Abstract：Photovoltaic (PV) array is often composed with a lot of photovoltaic modules in series or in parallel,which make it difficult to obtain the accurate fault locations when some PV modules are failure. To well dispose this problem,a novel strategy of fault location by use of Gaussian process(GP) regression is presented in this paper. First,binary strings are designed to represent the states of the PV array,and then a regression model of the fault location by converting the binary strings into corresponding integers is presented. Based on the voltage and current as well as the converted integers,the Gaussian process is trained. With newly measured voltage and current,the current state of the PV array is diagnosed by using the trained Gaussian Process. The proposed algorithm is applied to a 2#x000d7;4 PV array and verified via four different fault states,i.e.,one module,two modules,three modules and four modules are failure. By comparing with the common used BP network in fault diagnosis and location,the effectiveness of our algorithm is empirically demonstrated. The results show that the Gaussian Process based method outperforms BP network one in more accurately locating the faults. Furthermore,the proposed algorithm is more benefit for the first three fault states than the one that four modules are failure.
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2013, Vol. 28 
