# Wind profile power law relationship counseling

The following equation illustrates how to use the power law method where Vo is the wind speed at the original height, V is the wind speed at the new height, Ho. Equations are presented for calculating power law exponents from wind speed and surface roughness the exponent (_ with wind speed. These functions are the constant law, a step function (Fales, relationship. _ich will be discussed. On rated speed wind turbine can give constant rated power output and cut-off speed beyond The wind profile power law relationship can be expressed as.

More precisely, it is possible to define a reliable model for a particular complex zone. The originality of the considered method is to adapt the theoretical Weibull predictable model with the real experimental data production based only on the wind profile of the installation area.

The following Section 2 describes the GREEN platform and micro wind turbine as well as wind power parameters and data location. In this section, roughness coefficient is determined proofing that the experimental site correspond to a turbine urban sitting.

Section 3 gives the wind real measurements of the considered location. The wind power output for the urban sitting is presented in the Section 4 which briefly describes the considered Weibull Model estimation and its application for the considered study case where the measurement power output performance during five years are detailed. The modeling wind speed and power output methodology for the case study is presented in the Section 5, where experimental data have been compared with simulation results to validate a micro wind turbine output power prediction model and proving the reliability micro wind power estimation in a specific urban sitting.

Section 6 gives a discussion to justify the considered approach achieving the goal attempt. Finally, Section 7 draws appropriate conclusions. Micro Wind Turbine Power Parameters and Location Wind observation location For our study, the experimental data are provided from the GREEN platform where several renewable energy technologies are implemented for modeling, managing and optimization of energy consumption. All technologies are monitored, including real weather conditions data are recorded and processed for prediction analysis Figure 1.

Installing a domestic micro wind turbine in France is usually subject to planning permission and total height must not exceed 12 m. The blades are constructed from two halves of compression molded fiberglass. The curve of the blade helps to more efficiently capture the energy in the wind and to reduce the sound of the blades as they move through the air.

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The turbine is a downwind design where the blades of the turbine are downstream from the nacelle, which is quieter and inherently better at finding the wind direction than upwind designs. The associated 3 blades Wind power Skystream in an urban area is represented in the Figure 2.

The inverter constantly monitors the turbine and the electrical connection to ensure that the electric energy generated by the turbine is synchronized with the frequency and voltage of the building's electrical system.

Table 1 indicates the Skystrean technical specifications. The inverter actually draws about Watts to operate the monitoring system. Consequently, the turbine will not generate electricity when the electrical grid to the building is down.

Wind speed is measured by a 3-cups rotor anemometer at the same height as the wind power. The anemometer is part of a meteorological weather station and wireless computer interface allows direct communication with the anemometer. It displays the current weather station data in a real-time report on the computer. Figure 3A presents the block diagram of the considered micro-wind turbine system while the Figure 3B gives a snapshot of the power output monitoring.

Thus, a wireless wind monitors allows to save large quantities of data for download 2 Megabytes of internal memory and use a ZigBee wireless link to computer for data acquisition. Indeed, the wind turbine has a built in 2. More precisely, the wireless wind monitor measures wind speed, direction data every minute and stores wind statistics once per minute. Figure 3B shows the Skyview software track the generation of the turbine displaying the data wind turbine in a defined sample time [20].

Thus, from data acquisition we can calculate histogram data. The investigation site location is given in the Table 2. Figure 4 gives the climate of localization platform. More precisely, Figure 4A provides a map specifying isobaric and wind curves, temperature and nebulosity. Figure 4B gives the wind direction in percentage of the urban localization of the considered micro-wind turbine which mainly directed to south-west. Figure 4C details the real measured wind direction of the used micro-wind turbine for our experimental which is in concordance to local wind forecast where the maximal wind field is at the direction East and South-East with 5.

The wind turbine converts wind power into mechanical power. The mechanical power generated by the wind turbine at the shaft is given by the Equation 1 [ 21 ]. Figure 5 shows the measured power curve for the Skystream of the experimental GREEN platform site for an experimental day. It can be noted that the cut in speed is below the value indicated in the technical specifications as mentioned in the Table 1.

From the Equation 1, it can be concluded that each parameter has an effect on the output power. CP is the wind-turbine power coefficient. The theoretical maximum power efficiency of any design of wind turbine is 0. This is also called the Betz Limit. Wind turbines cannot operate at this maximum limit.

The CP value is unique to each turbine type and is a function of wind speed applying to operating turbine. Roughness coefficient The roughness coefficient depends on the variability of wind speed at the site due the height above the ground and the rough- ness of the terrain which is a function of the wind direction.

Several researchers have investigated wind speed profiles at different turbine heights and various expressions have been established to determine wind profiles while estimating the increase in wind speed with height [ 22 ]. In this study, we assumed the change in speed is less pronounced and we simply used the power law exponent relation [ 9 ] which is given by the following Equation 2. This paper presents the estimation of potential for wind energy generation maps based on fixed wind turbine capacity.

Although wind energy has developed substantially in recent years, we have only wind speed and wind potential density maps. Our attempt here is to generate wind energy generation potential maps. The model consists of three main components namely the weather, the turbines and energy conversion parameters.

The weather data are provided from the meteorological database, namely Meteonorm. The simulated output is compared with actual wind generation of wind farms. After comparing our model results with the existing wind energy generation data, we have extended to compute the wind energy generation for all locations in India.

For simulation, locations are identified considering 0. The energy generation simulated data are compiled and developed into maps that are useful to all wind energy developers. The data generated and presented in the form of maps are for all the 30 states of India.

Introduction The exponential increase in utilization of electrical energy and the constant decrease in conventional sources of energy have led to huge gap between demand and supply of electrical energy. This has led the people to switch over to renewable sources of energy such as solar, wind, biomass, geothermal, etc.

According to International Energy Agency, India and China are likely to consume more than 28 percent of the world total energy by Renewable energy sources must contribute to a significant amount to protect our environment as they are least pollutants [1]. This energy consumption is divided as 8.

The Government of India has set a target for total renewable capacity as GW by Among the various renewable sources of energy, wind is one of the most important sources and has widely gained attention in recent years. Although people harnessed energy from wind since ancient times, it was in different forms. Wind turbines were previously used for pumping water, grinding grains, etc. Wind is considered as a promising alternative for power generation because of its environmental and economic benefits such as reduced greenhouse gas emission, reduced fuel cost and provides clean and cost effective energy [1].

Additionally, wind energy is an optimum choice due to relatively short installation time, easy operation and maintenance with reduced natural habitat disturbance compared to conventional energy source. The factors that influence the energy produced by wind energy generators WTG over a particular location include: The total energy generated by WTG over a period can be calculated by summation of energies corresponding to all operational wind speed [5].

Our study presents an approach to develop wind energy generation map based on a typical wind turbine size and also presents a method of wind resource assessment in India. The selection of a particular wind turbine size is chosen in our study is based on Table 1. Cumulative capacity of different states [6].

### Windenergie-Daten der Schweiz

Based on this criterion, 0. Meteonorm is a meteorological database that gives access to meteorological data for every location in the world that can be used in a variety of applications [7]. It contains worldwide weather data that can be retrieved in more than 35 formats. It is used to simulate the behavior of transient systems [8]. Surfer is a powerful contouring, gridding and three dimensional surface mapping software that mainly runs under Microsoft Windows [9].

Materials and Methods The methodology used in this study is to evaluate the wind energy potential conducted by a series of steps. First, the wind data is collected from a weather database and then a reference turbine model is selected followed by development of wind power conversion in TRNSYS software. Collection of Wind Speed Data As discussed before and above the wind speed data for our study are taken from a meteorological database-Meteonorm.

It gives weather information at a universally accepted reference data collection from a height of 10 meters. The database provides an average value collected over a period of 10 years. For assessment, a wind turbine from Enercon model of E of kW is chosen.

### Wind Energy Generation and Assessment of Resources in India

This turbine size is selected because of the following reasons: More details on the technical parameters of the selected wind turbine are shown in the Table 2. Enercon Product Brochure The power curve is a graph showing wind speed versus power output of the chosen turbine as shown in Figure 1. There are three main points on this curve: On rated speed wind turbine can give constant rated power output and cut-off speed beyond which the turbine is not allowed to deliver power and stop rotating wind turbine to protect against storm.

Figure 2 shows the image of a wind farm in Gujarat. It is the first wind farm in India. It is located near the west coast 4 km from Mandvi.

The narrow strip is of 1. It was established in with a total capacity of 1. Technical specifications of enercon E Power curve of 0. Google Earth image of wind farm at Mandvi, Gujarat https: Wind Calculation Wind is not constant but varies with time. The variation of wind speed with height is called wind shear. It necessitates the need to convert the recorded wind speed to the height of the turbine used.

This conversion is achieved using the standard wind profile power law. This power law is widely used for wind resource assessment where wind speed for various heights is retrieved from the standard recorded wind data. The exponent is an empirically derived coefficient that varies depending upon the stability of the atmosphere.

Thus, this value of coefficient is chosen for our study [11]. As the wind speed varies with time and place, power from the wind at a particular location also varies. The theoretical power from wind is calculated using the following equation [12].

The swept area of the rotor is represented by A in sq.