Implementation of Wireless Network based Architecture on Wind Turbine Technology

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Implementation of Wireless Network based Architecture on Wind Turbine Technology

Aman Raj

  1. Tech, Department of Electronics & Communication Engineering

    National Institute of Technology, Jamshedpur

    Mr. Dilip Kumar

    Associate Professor, Department of Electronics & Communication Engineering

    National Institute of Technology, Jamshedpur

    Anand Kumar Sharma

    M. Tech, Department of Electronics & Communication Engineering

    National Institute of Technology, Jamshedpur

    Abstract There is growing interest in renewable energy around the world because of this energy is free for pollution and healthy for human being. All other power generation plant release harmful gases like carbon monoxide, sulfur dioxide, due to that reason of acid rain except wind energy. Development in the harvesting energy industry for the new generation of wind turbine with high efficiency and low maintains cost communication network architecture is very much important because wind turbine blind machines. Communication system are crucial technology which capable the accommodation of distribute renewable energy generation and play very important role in monitoring, protecting and processing Analysis of varies paper and then purposed a communication network architecture based on Zigbee. So, that the absence of unfiled monitoring and control solution acceding to the needs. The basic thing is that purposed for collecting sensing data from wind turbine parts, and connecting to wireless farm area network (WFANs) IES 61400-25 uses. One of big demerit of wireless sensor network is power so, wind turbine resolve and WSN resolve safety wind turbine of work Sampling frequency, data bit rate and guard time calculated. The sensor data frame include logical node ID (LNID), sensor type (ST) and sensor node ID (SNID). Paper present systematic representation that illustrate traffic along with wind turbine and control center. Bandwidth increases then data bit rate also incises with different wireless technology view end to end delay, bandwidth and amount of data rate. We present a model so that traffic evaluate in form of bandwidth and delay. The simulation result show traffic received delay an end – to – end delay. This work may contribute wireless communication building in harvesting energy. In future analysis of communication it may be possible in solar harvesting with optical fiber sensor network mixed with wireless sensor network.

    Keywords-LNID-Logical node, SNID-Sensor node ,WFAN- Wind farm area network, WSN-Wireless sensor network, ETE- End-to-End.

    1. INTRODUCTION

      Energy harvesting ( also known as power harvesting or energy scavenging or ambient power) is the process by which energy is acquire from external sources (e.g., solar power, thermal energy, wind energy, salinity gradients, and kinetic energy, also known as ambient energy), captured, and stored for small, wireless autonomous devices, like those used in apparel electronics and wireless sensor networks[1].Wind power is transformation of wind energy into a useful form of

      energy, such as using wind turbines to make electrical energy. Wireless sensor network (WSN) provide a powerful combination for the work in safety manner.The various and major environmental benefits of wind energy are the primary reason for many proponents and green energy purchasers to support it. In comparison with fossil fuels, wind energy emits no dangerous gasses like as sulphur monoxide, nitric oxides, particulates, carbon dioxide, or mercury. Irrespective of the form of communication process being considered, there are three elements in every communication system, namely, transmitter, channel, and receiver. The transmitter located at one point and receiver located at another point separated from transmitter, and the channel is the physical medium that connects them. The purpose of the transmitter is to convert the massage signal produced by the source of information into a form suitable for transmission over the channel. Everything will be connected in the future; not only will our phones and compute have Internet connection, but so will our light door, bulb, and other heating systems[4][5]. This is known as the Internet of Things. Home automation, health care, monitoring, transportation, smart environments, and many other sectors are also uses the applications envisioned for the Internet of Things. In analysis of communication resources on harvesting energy have two primary resources are employed first one transmitted power and second one transmitted signal. The receiver signal has task of operating receiving physical sensing data signal so, recognizable form of the original message signal. Wind energy made its debut in the wholesale electricity market in the early 1980s. In addition to federal tax credits and the federal PURPA, California Governor Jerry Brown has suggested incentives for contemporary wind power generation. The turbines were small and low -powered at first (about 50 kilowatts), but they have since grown into a successful and diverse enterprise [13]. For ages, the power of the wind has been harnessed to benefit civilization and trade. Mechanical wind turbines helped to open up the Greater Plains to human settlement and agricultural growth in the eighteen century by pumping water across the country. There isn't any industry that has as much potential for the future as renewable energy because wind energy anywhere. Wind energy is one of the most important economic sectors in this region, with growth rates ranging

      from 30% to 40%.Wireless sensor network play meager roll for sensing the harvesting data in a perfect manner .When the spectrum of message signal extend down to zero or low frequency ,we define the bandwidth of the signal as that upper frequency. The majority of system like as supervisory control and data acquisition (SCADA) use exclusivity protocols that has partial capacity and competences, making them unsuitable for future communication requirements. The fundamental aspect of providing successful monitoring, operation, in renewable source during converting electricity time and protection for both WPF generators and power systems is a dependable communication infrastructure.[11]

    2. METHODOLOGY

      The Power systems is a dependable communication infrastructure We consider Issues for connect to the control centre. Mainly high cost, as the WSN is too expensive and independent position of Low reliability, as a failure in a wind turbine so, that WSN can prevent the remaining turbines from witches and communication links add to the WSN's costs. Actually, Difficulty in ensuring real-time monitoring and control as all Wi-Fi devices share the same physical link. Environmental concerns: Wind turbines are subjected for the harsh environmental conditions such as high emission levels, salt, humidity, and temperature swings. Devices running in an offshore as well on shore setting must be designed specifically to avoid corrosion and high humidity. Redundancy is a term used to describe a situation in which the WPF communication network architecture must always operate correctly in the event of a single point of failure. Switches and routers, as well as other essential networking equipment, must be duplicated. Network of self-adoptable. The communication network for a wind power farm (WPF) must be extremely resistant to failings and have a quick recovery time. For the creation of protocols and algorithms to help environmental monitoring, data controlling, and energy harvesting presents new opportunities as well as challenges. As an alternative of focusing solely on reducing node energy consumption t extend network lifetime, as is the case in conventional WSNs, it is critical in EH-WSNs to understand the impact of performance metrics such as energy-efficiency, scalability, fireman and latency in the presence of energy flow into the network. Similarly, rather than simply minimizing overall energy consumption, physical, MAC, and routing protocols must be redesigned to maximize the rate at which energy is consumed less. Despite the fact that the cost of wind power has dropped significantly in recent decades, wind projects must be able to compete economically with the least expensive source of energy, and some place where might not be windy enough to be cost effective. The radio channel use for communication in adhoc wireless network in nature and is shared by all nodes when its direct transmission range. Data transmission by a nodes received by all nodes within its direct transmission range. This poor transmission can be minimized the perfectness due to that life time of WSN node effected. The operating environment where WSN used may not always be secure. Nodes of WSN are usually compact in nature. They could get damaged easily and are also vulnerable to theft. Main problem of wireless sensor network is power, the battery life time of wireless is no longer due to this reasons sensing data affected.

      System Model

      1. The Smart-WPFs communication network architecture

        Fig:-1 Communication network architecture of Smart- WPFS

        Turbine area network:-A lot of evaluation using SNs instruments is mounted within the wind turbine in order to track its activity. The WTC is shown in Figure -7 as the transitional stage among the sensor observing device and the network of optical communication unit interface and wireless admittance point (AP), and it is placed on the wind turbine side. Hop-by-hop, straight wired, or straight wireless wireless connections between the control centers additionally to the wind turbine are all options

        Farm area network: – In the FAN, there are two forms of network infrastructure: wired and wireless. The optical fiber is rooted in the cable of eclectic power in a wired architecture, which be planned, based on the electricity generation power topology. Electric configuration has no impact on the wireless infrastructure.

        Control area network:-Control area network is nothing but it is controls the sending and receiving data which have sensing by sensor node.

        AM stands for analogue measurements, SI stands for status information, PCI – security and control information, ONU stands for optical network device, and OLT stands meant for optical line terminal.

        There are nine sensors monitoring as follows WROT – Speed, temperature, position, pressure WTRM – Temperature, pressure, vibration WGEN voltage, current, power

        WCNV frequency, torque, voltage, current WTRF – voltage, current, temperature

        WNAC – wind speed, position, orientation, wind direction.

        WYAW – speed, position, temperature. WTOW – Humanity status

        WMET Wind speed, wind direction. – AM

        – SI

        -PCI

        -AM + -SI+ -PCI =

        Where, = Total Arrival rate,

        -AM = Measurements of Arrival analogue – SI = Arrival status information

        -PCI = protection and control information

      2. Zigbee Based Turbine Aria Network

      Zigbee is nothing but it is an IEEE 802.15.4-based protocol and more protected. Because of low power consumption and cost also low very widely use in everywhere. Like as medical, home Purpose. The designed model of this network plan is chipper and perfectly fit in any place. It create area network that name is pan and its very portable, suited for small-scale projects that require wireless communication, slightly higher, data collecting, and other limited uses. Work of this network in radio frequency advantage to take low power and work very long time with low data rate. In bottom figure show group of zigbee network are divided in separate personal area network. Individual sensor has particular connection and addressing space 64 bit. Coordinator, router and end device these are three types of

      Fig-2 ZigBee Based wireless network for a wind farm

      Total logical nodes of wind turbine have 9 (WROT, WCNV; WTRM, WGEN; WTRF, WNAC, and WYAW)

      WTLN = {WROT, WTRM, WNAC, WYAW, WGEN, WCNV; WTRF, WTOW, WMET} — (1)

      {I, V, RotPos, RotSpd, Hum, HubTemp}— (2) Where, I = Current

      V = Voltage

      Rot Pos = Rotor Position Rot Spd = Rotor speed

      Hub Temp= hub temperature

      = Type of sensor

      Actually each and every node has identification number and physical location inside wind turbine, which have given in question —– (3)

      = , , }—–(3)

      Router and end device these are three types of Amount of data calculated from each sensor by

      multiply sampling rate frequency Size of sample and number of channel Which is give in equation (4)

      = — (4)

      Traffic model

      AM+ SI + P CI = —————— (5)

      Where, = Total Arrival rate,

      AM = Arrival analogue measurements

      S I = Arrival status information

      PCI = protection and control information Bandwidth (max)

      = ( _ ) — (6)

      2 N

      Here, = Line rate = cycle time

      = Guard time

      Locatio n

      Types of sensor

      sampling rate

      data rate

      96m

      Anemometer

      4 Hz

      8 bytes/s

      95 m

      Wind Vane

      4 Hz

      8 bytes/s

      94 m

      Temperature

      1.5Hz

      3 bytes/s

      95 m

      Humidity

      1.5 Hz.

      3 bytes/s

      93 m

      Air Pressure

      100 Hz

      200 bytes/s

      86 m

      Anemometer

      3 Hz

      6 bytes/s

      85 m

      Wind Vane

      4 Hz

      8 bytes/s

      87 m

      Humidity

      1 Hz

      2 bytes/s

      51 m

      Anemometer

      3 Hz

      6 bytes/s

      52 m

      Wind Vane

      3 Hz

      6 bytes/s

      11m

      Anemometer

      3 Hz

      6 bytes/s

      11 m

      Humidity

      1 Hz

      2 bytes/s

      11 m

      Air Pressure

      100 Hz

      200 bytes/s

      10 m

      Rain sensor

      4 HZ

      8bytes/s

      Locatio n

      Types of sensor

      sampling rate

      data rate

      96m

      Anemometer

      4 Hz

      8 bytes/s

      95 m

      Wind Vane

      4 Hz

      8 bytes/s

      94 m

      Temperature

      1.5Hz

      3 bytes/s

      95 m

      Humidity

      1.5 Hz.

      3 bytes/s

      93 m

      Air Pressure

      100 Hz

      200 bytes/s

      86 m

      Anemometer

      3 Hz

      6 bytes/s

      85 m

      Wind Vane

      4 Hz

      8 bytes/s

      87 m

      Humidity

      1 Hz

      2 bytes/s

      51 m

      Anemometer

      3 Hz

      6 bytes/s

      52 m

      Wind Vane

      3 Hz

      6 bytes/s

      11m

      Anemometer

      3 Hz

      6 bytes/

      11 m

      Humidity

      1 Hz

      2 bytes/s

      11 m

      Air Pressure

      100 Hz

      200 bytes/s

      10 m

      Rain sensor

      4 HZ

      8bytes/s

      Table:-1 Types of sensor which sense physical parameter

      Figure:-3 Linear arrange wind turbine

      Point to point delay (Latency) between nearest turbine: – When distance between two turbines is less than 1km then point to point delay represent processing delay and transmission delay

      = Constant + Data packet size Channel transmission rate

      (7)

      Here, = Latency between turbines

      Complete end to end delay (E.T.E) for the N turbine connection

      = …. (8)

    3. RESULT

Fig: – 4 Exploitation of Bandwidth

Fig: – 5 Delay of average queuing

Actually fig-3 show graph between bandwidth utilization vs. generation traffic rate and in this when link under 100 mbps then utilization of bandwidth is 60% and it become 96% when arrival rat of 886 bytes/time slot. Utilization of Bandwidth nearly same when small change of 11% .In figure- 4 show delay of average vs. traffic generation in this absorb that when load of traffic is high then average delay is

13.89 ms for the 100 mbps and for the 1Gbps link the average delay queue is 0.074.

Fig:- 6 Traffic receive PAN 1 by Zigbee application

Fig:- 7 Traffic receive all PAN by Zigbee application

Above result show the simulation result of traffics received for the wind turbine internal network in figure

(5) When simulation time is zero mille second personal area networks not received any traffics data. After some delay time PAN-1 received Data traffics for the wind turbine. In a similar way show in figure (6) pan1; pan; pan3, pan4; pan5; pan6; pan7, pan 8 ,pan9 are received physical data in some delay time and then after continuously updated in a popper manner. When voltage and current sensor including total number sensor are 84sensor node and the total traffic collected by wind turbines is in bps.

Fig:- 8 PAN-1 End to end delay by Zigbee

Fig:- 9 ALL PAN End to end delay by Zigbee application

In figure (6) end-to-end delay (ETE) for a ZigBee- based wind turbine architecture with a single coordinator.. Similarly in figure (7) show end – to -end delay ZigBee construction with multiple controller. For every personal area network end to end delay time is varies like shown in table 3.

Table: – 3 ETE delay result

Personal area network nodes

End to end delay time (ms)

PAN1 – WROT PAN2 WTRM PAN 3 WGEN PAN 4 WCNV PAN 5 WNAC PAN 6 WYAC PAN 7 WTOW PAN 8 WTRE

PAN 9 WMET

3.46

9.90

2.13

3.96

2.30

3.01

2.06

2.04

3.03

Due to large amount of sensing data highest delay value is

    1. for PAN 2 logic node WTRM compare to other logical node. Above all simulating result simulated with NS2 software.

      IV CONCLUSION

      In wind harvesting communication infrastructure will take part in a effective role for real time large-scale WPF monitoring and control. ZigBee based model were capable to support wind turbine harvesting internal network and find the delay time for each logical node which is belong to those personal area network. Actually based on ZigBee protocol infrastructure more secures compare to other also power consumption is less. In future solar energy harvesting also

      may develop communication infrastructure so, that work in a safe manner with proper physical data. Optical fiber sensor network infrastructure may be developing in future therefore more performance real communication channel with more secure.

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