Nunierically stable and computationally efficient Power System Statc Estimation (PSSE) algorithms are designed using Orthogonalization (QR decomposition) approach. They u3e Givens rotations for orthogonalization which enables sparsity exploitation during factorization of large sparse auginentecl Ja,cobian. Apriori row and column ordering is usiially performed to reduce intermediate a.nd and overall fills. Column ordering methods, usually based on Minimum Degree .4lgorithm (T\ID.4), have matured. However, t,heir exists a significa.rit scopc for improving the quali t,y of row ordering. This paper introduces a new row ordering technique for Givens rotat*ions based power system staw est,imators. The proposed row processing method (IT-4IR) requires a shift, from conventionally used row orieiited QR decomposition impl6mentation to a column orierl:.ed QR decomposit,ion implement,ation. It is deII-lonstrht.rd that, the proposed colur in oriented Q R decompositio,i algorithm which uses iZ/ID:i for column ordering and VP.1 IR for row ordering can lead t,o a. milch faster PSSE. These aspects are justified by simulations on large power systems.

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Grid integration of non conventional energy resources is increasing in day to day life to supply the global energy utilization requirement. The major problem with such integrated Distributed Generation (DG) is islanding. The islanding is originated in the integrated system when a part of the power system is disconnected from the grid and continue to feed the local load. The islanding is not safe to field persons and equipment. As per IEEE 1547 standards, the islanding should be detected within 2 seconds with the equipments associated with it. In this paper, a new islanding detection method is proposed with fuzzy rule based approach with inputs as the change in frequency and power. This method classifies the islanding and non islanding events efficiently compared to other passive methods. The simulations are carried on Matlab/ Simulink 2018b environment.

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