Affiliations: [a] Department of Electrical Engineering, Hefei University, Hefei, China
| [b] Department of Statistical Science, Southern Methodist University, Dallas, TX, USA
Correspondence:
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Corresponding author. Maofa Zhen, Department of Electrical Engineering, Hefei University, Hefei 230601, China. E-mail: [email protected].
Abstract: Nowadays, the multi-sensor information fusion algorithm of the integrated power grid operation system based on Bayesian network is disturbed by the high flow data, causing that the single data fusion level and large convergence error. Therefore, an intelligent fusion algorithm of multi-sensor information in integrated power grid system is proposed. According to the asynchronous aggregation distribution construction algorithm based on hierarchical clustering, and in accordance with the hierarchical clustering, all nodes are put to aggregate and construct a collection tree according to the distance, then calculate the optimal grouping number. Then based on the number of grouping, grouping is implemented. According to asynchronous distributed strategy, selection of the optimal aggregation nodes and construction of the optimal transmission topology are carried out, to quickly find the aggregation mode of sensor data in power grid with minimal overhead, in order to reduce the data flow of power grid. In the aggregation distribution environment of multi-sensor, based on the principle of multi-sensor information fusion and detection in the integrated power grid operation system, the information fusion abstract model of the integrated power grid operation system is applied. The multi-sensor information fusion is divided into three levels: data level, feature level and decision level. The functional structure of multi-sensor information fusion can realize the effective fusion of multi-sensor information. The experimental results show that the proposed algorithm has a high accuracy and stability of information fusion, and can reduce the loss of the power grid.
Keywords: Integrated power grid, operation system, multi-sensor, hierarchical clustering, asynchronous distributed, information intelligent fusion
