Title :
Development of an expert configuration of stand-alone power PV system based on adaptive neuro-fuzzy inference system (ANFIS)
Author_Institution :
Dept. of Electron., Medea Univ. Center
Abstract :
Stand-alone photovoltaic power supply (SAPVPS) systems are widely used in renewable energy source (RES) application in order to product electricity particularly in remote areas. In this paper, the development of an expert configuration of PV power supply systems based on ANFIS model is described. The proposed configuration combines a PV system, data acquisition card, and an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS model has been trained by using a database of different signals obtained from the data acquisition system in order to identify and control the output current and voltage of the SAPVS needed by the load. The comparison between experimental and simulated signals gives an accuracy results. The developed configuration permits the rapid system development and has the advantage of the flexibility in case of change, while if can be easily extended for management the RES system operation
Keywords :
control engineering computing; data acquisition; electric current control; fuzzy neural nets; inference mechanisms; photovoltaic power systems; power engineering computing; power generation control; voltage control; ANFIS; adaptive neuro-fuzzy inference system; data acquisition system; expert configuration; output current control; photovoltaic power supply; renewable energy source; stand-alone power PV system; voltage control; Adaptive systems; Data acquisition; Databases; Photovoltaic systems; Power supplies; Power system modeling; Renewable energy resources; Signal processing; Solar power generation; Voltage control; ANFIS; Control; Expert system; Prediction;
Conference_Titel :
Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
Conference_Location :
Malaga
Print_ISBN :
1-4244-0087-2
DOI :
10.1109/MELCON.2006.1653242
