The field of power systems operation and control including renewable energy (RE) along with power, quality is considered as one of the major technical challenges among the researchers and practicing engineers. Several types of renewable energy resources are available on earth such as solar, wind, Geo-thermal, hydro, etc. The foremost resources of renewable energy are - Sunlight and Wind. The wind energy is always a center of attraction for power engineers. In the wind energy system, the pitch angle of turbine blades is playing an important role in controlling the power output of the system. The pitch angle imposes two types of control on the wind turbine system: aerodynamic torque and the rotational velocity of the turbine system. These parameters directly affect the performance of the wind power generation system in terms of the profile of power, voltage, and current. Conventionally, PID control-based system modeling has been used to evaluate the optimal pitch angle for a given wind pattern. However, PID based Pitch Angle Identification require regular tuning against variation in wind velocity and significant large time for tuning. Thus, Artificial Intelligence could provide a better solution in comparison to PID Based tuning strategy. The present work shows the evaluation of the optimal pitch angle of the wind turbines for variable wind velocity using the Fuzzy Logic Control Strategy. The test results are obtained by MATLAB Simulink modeling of the wind power generation system. The simulation shows that fuzzy logic control will provide an optimal pitch angle to obtain more efficient solutions. The existing fuzzy control-based simulation model solutions can be utilized as a testbed for evaluating the optimal pitch Angle of any geographical region. In the present work, the optimal pitch angle of Various Geographical regions of India.
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Pitch Angle Control of Wind Turbine using Fuzzy Logic Control
1. PITCH ANGLE CONTROL OF WIND TURBINE USING
FUZZY LOGIC CONTROL
A
Proposed Project Power Point Presentation
Submitted in partial fulfilment of the requirements for the degree of
BACHELOR OFTECHNOLOGY
in
ELECTRICAL & ELECTRONICS ENGINEERING
ELECTRICAL & ELECTRONICS ENGINEERING DEPARTMENT
KIET GROUP OF INSTITUTIONS, GHAZIABAD
Dr. A. P. J. ABDUL KALAM TECHNICAL UNIVERSITY, UTTAR PRADESH,
LUCKNOW
SUBMITTED BY:
GROUP NO.: P-01
1. Arpit Bhushan Sharma
2. Alok Shukla
CO-GUIDE:
Dr. Neeraj Gupta
(Professor cum Head of
Department)
Department of Electrical &
Electronics Engineering
GUIDE:
Dr. Brijesh Singh (Associate Professor)
Department of Electrical & Electronics
Engineering
KIET GROUP OF INSTITUTIONS, GHAZIABAD
13 August 2020
2. CONTENTS
• Introduction/ Basics Details
• Literature Review
• Objective Function
• Methodology
• Hardware/Software Setup
• Details and specification of equipment’s used in calibration, measurement and
data collection
• Testing, Data Collection & Analysis
• Findings, Results and Conclusions
• Conclusions and Future Scope
• Publications
• References
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3. INTRODUCTION
1. Several types of renewable energy resources are available on earth such as
solar, wind, Geo-thermal, hydro etc.
2. The foremost resources of renewable energy are - Sunlight and Wind.
3. In wind energy system, the pitch angle of turbine blades is playing an
important role for controlling the power output of the system.
4. The pitch angle imposes two types of control on wind turbine system:
aerodynamic torque and the rotational velocity of turbine system.
5. Conventionally, PID control-based system modelling has been used to
evaluate the optimal pitch angle for a given wind pattern.
6. Artificial Intelligence could provide a better solution in comparison to PID
Based tuning strategy.
7. The fuzzy logic control will provides an optimal pitch angle to obtain more
efficient solutions.
8. The existing fuzzy control-based simulation model solutions can be utilized
as a testbed for evaluating the optimal pitch Angle of any geographical
region.
13 August 2020 3
5. Aim :
Due to Scarcity of Electricity in Country and Government is still funding for smart cities,
however, there are still some villages with no electricity. Wind Energy is a constant and
free source of Energy. Using Wind Turbine to give constant supply of Electricity to these
rural areas and for future use, one of the major issue is by this project.
Objectives :
• To study the Wind Pattern of the Area
• To study the variation of Pitch Angle with Wind Speed
• To identify the Aerodynamic Torque of Wind and its Blades
• To study the effect of Pitch Angle on Wind Power.
• To Study Fuzzy Logic Controller
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Aim and Objectives of the Project
6. RESEARCH PROSPECTUS
1. The wind coming from the wind conversion process is not with perfect efficiency, as energy
extracted from wind is proportional to cube of wind speed.
2. The Pitch Angle is not adjustable according to variable wind speed, so it behaves as a non - linear
system, Therefore, in modern wind energy conversion systems (WECS) this issue of non-linearity,
control system plays a very vital role.
3. According to wind speed, a variable speed, variable pitch wind turbine has two operating regions.
Variable speed variable pitch wind turbine is of multiple inputs multiple outputs in nature.
4. The methods used to control Pitch angle is Fuzzy logic controller for interface with the process and
adjust the controller parameter by rules used.
5. The Fuzzy logic uses if-then rules defined with linguistic expressions and express the qualified
statements that comprise fuzzy logic.
6. A fuzzy if-then rule assume the form, if X is A then y is B. These verbal terminologies are derived
from human experts who have some experience and knowledge about the system.
7. Outputs produced by fuzzy Logic controller are more reliable because effect of noise parameter and
events due to wide range of control region had less impact on it.
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7. Suggestion for Future Work
India is a land of unlimited potential and Wind energy is a great source to fulfill
India’s energy needs as well as develop its economy. Future and development of
India depends upon many factors: one of them is being self dependent for its
energy demands. In India, metros network can be a great source of wind power
generation as it will need lighter
equipment than conventional wind turbines to harness the wind generated by
commute of metro trains.
wind turbines can be installed at sites of the metro tracks so without much extra
investment wind energy can be
generated.
Right now India’s is headed on an increasing graph with a slower slope than
before. It will have to keep the slope of this growth rate steeper if it wishes to
achieve its targets in energy sector.
713 August 2020
8. METYHODOLOGY
• The Project is about giving a simulation model of Wind
Turbine where we get an optimal pitch Angle of small
Wind Turbine model for the area where it will be installed.
• The Simulation Model used will provide the optimal Pitch
Angle for the Wind Turbine by analyzing the Wind pattern
of the Area.
• The Simulation model of MATLAB – SIMULINK R2019a
uses Mathematical calculations for giving the optimal
pitch Angle
• The THD are much more lower in Fuzzy Model as
Compare to PID model
13 August 2020
9. Tools and Technologies
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• Technologies involved while developing this project, is
Computational Intelligence and Power System
• Tools used is: Fuzzy Inference System, MATLAB 2019
Validation studies were conducted on the Dataset of Delhi NCR. The optimal
Pitch Angle came after the study by Fuzzy logic Control is 10.3 Degrees
which is precisely the value at which the pitch Angle is kept at the time of
Installation.
11. Diagrams
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Graphical Representation for Wind Speed and Pitch
Angle
Figure 2: Relation between Pitch Angle and Wind Speed
12. The graphical Changes between Pitch Angle and Power is:
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Graph between Pitch Angle and Wind Speed
Figure 3: Relation Between Pitch Angle & Power Output
14. Explanation of Results
1. When we change the rule-based membership functions of the fuzzy logic
controller, the model performance will be exaggerated.
2. The controller performance depends upon adopting the criteria of appropriate
rule base in the fuzzy inference system.
3. The rule base is depending upon variation in wind speed and an acceptable
pitch angle of turbines.
4. As a result, the variable velocity of the wind turbine using fuzzy logic
controllers for optimal pitch Angle has been obtained by MATLAB
simulation and shown in subsequent figures.
5. The Torque-Velocity Characteristics of Wind Turbine Model and PMSG
have been shown.
6. The results in terms of voltage, current and power output including rotor
velocity have been shown.
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15. The Results obtained from the simulation are shown and thus by using Fuzzy Inference
System and Fuzzy Logic Controller, The pitch angle controller and the output power has
been limited at variable wind speed and wind turbine can operate safely. The results are
taken at the values which are inherent in the MATLAB R2019a Simulink blocks and
from the Simulink results. The wind speed changes, then the pitch angle can be variable
according to pitch angle controller, for variable speed.
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CONCLUSIONS
16. FUTURE EXTENSION WORK
13 August 2020 16
The Work can be extended to a working prototype of project.
We can apply Machine Learning to the wind dataset for any coastal
area and can be trained to provide the data of pitch angle for that
area.
We can apply a feedback loop of fuzzy logic controller to PMSG for
better improvement of results.
Study on different parameters on which Pitch Angle depends
17. The Project can be extended by applying for funding to different schemes as:
1. Council of Science and Technology – Uttar Pradesh (CSTUP)
2. Kalam Annual Project and Poster Technical Competition (KAPPTeC)
3. Department of Science and Technology (DST)
4. Nidhi Prayas Yojna (NPY)
5. Nidhi EIR Yojna (NEIRY)
6. All India Council of Technical Education (AICTE)
7. Institute of Electrical and Electronics Engineering Grants (IEEE)
8. Institute of Electrical and Electronics Engineering Special Interest Group on
Humanitarian Technology (IEEE – SIGHT)
9. Ministry of Electronics and Technology (MIETY)
10.YCCC 2020 Stars, IIT Delhi
13 August 2020 17
GRANTS AND GOVERNMENT SCHEMES IN WHICH PROJECT CAN
BE APPLIED FOR FUTURE
18. FUTURE SCOPE
13 August 2020 18
India is a land of unlimited potential and Wind energy is a great source to fulfill
India’s energy needs as well as develop its economy. Future and development of
India depends upon many factors: one of them is being self dependent for its
energy demands. In India, metros network can be a great source of wind power
generation as it will need lighter
equipment than conventional wind turbines to harness the wind generated by
commute of metro trains.
wind turbines can be installed at sites of the metro tracks so without much extra
investment wind energy can be
generated.
Right now India’s is headed on an increasing graph with a slower slope than
before. It will have to keep the slope of this growth rate steeper if it wishes to
achieve its targets in energy sector.
19. PUBLICATION
13 August 2020 19
Poster Presentation on Arpit Bhushan Sharma, Brijesh Singh, Praveen Tyagi and
Neeraj Gupta, “Pitch Angle Control of Wind Turbine using fuzzy Inference
System for voltage and frequency control” in 3rd International Conference of
CIPECH’18 held at KIET Group of Institutions, Ghaziabad.
Poster Presentation on Arpit Bhushan Sharma, Brijesh Singh, Praveen Tyagi and
Neeraj Gupta, “Optimal Pitch Angle Control of Wind Turbine for power quality
improvement by using fuzzy Inference System” in KAPPTeC’19 held at Dr. APJ
Abdul Kalam Technical University, Lucknow.
Arpit Bhushan Sharma, Sandeep Tiwari and Brijesh Singh, “Optimal Pitch Angle
Identification and Minimizing of Power Variation in Wind Energy Conversion
System using Fuzzy Logic Controller” held at GUCON’2020, Noida.
First Prize in Technical Poster Presentation on Arpit Bhushan Sharma, Brijesh
Singh, Neeraj Gupta, “Pitch Angle Control of Wind Turbine using fuzzy logic
control” in JSPM'S Jayantrao Sawant College of Engineering Sponsored by IEEE
Pune Section, Pune Maharashtra
20. REFERENCES
[1] Pitch angle control for variable speed wind turbines
https://app.myloft.xyz/browse/article/ck99oh5lzi9820902kx6g6zpq
[2] Pitch angle control of a wind turbine operating above the rated wind speed: A sliding
mode control approach
https://app.myloft.xyz/browse/article/ck99okxn2id6x09028noq8513
[3] Wind Turbine Control Using PI Pitch Angle Controller
https://app.myloft.xyz/browse/article/ck99olnitidx00902naxstyx1
[4] Improving transition between power optimization and power limitation of variable speed,
variable pitch wind turbines using fuzzy control techniques
https://app.myloft.xyz/browse/article/ck99olwfeie610902otg9jbi4
[5] Pitch-control for large-scale wind turbines based on feed forward fuzzy-PI
https://app.myloft.xyz/browse/article/ck99om32eiec40902yjgbbpr0
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Downloaded from AKTU E- Consortium Application
21. [7] Wind turbine pitch angle control using Fuzzy Logic
https://app.myloft.xyz/browse/article/ck99pokoijhzw0902f2zyge85
[8] Aerodynamic power control of wind turbine using fuzzy logic
https://app.myloft.xyz/browse/article/ck99pou41jia2090243v6ldcf
[9] Pitch angle control for variable speed wind turbines
https://app.myloft.xyz/browse/article/ck99prhocjl9809024qbpwl5u
[10] Advanced Pitch Angle Control Based on Fuzzy Logic for Variable-Speed Wind Turbine
Systems
https://app.myloft.xyz/browse/article/ck99pr6vgjksn0902iwl81ta8
[11] Control of Pitch Angle of Wind Turbine by Fuzzy PID Controller
https://app.myloft.xyz/browse/article/ck99pruc0jlky090212vi1ljq
[12] Smoothing wind power fluctuations by fuzzy logic pitch angle controller
https://app.myloft.xyz/browse/article/ck99ps58cjltf0902e7pulcob
13 August 2020 21
22. [13] Pitch Angle Control for Variable Speed Wind Turbine Using Fuzzy Logic
https://app.myloft.xyz/browse/article/ck99psey2jm7d0902zof9i8gw
[14] Control strategy of wind power output by pitch angle control using fuzzy logic
https://app.myloft.xyz/browse/article/ck99ptpynjnhu09029464c2ye
[15] PI/FL based blade pitch angle control for wind turbine used in wind energy
conversion system
https://app.myloft.xyz/browse/article/ck99pt3ljjn2209020ov59h3m
[16] Coordinated Control of Wind Turbine Blade Pitch Angle and PHEVs Using MPCs for
Load Frequency Control of Microgrid
https://app.myloft.xyz/browse/article/ck99pthavjncx0902ij1yxy8v
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