Distributed State Estimation Using RSC Coded Smart Grid Communications

作者：Rana Md Masud; Li Li; Su Steven

来源：IEEE Access, 2015, 3: 1340-1349.

DOI：10.1109/ACCESS.2015.2467168

• Distributed energy resource
• Kalman filter
• recursive systematic convolutional code
• smart grid
• state estimation

Recently, the renewable distributed energy resources (DERs) have become more and more popular due to carbon-free energy sources and environment-friendly electricity generation. Unfortunately, these power generation patterns are mostly intermittent in nature and distributed over the electrical grid, which creates challenging problems in the reliability of the smart grid. Thus, the smart grid has a strong requisite for an efficient communication infrastructure to facilitate estimating the DER states. In contrast to the traditional methods of centralized state estimation (SE), we propose a distributed approach to microgrid SE based on the concatenated coding structure. In this framework, the DER state is treated as a dynamic outer code, and the recursive systematic convolutional (RSC) code is seen as a concatenated inner code for protection and redundancy in the system states. Furthermore, in order to properly monitor the intermittent energy source from any place, this paper proposes a distributed SE method. Particularly, the outputs of the local SE are treated as measurements, which are fed into the master fusion station. At the end, the global SE can be obtained by combining local SEs with corresponding weighting factors. The weighting factors can be calculated by inspiring the covariance intersection method. The simulation results show that the proposed method is able to estimate the system state properly.

• 出版日期2015