Maximizing Solar Cell Power Output using in Solar Powered Water Treatment System by Particle Swarm Optimization Algorithm
Keywords:
Solar cell, Maximum Power Point Tracking, Efficiency, Particle Swarm OptimizationAbstract
This research presents the optimization of solar powered water treatment system by Particle Swarm Optimization algorithm. This algorithm is used to find the maximum power point tracking (MPPT) of the solar cell to send the maximum power output to the of solar powered water treatment system. Even in the case of shadows obscure portions or in the case of low light intensity. Therefore, the efficiency of the solar powered water treatment system is more efficient. This research has applied the average particle swam optimization algorithm. This algorithm has a structure that is easy to use, uncomplicated and accuracy in calculations. The system consists of solar cells connected in an array which power supply through the inverter circuit. To find the peak of power output. The System simulation is performed using MATLAB and POWERSIM in the simulation of average Particle Swarm Optimization algorithm and Setting to cover some shadows. Conducted a real experiment, which the results of the experiment found to be consistent with the simulation results.
References
Kashif, I., & Zainal, S. (2012). Deterministic Particle Swarm Optimization Maximum Power Point Tracker for Photovoltaic System Under Partial Shading Condition. IEEE Transactions on Industrial Electronics, Vol 60 , Issue: 8.
Kaweepoj Woranetsuttikul, Isaree Srikun, Promphak Dawan. (2019) .Design and Construction a brushless DC Motor control For small electric vehicles. The journal of Industrial Technology Suan Sunandha Rajabhat University, Vol 7 (No 1), Page 53-61.
Krittapas Phinsuntea. (2015). Design Technique of brushless DC motor control with Sensorless Back EMF Zero Crossing Detection. (Master’s thesis). King Mongkut’s Institute of Technology Ladkrabang, Faculty of Engineering, Majoring in Electrical Engineering.
Nattawat Jumpasri. (2014). Improved particle swarm optimization algorithm using average model on PV array maximum power point tracking. (Master’s thesis). King Mongkut’s Institute of Technology Ladkrabang, Faculty of Engineering, Majoring in Electrical Engineering.
Nattawat Jumpasri. (2014). Improved Particle Swarm Optimization Algorithm using Average Model on MPPT for Partial Shading in PV Array” iEECON 2014. Page 101-104.
Nattawat Jumpasri. (2014). “Comparison of Distributed and Centralized control for Partial Shading in PV Parallel Based on Particle Swarm Optimization Algorithm” iEECON 2014. Page 363-366.
Nop Mahisanon. (2017). Solar system And self-produced energy. (1) Bangkok: Core Function.
Poom Konghuayrob. (2013). A study on multiple step size incremental conductance technique and fuzzy logic control for MPPT in flyback PV inverter. (Master’s thesis). King Mongkut’s Institute of Technology Ladkrabang, Faculty of Engineering, Majoring in Electrical Engineering.
Siwa Hongnapha. (2004). Control and AC Drive Application. Bangkok: Good View Collection Co.,L
Suwattana Jitladakorn. (2013). Decision Support System for Water Resources Engineering Management. (1). Bangkok: Kasetsart University.
Taywin nilsakron. Promphak Dawan . (2016). A Study of the Effect of BLDC Motor Operation and ASD Adjusted by Various Position of Hall Effect Sensors. Wichcha journal Nakhon Si Thammarat Rajabhat University,Vol. 35 (No.), Page 79 – 91.
Tawin Nilsakhon. (2014). Efficiency improvement on brushless DC motor drive systems. Thesis Master of Engineering in Engineering King Mongkut's Institute of Technology Ladkrabang.
Weerachet khunngern and Wuttipol Tarateraset. (2014). Power Electronices (3). Bangkok: v-j-printing-limited-partnership.
Yi-Hwa Liu ; Shyh-Ching Huang, Jia-Wei Huang & Wen-Cheng Liang. (2012). A Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for PV Systems Operating Under Partially Shaded Conditions. IEEE Transactions on Energy Conversion, Vol 27, Issue: 4.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Faculty of Industrial Technology, Suan Sunandha Rajabhat University
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
บทความที่ได้รับการตีพิมพ์เป็นลิขสิทธิ์ของคณะเทคโนโลยีอุตสาหกรรม มหาวิทยาลัยราชภัฎสวนสุนันทา
ข้อความที่ปรากฏในบทความแต่ละเรื่องในวารสารวิชาการเล่มนี้เป็นความคิดเห็นส่วนตัวของผู้เขียนแต่ละท่านไม่เกี่ยวข้องกับมหาวิทยาลัยราชภัฎสวนสุนันทา และคณาจารย์ท่านอื่นๆในมหาวิทยาลัยฯ แต่อย่างใด ความรับผิดชอบองค์ประกอบทั้งหมดของบทความแต่ละเรื่องเป็นของผู้เขียนแต่ละท่าน หากมีความผิดพลาดใดๆ ผู้เขียนแต่ละท่านจะรับผิดชอบบทความของตนเองแต่ผู้เดียว
