عنوان مقاله [English]
Wind is known as an intermittent event because of its rapid change in direction and value. Various effects of storm on civil aviation, besides of its danger to the urban, industrial and agricultural areas, make it very important to forecast wind in appreciate lead time. Direct effect of wind on many industries, specially its role in energy generation and increasing share of wind energy in the market, made it very important. High penetration of wind power in the electricity system provides many challenges to the power system operators, mainly due to the unpredictability and variability of wind power generation.
Material and methods
Different kind of observation systems including in-situ devices and remote sensing devices are useful to measure wind, and different methods are useful to detect and estimate probability of extreme events as well as forecast the wind speed. Different methods for detection and forecasting of wind have been invented and several works were done for comparing and improving them. In-situ measuring devices include, cup anemometer, ultrasonic anemometer and hotwire anemometer, while remote sensing measuring devices include, SODAR, LiDAR and radar. SODAR, LiDAR and radar operate in a similar manner except that they use different kind of pulses for transition. Generally, both the intensity and the Doppler frequency shift of the return signal are analyzed to determine wind speed, wind direction and turbulence. In spite of in-situ measuring instruments which measure the wind at a single point, remote sensing devices measure the wind in several points or a limited area. Each measuring device has its advantage and limitations witch has been listed in the paper. Wind farm deployment is moving from flat to complex terrains because of the availability of stronger winds there. The cost of site assessment through local sensing techniques is also growing due to the increasing height of meteorological masts. The maintenance required after installing the setup makes this approach even more expensive. On the other hand, remote sensing technologies are cheaper solutions, but their accuracy in complex terrains is still questionable. Turbulence also needs to be considered when measuring the wind. Turbulence is caused by (i) friction with the earth’s surface, that is flow disturbances caused by the topographical features and (ii) thermal effects that can cause air masses to move vertically as a result of variations in temperature. Turbulent flow is chaotic with a variable pattern over a short time frame but it has a relatively constant average over longer time periods. Wind turbulence is the rapid disturbances or irregularities in the wind speed, direction, and vertical component. The most common indicator of turbulence is the standard deviation (σ) of wind speed. σ normalized with the average wind speed gives the Turbulence Intensity (TI) of a site.
Results and discussion
Various methods classified according to time-scales or methodology, are available for wind forecasting. According to the time-scales, wind forecasting methods can be divided into 4 categories. (i) ultra-short-term forecasting: from few minutes to 1 hour ahead, (ii) Short-term forecasting: from 1 hour to several hours ahead, (iii) medium-term forecasting: from several hours to 1 week ahead and (iv)long-term forecasting: from 1 week to 1 year or more ahead. Each category has its own application in industry.
The rapid increase in numbers of connectable devices, the expansion of networks, the implementation of new networks, and the requirement for field workers to be completely mobile but always connected (with laptops, smart tablets, smart phones), makes even more imperative the implementation of some form of Unified Communications. Otherwise it takes too long to adapt to changes. Under this paradigm the communications medium from the central server to a remote station, and around the remote station may still be varied (fibre, cable, cellular, satellite, ADSL, Radio, Microwave, WiFi, Ethernet etc.). However the interconnection method between the different medium link modules is all the same - Ethernet, with Power over Ethernet (PoE) where practicable. New frameworks in observation systems like IOT (Internet Of Things), make a revolution in measuring methods along with data transfer. In IOT, all of the data sources (sensors), end user devices (displays, databases), and even a data source and sink (an actuator, smart phone) are connected to the Internet and have two ways communication.
This paper review the wind measuring devices along with the new frameworks of measuring methods like IOT and then presents a comparison between different wind forecasting methods. Spatial correlation method has been depicted by use of measured data of two ultrasonic wind sensors of IKIA (Imam Khomeini International Airport) in March 31st 2015. Results show strong dependencies of the observed data of two sites, and wind speed and direction in second site, follow the first site with a delay. Comparison between wind measurement by radiosonde and VVP and CAPPI products of S-band weather radar in Ahwaz shows good consistency at higher at elevation.