Int. J. Simul. Multidisci. Des. Optim.
Volume 11, 2020
|Number of page(s)||11|
|Published online||14 July 2020|
Cleaning cycle optimisation in non-tracking ground mounted solar PV systems using Particle Swarm Optimisation
Department of Industrial and Manufacturing Engineering, Harare Institute of Technology, Belvedere, Harare, Zimbabwe
2 Amity School of Engineering and Technology, Amity University, Gurgaon, India
3 Department of Mechanical and Industrial Engineering, University of South Africa, Florida, South Africa
* e-mail: email@example.com
Accepted: 5 June 2020
The effect of installation azimuth angle in the optimization of the cleaning cycle of a solar photovoltaic plant was experimentally investigated in this study. The optimum cleaning cycle was determined using Particle Swarm Optimization algorithm cognizance of the fact that different orientations have different soiling rates. Soiling rates on three different azimuth configurations were experimentally investigated and an exponential soiling loss model was developed for each configuration for use in the optimization problem. Azimuth angle differences of ±12.5% were found to have a significant influence on soiling of as much as 28.29% for the selected location. The North of North West configuration was found to be optimal as opposed to the generally accepted North configuration for maximum energy generation at a minimum cost of energy. This configuration generated 0.87% more energy at unit energy cost of $0.093 compared to the North configuration which had a minimum cost of $0.113. The optimized cleaning cycles were 35 days for the optimal configuration while the North configuration had an optimized cleaning cycle of 28 days. A 17.7% difference in the cost of energy was recorded due the influence of soiling. The study revealed that for minimizing the unit energy cost, it is necessary to take into effect the influence of soiling.
Key words: Soiling / solar photovoltaics / installation azimuth / cleaning optimization / cleaning frequency
© K. Chiteka et al., published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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