DEVELOPMENT OF REAL-TIME SIMULATOR BASED ON INTELLIGENT TECHNIQUES FOR MAXIMUM POWER POINT CONTROLLER OF PHOTOVOLTAIC SYSTEM


Syafaruddin S., KARATEPE E., Hiyama T.

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, vol.6, no.4, pp.1623-1642, 2010 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 4
  • Publication Date: 2010
  • Journal Name: INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1623-1642
  • Keywords: Photovoltaic system, MPP, ANN, Fuzzy logic controller, Real-time simulator, NEURAL-NETWORKS, TRACKING, IDENTIFICATION, MODEL, CONVERTER, ARRAYS
  • Dokuz Eylül University Affiliated: No

Abstract

The power conversion efficiency of solar cell depends on material science. On the other hand, it is a very important issue to reduce the power losses in photovoltaic systems. Many available commercial P V modules have been used. However, since their characteristics are not unique and on-site testing of PV system is costly, time-consumed and highly dependent on the prevailing weather conditions, a real-time simulator becomes an important tool to support the research and development in P V system. The impact of operating conditions on different solar cells performance should be well understood at optimal operating points to increase the efficiency of photovoltaic systems. This paper firstly explores the relationships between solar intensity and operating temperature variations and key solar cell parameters for commercial available photovoltaic modules. The results show that the characteristics of different solar cell technologies at maximum power point (MPP) have different trends in current-voltage characteristic. In this reason, a robust real-time simulator is very important for different solar cell technologies. Then, this paper presents intelligent real-time simulator for simulating and testing the effect of the fluctuation of irradiance level and cell temperature on the MPP performance of PV modules. Intelligent techniques are becoming useful for non-linear problems because of their symbolic reasoning, flexibility and generalization capabilities. There is a trade-off between the complexity of system and efficiency in optimally operating photovoltaic modules. This method is highly dependent on ANN training process for each cell technology and simply generates control signal required in fuzzy logic controller. The developed real-time simulator has been successfully demonstrated for different commercially available photovoltaic modules.