Abstract: This study investigated the climatic factors associated
with Influenza incidence in Nakhon Si Thammarat, Southern
Thailand. Climatic factors comprised of the amount of rainfall,
percent of rainy days, relative humidity, wind speed, maximum,
minimum temperatures and temperature difference. A multiple
stepwise regression technique was used to fit the statistical model.
The result showed that the temperature difference and percent of
rainy days were positively associated with Influenza incidence in
Nakhon Si Thammarat.
Abstract: This paper proposes the method combining artificial
neural network (ANN) with particle swarm optimization (PSO) to
implement the maximum power point tracking (MPPT) by controlling
the rotor speed of the wind generator. First, the measurements of wind
speed, rotor speed of wind power generator and output power of wind
power generator are applied to train artificial neural network and to
estimate the wind speed. Second, the method mentioned above is
applied to estimate and control the optimal rotor speed of the wind
turbine so as to output the maximum power. Finally, the result reveals
that the control system discussed in this paper extracts the maximum
output power of wind generator within the short duration even in the
conditions of wind speed and load impedance variation.
Abstract: Dengue fever has become a major concern for health
authorities all over the world particularly in the tropical countries.
These countries, in particular are experiencing the most worrying
outbreak of dengue fever (DF) and dengue haemorrhagic fever
(DHF). The DF and DHF epidemics, thus, have become the main
causes of hospital admissions and deaths in Malaysia. This paper,
therefore, attempts to examine the environmental factors that may
influence the recent dengue outbreak. The aim of this study is twofold,
firstly is to establish a statistical model to describe the
relationship between the number of dengue cases and a range of
explanatory variables and secondly, to identify the lag operator for
explanatory variables which affect the dengue incidence the most.
The explanatory variables involved include the level of cloud cover,
percentage of relative humidity, amount of rainfall, maximum
temperature, minimum temperature and wind speed. The Poisson and
Negative Binomial regression analyses were used in this study. The
results of the analyses on the 915 observations (daily data taken from
July 2006 to Dec 2008), reveal that the climatic factors comprising of
daily temperature and wind speed were found to significantly
influence the incidence of dengue fever after 2 and 3 weeks of their
occurrences. The effect of humidity, on the other hand, appears to be
significant only after 2 weeks.
Abstract: An experimental and simulation flight test has been carried out to evaluate the longitudinal gliding characteristics of a lifting body with blunted half-cone geometry. The novelty here is the lifting body's pitch control mechanism, which consists of a pair of leading-edge rotating cylinders. Flight simulation uses aerodynamic data from computational fluid dynamics supported by wind-tunnel test. Flight test consists of releasing an aluminum lifting body model from a moving vehicle at the appropriate wind speed while measuring the lifting body's variation of altitude against time of flight. Results show that leading-edge rotating cylinder is able to give small amounts of improvement to the longitudinal stability and pitch control to the lifting body.
Abstract: Nuclear energy sources have been widely used in the
past decades in order to power spacecraft subsystems. Nevertheless,
their use has attracted controversy because of the risk of harmful
material released into the atmosphere if an accident were to occur
during the launch phase of the mission, leading to the general
adoption of photovoltaic systems.
As compared to solar cells, wind turbines have a great advantage
on Mars, as they can continuously produce power both during dust
storms and at night-time: this paper focuses on the potential of a wind
energy conversion system (WECS) considering the atmospheric
conditions on Mars. Wind potential on Martian surface has been
estimated, as well as the average energy requirements of a Martian
probe or surface rover. Finally, the expected daily energy output of
the WECS has been computed on the basis of both the swept area of
the rotor and the equivalent wind speed at the landing site.
Abstract: This paper addresses linear quadratic regulation (LQR)
for variable speed variable pitch wind turbines. Because of the
inherent nonlinearity of wind turbine, a set of operating conditions is
identified and then a LQR controller is designed for each operating
point. The feedback controller gains are then interpolated linearly to
get control law for the entire operating region. Besides, the
aerodynamic torque and effective wind speed are estimated online to
get the gain-scheduling variable for implementing the controller. The
potential of the method is verified through simulation with the help of
MATLAB/Simulink and GH Bladed. The performance and
mechanical load when using LQR are also compared with that when
using PI controller.
Abstract: Nowadays, power systems, energy generation by wind
has been very important. Noting that the production of electrical
energy by wind turbines on site to several factors (such as wind speed
and profile site for the turbines, especially off the wind input speed,
wind rated speed and wind output speed disconnect) is dependent. On
the other hand, several different types of turbines in the market there.
Therefore, selecting a turbine that its capacity could also answer the
need for electric consumers the efficiency is high something is
important and necessary. In this context, calculating the amount of
wind power to help optimize overall network, system operation, in
determining the parameters of wind power is very important.
In this article, to help calculate the amount of wind power plant,
connected to the national network in the region Manjil wind,
selecting the best type of turbine and power delivery profile
appropriate to the network using Monte Carlo method has been.
In this paper, wind speed data from the wind site in Manjil, as minute
and during the year has been. Necessary simulations based on
Random Numbers Simulation method and repeat, using the software
MATLAB and Excel has been done.
Abstract: This paper presents a reliability-based approach to select appropriate wind turbine types for a wind farm considering site-specific wind speed patterns. An actual wind farm in the northern region of Iran with the wind speed registration of one year is studied in this paper. An analytic approach based on total probability theorem is utilized in this paper to model the probabilistic behavior of both turbines- availability and wind speed. Well-known probabilistic reliability indices such as loss of load expectation (LOLE), expected energy not supplied (EENS) and incremental peak load carrying capability (IPLCC) for wind power integration in the Roy Billinton Test System (RBTS) are examined. The most appropriate turbine type achieving the highest reliability level is chosen for the studied wind farm.
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: Data of wave height and wind speed were collected
from three existing oil fields in South China Sea – offshore
Peninsular Malaysia, Sarawak and Sabah regions. Extreme values
and other significant data were employed for analysis. The data were
recorded from 1999 until 2008. The results show that offshore
structures are susceptible to unacceptable motions initiated by wind
and waves with worst structural impacts caused by extreme wave
heights. To protect offshore structures from damage, there is a need
to quantify descriptive statistics and determine spectra envelope of
wind speed and wave height, and to ascertain the frequency content
of each spectrum for offshore structures in the South China Sea
shallow waters using measured time series. The results indicate that
the process is nonstationary; it is converted to stationary process by
first differencing the time series. For descriptive statistical analysis,
both wind speed and wave height have significant influence on the
offshore structure during the northeast monsoon with high mean wind
speed of 13.5195 knots ( = 6.3566 knots) and the high mean wave
height of 2.3597 m ( = 0.8690 m). Through observation of the
spectra, there is no clear dominant peak and the peaks fluctuate
randomly. Each wind speed spectrum and wave height spectrum has
its individual identifiable pattern. The wind speed spectrum tends to
grow gradually at the lower frequency range and increasing till it
doubles at the higher frequency range with the mean peak frequency
range of 0.4104 Hz to 0.4721 Hz, while the wave height tends to
grow drastically at the low frequency range, which then fluctuates
and decreases slightly at the high frequency range with the mean
peak frequency range of 0.2911 Hz to 0.3425 Hz.
Abstract: Recent trends in building constructions in Libya are
more toward tall (high-rise) building projects. As a consequence, a
better estimation of the lateral loading in the design process is
becoming the focal of a safe and cost effective building industry. Byin-
large, Libya is not considered a potential earthquake prone zone,
making wind is the dominant design lateral loads. Current design
practice in the country estimates wind speeds on a mere random
bases by considering certain factor of safety to the chosen wind
speed. Therefore, a need for a more accurate estimation of wind
speeds in Libya was the motivation behind this study. Records of
wind speed data were collected from 22 metrological stations in
Libya, and were statistically analysed. The analysis of more than four
decades of wind speed records suggests that the country can be
divided into four zones of distinct wind speeds. A computer “survey"
program was manipulated to draw design wind speeds contour map
for the state of Libya.
The paper presents the statistical analysis of Libya-s recorded
wind speed data and proposes design wind speed values for a 50-year
return period that covers the entire country.
Abstract: Abstract— The paper presents a preliminary study on modeling and estimation of basic wind speed ( extreme wind gusts ) for the consideration of vulnerability and design of building in Ayeyarwady Region. The establishment of appropriate design wind speeds is a critical step towards the calculation of design wind loads for structures. In this paper the extreme value analysis of this prediction work is based on the anemometer data (1970-2009) maintained by the department of meteorology and hydrology of Pathein. Statistical and probabilistic approaches are used to derive formulas for estimating 3-second gusts from recorded data (10-minute sustained mean wind speeds).
Abstract: This paper presents the study of a variable speed wind
energy conversion system based on a Doubly Fed Induction Generator
(DFIG) based on a sliding mode control applied to achieve control of
active and reactive powers exchanged between the stator of the DFIG
and the grid to ensure a Maximum Power Point Tracking (MPPT) of
a wind energy conversion system. The proposed control algorithm is
applied to a DFIG whose stator is directly connected to the grid and
the rotor is connected to the PWM converter. To extract a maximum
of power, the rotor side converter is controlled by using a stator
flux-oriented strategy. The created decoupling control between active
and reactive stator power allows keeping the power factor close to
unity. Simulation results show that the wind turbine can operate at
its optimum energy for a wide range of wind speed.
Abstract: Wind power is among the most actively developing distributed generation (DG) technology. Majority of the wind power based DG technologies employ wind turbine induction generators (WTIG) instead of synchronous generators, for the technical advantages like: reduced size, increased robustness, lower cost, and increased electromechanical damping. However, dynamic changes of wind speed make the amount of active/reactive power injected/drawn to a WTIG embedded distribution network highly variable. This paper analyzes the effect of wind speed changes on the active and reactive power penetration to the wind energy embedded distribution network. Four types of wind speed changes namely; constant, linear change, gust change and random change of wind speed are considered in the analysis. The study is carried out by three-phase, non-linear, dynamic simulation of distribution system component models. Results obtained from the investigation are presented and discussed.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: Climate change is a cumulative change in weather
patterns over a period of time. Trend analysis using non-parametric
Mann-Kendall test may help to determine the existence and
magnitude of any statistically significant trend in the climatic data.
Another index called Sen slope may be used to quantify the
magnitude of such trends. A toolbar extension to ESRI ArcGIS
named Arc Trends has been developed in this study for performing
the above mentioned tasks. To study the temporal trend of
meteorological parameters, 32 years (1971-2002) monthly
meteorological data were collected for 133 selected stations over
different agro-ecological regions of India. Both the maximum and
minimum temperatures were found to be rising. A significant
increasing trend in the relative humidity and a consistent significant
decreasing trend in the wind speed all over the country were found.
However, a general increase in rainfall was not found in recent years.
Abstract: This paper presents an evaluation of the wind potential in the area of the Lagoon of Venice (Italy). A full anemometric campaign of 2 year measurements, performed by the "Osservatorio Bioclimatologico dell'Ospedale al Mare di Venezia" has been analyzed to obtain the Weibull wind speed distribution and the main wind directions. The annual energy outputs of two candidate horizontal-axis wind turbines (“Aventa AV-7 LoWind" and “Gaia Wind 133-11kW") have been estimated on the basis of the computed Weibull wind distribution, registering a better performance of the former turbine, due to a higher ratio between rotor swept area and rated power of the electric generator, determining a lower cut-in wind speed.
Abstract: Tourism is a phenomenon respected by the human communities since a long time ago. It has been evoloving continually based on a variety of social and economic needs and with respect to increasingly development of communication and considerable increase of tourist-s number and resulted exchange income has attained much out come such as employment for the communities. or the purpose of tourism development in this zone suitable times and locations need to be specified in the zone for the tourist-s attendance. One of the most important needs of the tourists is the knowledge of climate conditions and suitable times for sightseeing. In this survey, the climate trend condition has been identified for attending the tourists in Isfahan province using the modified tourism climate index (TCI) as well as SPSS, GIS, excel, surfer softwares. This index evoluates systematically the climate conditions for tourism affairs and activities using the monthly maximum mean parameters of daily temperature, daily mean temperature, minimum relative humidity, daily mean relative humidity, precipitation (mm), total sunny hours, wind speed and dust. The results obtaind using kendal-s correlation test show that the months January, February, March, April, May, June, July, August, September, October, November and December are significant and have an increasing trend that indicates the best condition for attending the tourists. S, P, T mean , T max and dust are estimated from 1976-2005 and do kendal-s correlation test again to see which parameter has been effective. Based on the test, we also observed on the effective parameters that the rate of dust in February, March, April, May, June, July, August, October and November is decreasing and precipitation in September and January is increasing and also the radiation rate in May and August is increasing that indicate a better condition of convenience. Maximum temperature in June is also decreasing. Isfahan province has two spring and fall peaks and the best places for tourism are in the north and western areas.
Abstract: Based on a long-term vegetation index dataset of NDVI and meteorological data from 68 meteorological stations in the Qinghai-Tibet plateau and their relations with major climate factors were analyzed. The results show the following: 1) The linear trends of temperature in the Qinghai-Tibet plateau indicate that the temperature in the plateau generally increased, but it rose faster in the last 20 years. 2) The most significant NDVI increase occurred in the eastern and southern plateau. However, the western and northern plateau demonstrate a decreasing trend. 3) There is a significant positive linear correlation between NDVI and temperature and a negative correlation between NDVI and mean wind speed. However, no significant statistical relationship was found between NDVI and relative humidity, precipitation or sunshine duration.4) The changes in NDVI for the plateau are driven by temperature-precipitation, but for the desert and forest areas, the relation changes to precipitation-temperature-wind velocity and wind velocity-temperature-precipitation.
Abstract: This research were investigated, determined, and
analyzed of the climate characteristically change in the provincial
Udon Thani in the period of 60 surrounding years from 1951 to 2010
A.D. that it-s transferred to effects of climatologically data for
determining global warming. Statistically significant were not found
for the 60 years- data (R2