A new online static voltage stability monitoring method for power systems is proposed by using phasor measurement unit (PMU) data in this paper. This approach uses the real-time power, voltage, and phase angle data collected by the PMU to estimate the power flow Jacobian matrix of the system, and then the static voltage stability is monitored via the minimum singular values (MSVs) of the power flow Jacobian matrix. The novelty of the approach lies in the fact that it only utilizes PMU data for implementing online monitoring of the power system static voltage stability, independent of the physical model and its parameters. The application results on the IEEE 57-bus test system verify the effectiveness of the proposed approach.

A novel transient stability assessment (TSA) approach using random vector functional link (RVFL) network optimized by Jaya algorithm, called Jaya-RVFL, is proposed for power systems in this paper. First, by extracting system-level features from phasor measurement unit (PMU) measurements as predictors, an RVFL-based TSA model is proposed. In order to improve the performance of RVFL classifiers, a quantile scaling approach is utilized to optimize the randomization range of input weights via the Jaya algorithm. The simulation results on IEEE 39-bus system and a real-world power system show that the presented method outperforms other popular methods comprising multilayer perception, probabilistic neural network, and support vector machine.

With the deepening of digital transformation and upgrading of power grid enterprises, the digital system evaluation method of power grid enterprises based on experts’ subjective experience has been unable to meet the management needs of modern enterprises. In this paper, a method based on fuzzy information axiom for dynamic design quality evaluation of digital system in electric power enterprises is proposed. Firstly, the electric power enterprise digital system dynamic design quality comprehensive evaluation index system is set up from three aspects, which are achievement degree of target business function, logical relation rationality, and technical economy of physical model. Secondly, the quantitative and qualitative index values are processed by using the information calculation formula of minimum information axiom and fuzzy membership function. And then best-worst method and antientropy weight method are used to form the comprehensive evaluation model. Finally, the feasibility and effectiveness of the design scheme are verified by an example of dynamic design of digital system in power enterprise.

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