Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania

2017 ◽  
Vol 113 ◽  
pp. 190-201 ◽  
Author(s):  
Vladislovas Katinas ◽  
Mantas Marčiukaitis ◽  
Giedrius Gecevičius ◽  
Antanas Markevičius
Keyword(s):  
Power Generation ◽  
Statistical Analysis ◽  
Wind Characteristics

scholarly journals The Construction of a Mock-Up Test Building and a Statistical Analysis of the Data Acquired to Evaluate the Power Generation Performance of Photovoltaic Modules

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1546
Author(s):  
Seung-Joon Lee ◽  
Kyu-Jin Kim ◽  
Da-Sol Kim ◽  
Eui-Hwan Ryu ◽  
Jae Lee
Keyword(s):  
Power Generation ◽  
Statistical Analysis ◽  
Architectural Design ◽  
Statistical Correlation ◽  
Design Element ◽  
Design Elements ◽  
State College ◽  
Contour Plots ◽  
One Year ◽  
Power Generation Performance

Traditionally, studies on the power generation performance analysis of the photovoltaic (PV) modules used in building-integrated PV (BIPV) systems have been based on computer simulations and actual experiments with constraints, resulting in the results being inaccurate and limited. This paper proposes a two-step analysis method that results in a more versatile and reliable means of analysis. The steps are: (1) construction of a mock-up test building in the form of BIPV systems and the collection of a massive amount of operational data for one year; and (2) a statistical analysis of the acquired data using Minitab software (Version: 17, Manufacturer: Minitab Inc., State College, PA, USA) to examine the power generation performance. The constructed BIPV mock-up applies design elements such as material types (c-Si and a-Si) and various directions and angles for different module installations. Prior to the analysis, the reliability of the large database (DB) constructed from the acquired data is statistically validated. Then, from the statistical correlation analysis of the DB, several plots that visualize the performance characteristics governed by design elements, including contour plots that show the region of higher performance, are generated. Further, a regression model equation for power generation performance is derived and verified. The results of this study will be useful in determining whether a BIPV system should be adopted in a building’s architectural design and, subsequently, selecting design element values for an actual BIPV system.

Blade Faults Diagnosis in Power Generation Gas Turbines

2017 ◽  
Author(s):  
Meng Hee Lim ◽  
Salman Leong ◽  
Kar Hoou Hui
Keyword(s):  
Power Generation ◽  
Statistical Analysis ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Vibration Signal ◽  
Health Condition ◽  
Baseline Data ◽  
Compressor Blades ◽  
Industrial Gas Turbines

This paper presents a case study in managing the dilemma of whether to resume or stop the operation of a power generation gas turbine with suspected blade faults. Vibration analysis is undertaken on the vibration signal of the gas turbine, to obtain an insight into the health condition of the blades before any decision is made on the operation of the machine. Statistical analysis is applied to study the characteristics of the highly unstable blade pass frequency (BPF) of the gas turbine and to establish the baseline data used for blade fault assessment and diagnosis. Based on the excessive increase observed on specific BPF amplitudes in comparison to the statistical baseline data, rubbing at the compressor blade is suspected. An immediate overhaul is therefore warranted, and the results from the inspection of the machine confirm the occurrence of severe rubbing at the compressor blades and labyrinth glands of the gas turbine. In conclusion, statistical analysis of BPF amplitude is found to be a viable tool for blade fault diagnosis in industrial gas turbines.

scholarly journals CO2 emissions of nuclear power and renewable energies: a statistical analysis of European and global data

2021 ◽  
Vol 136 (5) ◽  
Author(s):  
Friedrich Wagner
Keyword(s):  
Power Generation ◽  
Statistical Analysis ◽  
Co2 Emissions ◽  
Electricity Generation ◽  
Nuclear Power ◽  
Statistical Techniques ◽  
Coal Gas ◽  
Renewable Power ◽  
Renewable Power Generation ◽  
Global Data

AbstractIn this paper, we investigate the CO2 emissions caused by nuclear and renewable power generation. The knowledge of the share of coal, gas and oil in electricity generation permits the exact calculation of the related CO2 emissions. In addition, there is a second approach especially within the economic sciences, which applies statistical techniques for the study of the energy-related emissions. The background for these studies is the provision of general political advice and the expectation that political, cultural, or infrastructural considerations guide nations in the preference and choice of specific technologies. In this paper, we are applying both approaches and come to the certain conclusion, that nuclear power is as effective as renewable power in order to reduce the CO2 emissions. Our results are in complete contradiction to a recent publication (Sovacool et al. in Nat Energy 5:928–935, 2020. 10.1038/s41560-020-00696-3). The authors of this paper conclude that nuclear power does not reduce the CO2 emissions, but renewable power efficiently does. In addition, they argue that these two technologies crowd out each other. The possible reason for their claims may result from a specific conditioning of the data. In contrast, our analysis clearly confirms the adequacy of both nuclear and renewable power generation.

Energy Efficiency Evaluation of Wind Energy Based on Energy Reports

2014 ◽  
Vol 1008-1009 ◽  
pp. 188-191 ◽  
Author(s):  
Ana Maria Smaranda Florescu ◽  
Georgeta Bandoc ◽  
Mircea Degeratu
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Efficiency Evaluation ◽  
Monthly Data ◽  
Different Types ◽  
Wind Characteristics ◽  
Global Estimates ◽  
Preliminary Study ◽  
Energy Efficiency Evaluation

Harnessing wind energy for power generation involves first achieving a preliminary study to understand the wind characteristics for the chosen location. In this way, the results are useful for understanding performace of an project that is connected with wind energy. The purpose of this article is to determine global estimates and different energy reports (ER). This is necessary because we do not always have a lots of meteorological datas. For the determination of these reports (ER) it used different kinds of energies calculated for a period of six years, hourly, daily and monthly data. Therfor, it was calculated the energy monthly, seasonally and annually report between monthly energy calculated with daily wind date and monthly energy calculated with instantaneous wind date (R m, Z/I); energy monthly, seasonally and annually report between monthly energy calculated with monthly wind date and monthly energy calculated with instantaneous wind date (R m, L/I); energy monthly, seasonally and annually report between monthly energy calculated with instantaneous wind date and monthly energy Betz (R m, I/B). All these reports were determined for a certain family of wind turbines used for a functional home using wind and solar energy. From the obtained results that are quite significant differences between seasonal and annual energy reports values determined with different types of energy.

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