level determinants are significant in the RE Industry but the firm level determinants had higher explanatory power (R2). The determinants' relationships were found to follow those from the manufacturing industry more than the utilities' industry. Out of the market level determinants Consumer Price Index (CPI), Interest Rates and Oil prices were significant. Out of the firm level determinants Debt to Assets, Net Investments, Cash flows from operations, Sales and Earnings Before Interests and Taxes (EBIT) were significant. I concluded that this information is valuable for key industry players as they can achieve their objectives faster by elaborating better strategies using these results.

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The superconducting gap is a basic character of a superconductor. While the cuprates and conventional phonon-mediated superconductors are characterized by distinct d- and s-wave pairing symmetries with nodal and nodeless gap distributions respectively, the superconducting gap distributions in iron-based superconductors are rather diversified. While nodeless gap distributions have been directly observed in Ba1–xKxFe2As2, BaFe2–xCoxAs2, LiFeAs, KxFe2–ySe2, and FeTe1–xSex, the signatures of a nodal superconducting gap have been reported in LaOFeP, LiFeP, FeSe, KFe2As2, BaFe2–xRuxAs2, and BaFe2(As1–xPx)2. Due to the multiplicity of the Fermi surface in these compounds s± and d pairing states can be both nodeless and nodal. A nontrivial orbital structure of the order parameter, in particular the presence of the gap nodes, leads to effects in which the disorder is much richer in dx2–y2-wave superconductors than in conventional materials. In contrast to the s-wave case, the Anderson theorem does not work, and nonmagnetic impurities exhibit a strong pair-breaking influence. In addition, a finite concentration of disorder produces a nonzero density of quasiparticle states at zero energy, which results in a considerable modification of the thermodynamic and transport properties at low temperatures. The influence of order parameter symmetry on the vortex core structure in iron-based pnictide and chalcogenide superconductors has been investigated in the framework of quasiclassical Eilenberger equations. The main results of the thesis are as follows. The vortex core characteristics, such as, cutoff parameter, ξh, and core size, ξ2, determined as the distance at which density of the vortex supercurrent reaches its maximum, are calculated in wide temperature, impurity scattering rate, and magnetic field ranges. The cutoff parameter, ξh(B; T; Г), determines the form factor of the flux-line lattice, which can be obtained in _SR, NMR, and SANS experiments. A comparison among the applied pairing symmetries is done. In contrast to s-wave systems, in dx2–y2-wave superconductors, ξh/ξc2 always increases with the scattering rate Г. Field dependence of the cutoff parameter affects strongly on the second moment of the magnetic field distributions, resulting in a significant difference with nonlocal London theory. It is found that normalized ξ2/ξc2(B/Bc2) dependence is increasing with pair-breaking impurity scattering (interband scattering for s±-wave and intraband impurity scattering for d-wave superconductors). Here, ξc2 is the Ginzburg-Landau coherence length determined from the upper critical field Bc2 = Φ0/2πξ2 c2, where Φ0 is a flux quantum. Two types of ξ2/ξc2 magnetic field dependences are obtained for s± superconductors. It has a minimum at low temperatures and small impurity scattering transforming in monotonously decreasing function at strong scattering and high temperatures. The second kind of this dependence has been also found for d-wave superconductors at intermediate and high temperatures. In contrast, impurity scattering results in decreasing of ξ2/ξc2(B/Bc2) dependence in s++ superconductors. A reasonable agreement between calculated ξh/ξc2 values and those obtained experimentally in nonstoichiometric BaFe2–xCoxAs2 (μSR) and stoichiometric LiFeAs (SANS) was found. The values of ξh/ξc2 are much less than one in case of the first compound and much more than one for the other compound. This is explained by different influence of two factors: the value of impurity scattering rate and pairing symmetry.

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This study focused on identifying various system boundaries and evaluating methods of estimating energy performance of biogas production. First, the output-input ratio method used for evaluating energy performance from the system boundaries was reviewed. Secondly, ways to assess the efficiency of biogas use and parasitic energy demand were investigated. Thirdly, an approach for comparing biogas production to other energy production methods was evaluated. Data from an existing biogas plant, located in Finland, was used for the evaluation of the methods. The results indicate that calculating and comparing the output-input ratios (Rpr1, Rpr2, Rut, Rpl and Rsy) can be used in evaluating the performance of biogas production system. In addition, the parasitic energy demand calculations (w) and the efficiency of utilizing produced biogas (η) provide detailed information on energy performance of the biogas plant. Furthermore, Rf and energy output in relation to total solid mass of feedstock (FO/TS) are useful in comparing biogas production with other energy recovery technologies. As a conclusion it is essential for the comparability of biogas plants that their energy performance would be calculated in a more consistent manner in the future.