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To satisfy the robust and real-time requirements of power flow calculation for large-scale power systems, a globally convergent method is proposed with trust-region techniques, which shows satisfying robustness and convergence. Then, this method is combined with Newton's method to achieve a two-stage algorithm, benefiting from their different advantages. In the first stage, the proposed globally convergent method is used for searching power flow solution. When the values of state variables in a certain iteration are close enough to the real operational point, the algorithm enters the second stage to use Newton's method to achieve the solution. This two-stage algorithm can achieve an accurate solution for solvable cases, and can also achieve a least-square solution, which is an approximate solution for unsolvable cases. Numerical experiments show that the proposed globally convergent method and two-stage algorithm have better robustness and efficiency than the existing methods in previous research. They have universality for well- and ill-conditioned systems as well as the cases under ill-conditioned operational modes, heavy loads and inappropriate initial values. They can also handle different limit violations, such as reactive power limit in PV buses and voltage limit with tap changers action, which could significantly benefit real practice. [ABSTRACT FROM AUTHOR]

Previous work has shown that robust state estimator based on maximum normal measurement rate is accurate and reliable. However, in the existing algorithm, the optimal solutions cannot be obtained due to the approximation of evaluation function. Besides, there are no noise-filtering effects on normal measurements. To deal with these two problems, this letter presents an improved algorithm to get a more accurate solution with higher normal measurement rate. Numerical tests on different systems show the proposed algorithm is efficient. [ABSTRACT FROM PUBLISHER]

• A parallel and asynchronous state estimation method for power system is proposed. • The method contains four improvements to speed up the iteration process. • A sensitivity analysis mechanism to obtain key distribution network is proposed. • The method proposed can effectively handle with communication delays. • The method proposed has low sensitivity to parameter changes. Considering the increasing scale of power systems and gradually coupling between transmission networks (TNs) and distribution networks (DNs), a parallel and asynchronous state estimation (par&async-SE) algorithm is proposed to deal with communication delays. First, the coupled transmission-distribution network state estimation problem is reformulated in line with engineering practice. Then, a TN broadcast transmitting strategy, a synchronous preprocessing technique, and a receive-compute-transmit parallel mechanism are applied to improve conventional asynchronous algorithm. Moreover, a 'key DN' concept is introduced and a sensitivity analysis method is proposed to realize key DNs selection. These improvements make the par&async-SE algorithm proposed not only have a higher convergence rate and efficiency but also be less sensitive to parameter settings. Numerical experiments demonstrate that the par&async-SE algorithm has the same accuracy as conventional algorithms. It can also achieve better convergence, reduce computation time, and be less sensitive to parameter settings than the synchronous state estimation algorithm and conventional asynchronous state estimation algorithm when communication delays exist, so that parameter tuning for this self-adaptive algorithm is not necessary in engineering practice. Besides, the par&async-SE algorithm also has bad data robustness when choosing appropriate methods to solve extended-TNSE and DNSE subproblems. [ABSTRACT FROM AUTHOR]