IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

International Journal of Research in Information Technology (IJRIT) www.ijrit.com

ISSN 2001-5569

A Model for the Optimization of the Maintenance Support Organization for Offshore Wind Farms Rhittik Bhattacharyya Embedded System Technology (Dept. of ECE) SRM University Chennai, India [email protected]

A.JOSHUA JAFFERSON Asst. Professor (O.G), Department of ECE SRM University Chennai, India [email protected] Abstract— Offshore wind power refers to the construction of wind farms in bodies of water to generate electricity from wind. Offshore wind power capacity is expected to reach a total of 75 GW worldwide by 2020, with significant contributions from China and the United States. Better wind speeds are available offshore compared to on land, so offshore wind power’s contribution in terms of electricity supplied is higher. Maintenance of offshore wind power plants is known to be extensive and costly. Operation and maintenance is expected to contribute between15%–30% of the cost of energy generated by offshore wind farms. This paper provides an analytical model is proposed which enables fast computation of the performance of a maintenance support for offshore wind farms by focusing on factors like Time, Season and Environmental Conditions and Corrective and Preventive Maintenance. I. INTRODUCTION Offshore wind power refers to the construction of wind farms in bodies of water to generate electricity from wind. Unlike the typical usage of the term "offshore" in the marine industry, offshore wind power includes inshore water areas such as lakess and sheltered coastal areas, utilizing traditional fixed-bottom wind turbine technologies, as well as deep-water areas utilizing floating wind turbines. The advantage is that the wind is much stronger off the coasts, and unlike wind over the continent, offshore breezes can be strong in the afternoon, matching the time when people are using the most electricity. Offshore wind power can help to reduce energy imports, reduce air pollution and greenhouse gases (by displacing fossil-fuel power generation), meet renewable electricity standards, and create jobs and local business opportunities. Offshore wind resource characteristics span a range of spatial and temporal scales and field data on external conditions. Necessary data includes water depth, currents, seabed, migration, and wave action, all of which drive mechanical and structural loading on potential turbine configurations. Other factors include marine growth, salinity, icing, and the geotechnical characteristics of the sea or lake bed. A number of things are necessary in order to attain the necessary information on these subjects. Existing hardware for these measurements includes LIDAR, SODAR, radar, AUV, and remote satellite sensing. Because of the previous factors, one of the biggest difficulties with offshore wind farms is the ability to predict loads. Despite high capital cost and the cost of operation and maintenance, the installed capacity of offshore wind power has increased exponentially in Europe from 800 MW installed at the end of 2006 to 3.8 GW at the end of 2011 and many offshore wind farms are expected to be built in the near future, especially in the U.K., Germany, Denmark, and the Netherlands. The reasons for this trend are high wind resources, the availability of space, low visual and noise impact, better understanding of the economic risks, and high financial incentives. Operation and maintenance is expected to contribute between15%–30% of the cost of energy generated by offshore wind farms. Fault location is historically one of the most appealing topics for people working in Power Systems given that it involves several technical and scientific aspects, such as electromagnetic transient, material engineering, instrumentation and measurement, reliability, power electronic and so on. In the era of smartgrid, the demand of intelligent measurement systems

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

capable of providing quickly and with high accuracy the right location of faults in power networks is growing fast. These are especially of interest in microgrids, in data and telecom centers, in renewable energy systems, in dc zonal power systems, and in other increasingly common industrial applications that have no inherent 50/60 Hz ac nature The optimization of maintenance can be separated into interconnected areas like 1) maintenance strategies 2) maintenance scheduling in addition to maintenance support organization. This project provides an analytical model is proposed which enables fast computation of the performance of a maintenance support for offshore wind farms by focussing on factors like Time, Season and Environmental Conditions and Corrective and Preventive Maintenance. II. PROPOSED IMPLEMENTATION METHOD Embedded systems are designed to do some specific task, rather than be a general-purpose computer for multiple tasks. Some also have real-time performance constraints that must be met, for reason such as safety and usability; others may have low or no performance requirements, allowing the system hardware to be simplified to reduce costs. In this project we used PIC 16f877A microcontroller. For most applications, we will be able to find a device within the family that meets our specifications with a minimum of external devices, or an external but which will make attaching external devices easier, both in terms of wiring and programming.

BLOCK DIAGRAM:

Figure1: Block Diagram The proposed model uses a PIC microcontroller for interfacing purposes. An ultrasonic sensor is used to measure the windspeed. A current sensor is used to measure the current produced by the windmill. The potential transformer measures the

Rhittik Bhattacharyya, IJRIT

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

output voltage of the windmill. The oil level sensor is used to measure the lubricant level of the wind rotor system. All these are connected to the windmill and interfaced with the microcontroller . A wireless sensor network is interfaced to the microcontroller via a UART .All load prediction, oil level measurements and wind speed measurements are sent to the base receiver station via the WSN. The output power is delivered to the load via a driver circuit. A battery is provided to store power for backup to the delivery of loads in case the windmill doesn’t function.

III.HARDWARE DESIGN

PIC 16f877A

Fig. 2: PIC 16f877A PIC is a family of Harvard architecture microcontrollers made by Microchip Technology, derived from the PIC1640 originally developed by General Instrument’s Microelectronics Division. The name PIC initially referred to "Peripheral Interface Controller. These microcontrollers are popular with both industrial developers and hobbyists alike due to their low cost, wide availability, large user base, extensive collection of application notes, availability of low cost or free development tools, and serial programming (and re-programming with flash memory) capability, peripheral Interface Controller. PIC16F874A/877A devices are available in 40-pin and 44-pin packages. All devices in the PIC16F87XA family share common architecture with the following features • • • • •

Only 35 single-word instructions to learn All single-cycle instructions except for program branches, which are two-cycle Operating speed: DC – 20 MHz clock input DC – 200 ns instruction cycle Up to 8K x 14 words of Flash Program Memory, Up to 368 x 8 bytes of Data Memory (RAM), Up to 256 x 8 bytes of EEPROM Data Memory Pin out compatible to other 28-pin or 40/44-pin

ULTRASONIC SENSOR:

Fig2: This figure shows the hardware of PIR sensor which is used for the unauthorized entry. Ultrasonic sensors (also known as transceivers when they both send and receive) work on a principle similar to radar or sonar which evaluate attributes of a target by interpreting the echoes from radio or sound waves respectively. Ultrasonic sensors generate high frequency sound waves and evaluate the echo which is received back by the sensor. Sensors calculate the time interval between sending the signal and receiving the echo to determine the distance to an object.

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

This technology can be used for measuring:wind speed and direction (anemometer), fullness of a tank and speed through air or water. For measuring speed or direction a device uses multiple detectors and calculates the speed from the relative distances to particulates in the air or water. To measure the amount of liquid in a tank, the sensor measures the distance to the surface of the fluid. Further applications include: humidifiers, sonar, medical, ultrasonography, burglar alarms and non-destructive testing. Features : • • • • • • •

1.Supply Voltage – 5 VDC 2.Supply Current – 30 mA typ; 35 mA max 3. Range – 2 cm to 3 m (0.8 in to 3.3 yrds) 4.Input Trigger – positive TTL pulse, 2 uS min, 5 µs typ. 5. Echo Pulse – positive TTL pulse, 115 uS to 18.5 ms 6.Echo Hold-off – 750 µs from fall of Trigger pulse 7.Burst Frequency – 40 kHz for 200 µs

CURRENT SENSOR:

Fig.3: The above figure shows the hardware structure of current sensor CS60 010 A current sensor is a device that detects electrical current (AC or DC) in a wire, and generates a signal proportional to it.It can be then utilized to display the measured current in an ammeter or can be stored for further analysis in a data acquisition system or can be utilized for control purpose. The standard design uses an accurate and specific resistive termination on the secondary. By transformer action, the loading effect of this resistance is transferred to the primary and appears as a shunt resistance across the primary. The parallel combination of this shunt resistance and the impedance of the primary winding form the impedance through which the current flows. LEVEL SENSOR:

Fig.4: The figure shows the Magnetoresistance float level sensor Level sensors detect the level of substances that flow, including liquids, slurries, granular materials, and powders. Magnetoresistance float level sensors are similar to float level sensors however a permanent magnet pair is sealed inside the float arm pivot. As the float moves up the motion and location are transmitted as the angular position of the magnetic field. This detection system is highly accurate down to 0.02 Degrees of motion. The field compass location provides a physical location of the float position.

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

VOLTAGE SENSOR

Fig.5 :Basic voltage sensor A capacitor voltage transformer (CVT), or capacitance coupled voltage transformer (CCVT) is a transformer used in power systems to step down extra high voltage signals and provide a low voltage signal, for measurement or to operate a protective relay.In its most basic form the device consists of three parts: two capacitors across which the transmission line signal is split, an inductive element to tune the device to the line frequency, and a transformer to isolate and further step down the voltage for the instrumentation or protective relay.A Potential Transformer is a special type of transformer that allows meters to take readings from electrical service connections with higher voltage (potential) than the meter is normally capable of handling without at potential transformer. DRIVER:

Fig. 6 : ULN 2003 An ULN2003A is a high-voltage, high-current Darlington transistor array. It consists of seven NPN Darlington pairs that feature high-voltage outputs with common-cathode flyback diodes for switching inductive loads.It is very similar to the ULN2801A, ULN2802A, ULN2803A, ULN2804A, and ULN2805A, only differing in logic input levels (TTL, CMOS, PMOS) and number of inputs (8).The drivers can be paralleled for higher current capability, even stacking one chip on top of another, both electrically and physically has been done. ZIGBEE

Fig.7 : ZigBee CC2530 ZigBee is a specification for a suite of high level communication protocols using small, low-power digital radios based on the IEEE 802.15.4-2003 standard for wireless personal area networks (WPANs), such as wireless headphones connecting with cell phones via short-range radio.The technology defined by the ZigBee specification is intended to be simpler and less expensive than other WPANs, such as Bluetooth. ZigBee is targeted at radio-frequency (RF) applications that require a low data rate, long battery life, and secure networking. Texas Instruments CC2530 is a complete 2.4-GHz RF System-on-Chip solution supporting IEEE 802.15.4 and an extensive set of applications, such as ZigBee Pro, ZigBee RF4CE remote controls, Smart Energy, home and commercial building automation, environmental monitoring and wireless medical.

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 4, April 2014, Pg: 836- 841

IV.CONCLUSION By implementing this system of working we can achieve fast computation of the performance of a maintenance support for offshore wind. The advantages of implementing this system are Sensors implementation, Priority with computerized monitoring, fault detection and diagnosis that too at a low cost and remotely unlike the present situation in which a 24*7 support crew has to be maintained on site for monitoring the offshore windmill. Instead we can remotely monitor the readings and determine faults if there are anomalies in the measurements. Thus maintainace cost is reduced making the way clear for a greener earth and more cheap energy. Further enhancements can be done applying queuing theory, more sensor applications etc. REFERENCES 1.

J. Ribrant and L. M. Bertling, “Survey of failures in wind power systems with focus on swedish wind power plants during 1997–2005,” IEEE Trans. Energy Convers., vol. 22, no. 1, pp. 167–173, Mar. 2007.

2.

F. Spinato, P. J. Tavner,G. J.W. vanBussel, and E. Koutoulakos, “Reliability of wind turbine subassemblies,” IET Renew. Power Generat., vol. 3, no. 4, pp. 387–401, 2010.

3.

E. Echavarria, B. Hahn, G. J.W. van Bussel, and T. Tomiyama, “Reliability of wind turbine technology through time,” J. Solar Energy Eng., vol. 130, no. 3, pp. 1–7, 2008.

4.

K. Harman, R.Walker, and M.Wilkisnon, “Availability trend observed at operational wind farms,” in Proc. Eur. Wind Energy Assoc. Conf., Brussels, Belgium, Apr. 31, 2008

5.

"Wind turbines Part 3: Design requirements for offshore wind turbines" Austrian Standards Institute

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Coupling Capacitor Voltage Transformers Transients Fundamentals ,roger hedding,abb dousman, wi

7.

Voltage Measurement with A PIC Microcontroller ,Ryan Popa ,03/30/2012

8.

J. Nilsson, “IMaintenance Management of Wind Power Systems—Cost Effect Analysis of Condition Monitoring Systems,” Master’s thesis, Royal Institute of Technology, Stockholm, Sweden, 2010.

9.

J. Broehl, Servicing a Turbine, Wind Power Special Report—Supplement to Wind Power Monthly Mar. 2010.

10. L. W. M. M. Rademakers, H. Braam, T. S. Obdam, and R. P. van de Pieterman, “Operation and maintenance cost estimator (OMCE) to estimate the future O&M costs of offshore wind farms,” in Proc. Eur.Offshore Wind 2009 Conf., Stockholm, Sweden, Sep. 14–16, 2009. 11. F.Besnard, M. Patriksson, A.-B. stromberg, .Wojciechowski, K. FischerBertling, and L. Bertling, “A stochastic model for opportunistic service maintenance planning of offshore wind farms,” in Proc. IEEE Powertech Conf., Trondheim, Norway, Jun. 19–23, 2011. 12. Capacitive voltage transformers and coupling capacitors Oil-paper insulation, ARTECHE 13. Microcontroller to Sensor Interfacing Techniques, BiPOM Electronics , 2009 14. Ferran Reverter, The Art of Directly Interfacing Sensors to Microcontrollers, Journal of Low Power Electronics and Applications, 2012

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A Model for the Optimization of the Maintenance Support ... - IJRIT

measurements includes LIDAR, SODAR, radar, AUV, and remote satellite sensing. Because of the previous factors, one of the biggest difficulties with offshore wind farms is the ability to predict loads. Despite high capital cost and the cost of operation and maintenance, the installed capacity of offshore wind power has.

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