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The performance of the process network in the smart substation is particularly important for relaying functions implementation, and the transmission quality of sampled value packets is becoming the key constraint on protections because they carry practical parameters of the power system without repeated transmission. By means of phasor form and simulation, the model is built to analyze the operating characteristics of differential protection during the normal condition, external faults, and internal faults of the transformer, while packet loss/delay occurring at a different time and using different corrective measures. Considering the change of power equipment capacity, external fault types, starting points on wave and sampling frequency, the security boundaries are constructed for consecutive loss of sampled value packets. In addition, two indices are put forward to weigh the tolerance thresholds. Finally, the degree of dependability of differential protection due to the packet loss is further analyzed under the transformer internal faults.

In traditional data fusion algorithms based on context awareness, time-varying application situations and context acquisition cost are not considered, which leads to inaccurate situation prediction and low applicability of data fusion. In this paper, a space-based context model is introduced, in which the sensors' history from three aspects, the context attribute, the context state and the situation space are described. Then optional attributes with the maximum overall utility are chosen by Dynamic Bayesian Networks. After that, the related situation prediction is obtained through data fusion. A data fusion algorithm CFACA (Context Fusion Algorithm based on Context Awareness) proposed in this paper gives a dynamic data fusion method. In the end, the simulation of this algorithm is discussed and the results show the effectiveness of the CFACA.