Assessment on power systems non-deterministic state estimation algorithms

Power systems are operated in a deterministic way. However, the increase in uncertainties (caused by measurement and communication errors or the absence of complete knowledge of the measured quantity) requires algorithms capable of assessing randomness in real-time monitoring and operation of energy management systems. Among them, state estimation is a fundamental element that provides complete and reliable information about the current network state. This paper offers a review of non-deterministic algorithms, used to assess the randomness caused by the uncertainties in power system state estimation. Depending on the uncertainty modeling method, different static and dynamic non-deterministic state estimation algorithms for transmission and distribution systems are reviewed. Also, four of the most relevant algorithms are implemented and results are compared for distribution networks. The relevance of such models, as well as their motivation, are addressed.