SOLAR ENERGY CONTROL AND POWER QUALITY IMPROVEMENT USING MULTILAYER FEED FORWARD NEURAL NETWORK

Abstract

Oil, coal and gas continue to be the most demanded source of energy throughout the world along. In recent years, the alarming fall in amounts of fossil fuels and increase in atmospheric carbon dioxide composition have been seen on several occasions. These disadvantages of fossil fuels orientate the researchers toward renewable energy sources as a more durable long-term solution. The aim of this paper is to present a shunt active power filter (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF)  feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability

Keywords

• Harmonics Current,MLFFN,Photovoltaic Cells,MPPT,Shunt Active Power Filter SAPF

References

1. [1] Busa, V., Narsingoju, K. K., & Kumar, G. V. (2012). Simulation analyis of maximum power control of photo voltaic power system. International Journal on Advanced Electrical and Electronics Engineering (IJAEEE), 1(1), 9-14.
2. [2] Setiawan, E. A., Setiawan, A., & Siregar, D. (2017). Analysis on solar panel performance and pv-inverter configuration for tropical region. Journal of Thermal Engineering, 3(3), 1259-1270.
3. [3] Jeong, G. Y., Park, T. J., & Kwon, B. H. (2000). Line-voltage-sensorless active power filter for reactive power compensation. IEE Proceedings-Electric Power Applications, 147(5), 385-390.
4. [4] Izhar, M., Hadzer, C. M., Syafrudin, M., Taib, S., & Idris, S. (2004). Performance for passive and active power filter in reducing harmonics in the distribution system. In Power and Energy Conference, 2004. PECon 2004 Proceedings, 104-108.
5. [5] Gao, D., Lu, Q., & Sun, X. (2002). Design and performance of an active power filter for unbalanced loads. In Power System Technology, 2002. ProceedingsmPowerCon 2002, 2496-2500.
6. [6] Tumbelaka, H. H. (2006). A grid current-controlling shunt active power filter using polarized ramptime current control. Curtin University of Technology.
7. [7] Tumbelaka, H. H., Borle, L. J., & Nayar, C. V. (2002). Application of a shunt active power filter to compensate multiple non-linear loads. In Australasian Universities Power Engineering Conference (AUPEC).
8. [8] Tumbelaka, H. H., Nayar, C. V., Tan, K., & Borle, L. J. (2003). Active filtering applied to a line-commutated inverter fed permanent magnet wind generator. In International Power Engineering Conference IPEC2003, Singapore.

9. [9] Wada, K., Fujita, H., & Akagi, H. (2002). Considerations of a shunt active filter based on voltage detection for installation on a long distribution feeder. IEEE Transactions on Industry Applications, 38(4), 1123-1130.
10. [10] Yahfdhou, A., Mahmoud, A., & Youm, I. (2013). Modeling and optimization of a photovoltaic generator with matlab/simulink. International Journal of I Tech and E Engineering, 3(4), 108-111.
11. [11] Dehini, R., Bassou, A., & Ferdi, B. (2009). Artificial neural networks application to improve shunt active power filter. International Journal of Computer and Information Engineering, 3(4), 247-254.
12. [12] Pusat, S., & Akkoyunlu. (2018). Effect of time horizon on wind speed prediction with ANN. Journal of Thermal Engineering, 4 (2), pp. 1770-1779.