Call for Paper

CAE solicits original research papers for the July 2019 Edition. Last date of manuscript submission is June 30, 2019.

Read More

Genetic Algorithm-Optimized PID Controller for better Performance of PV System

Roshdy Abdelrassoul, Yosra Ali, Mohamed Saad Zaghloul. Published in Algorithms.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Roshdy Abdelrassoul, Yosra Ali, Mohamed Saad Zaghloul

Roshdy Abdelrassoul, Yosra Ali and Mohamed Saad Zaghloul. Genetic Algorithm-Optimized PID Controller for better Performance of PV System. Communications on Applied Electronics 5(9):55-60, September 2016. BibTeX

	author = {Roshdy Abdelrassoul and Yosra Ali and Mohamed Saad Zaghloul},
	title = {Genetic Algorithm-Optimized PID Controller for better Performance of PV System},
	journal = {Communications on Applied Electronics},
	issue_date = {September 2016},
	volume = {5},
	number = {9},
	month = {Sep},
	year = {2016},
	issn = {2394-4714},
	pages = {55-60},
	numpages = {6},
	url = {},
	doi = {10.5120/cae2016652380},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing PID controller to control the system. Parameters of the designed controller are tuned using genetic algorithm (GA) which leads to getting the best performance of the designed PV system. Using GA the maximum overshoot and rise time obtained become 0.1% and 0.175 seconds, respectively.


  1. Pandiarajan, N.; Muthu, Ranganath. Mathematical modeling of photovoltaic module with Simulink. In: Proceeding of International Conference on Electrical Energy System. 2011. pp. 3 -5.‏
  2. Qi, Chen; Ming, Zhu. Photovoltaic module Simulink model for a stand-alone PV system. physics procedia, 2012, 24: pp. 94 -100.‏
  3. Sahin, Erol; Ayas, Mustafa Sinasi; Altas, Ismail Hakki. A PSO optimized fractional-order PID controller for a PV system with DC-DC boost converter. In:Power Electronics and Motion Control Conference and Exposition (PEMC), 2014 16th International. IEEE, 2014. pp. 477 - 481.‏
  4. Chowdhury, Ahmed Sony Kamal; Salam, K. M. A.; Razzak, M. Abdur. Modeling of MATLAB-Simulink based photovoltaic module using flyback converter. In: Strategic Technology (IFOST), 2014 9th International Forum on. IEEE, 2014. pp. 378 - 381.‏
  5. Brigitte Hauke, “Low power DC-DC application/Basic calculation of a boost converter’s power stage”, Texas Instrument application report, July, 2010.
  6. L.Y. Chang, H.C. Chen, “Tuning of fractional PID controllers using adaptive genetic algorithm for active magnetic bearing system”, WSEAS Transactions on Systems, Vol. 8, 2009, pp. 226-236.
  7. A. Biswas, S. Das, A. Abraham, S. Dasgupta, “Design of fractionalorder P IλDµ controllers with an improved differential evolution”, Engineering Applications of Artificial Intelligence, Vol. 22, 2009, pp. 343- 350.
  8. M. Zamania, M. Karimi-Ghartemanib, N. Sadatib, M. Parnianib,, “Design of a fractional order PID controller for an AVR using particle swarm ptimization”, Control Engineering Practice, Vol. 17, 2009, pp. 1380-1387.
  9. Johnson, Michael A., and Mohammad H. Moradi. PID control. Springer-Verlag London Limited, 2005.
  10. Haupt Randy L., Haupt Sue Ellen, "Practical Genetic Algorithms" Second Edition, 2004, pp.189-190.


Genetic algorithm, photovoltaic, PID controller