The unbalanced distribution of resource and consuming centers in China has prompted the AC/DC hybrid transmission technology. The maintenance scheduling of an AC/DC hybrid transmission network is the key technology to ensure its safety and reliability. In this study, the mutual influence mechanism of an AC/DC system in a maintenance period was analyzed in detail. The overhead transmission line and transformer are key equipment within an AC/DC hybrid transmission network, and an optimization model of the key equipment maintenance scheduling was established. The objective of the model was to improve the system reliability during the maintenance scheduling. By considering the constraints of maintenance cost, maintenance resources, and maintenance workload, the maintenance scheduling of overhead transmission lines and transformer branches was obtained. The over-limit situation of power flow and the weakness of the system during the maintenance period was evaluated. The “double-layer substitution method” was adopted to convert the nonlinear constraints into its bilinear formulation such that it could then be solved. The random number sampling method was used to quantify the system reliability, and the commercial optimization software was used to solve the optimized scheduling. Based on the improved IEEE RTS-79 system and the Hubei Province electrical system, the simulation results showed the effectiveness of the proposed method.
Multi-microgrids (MMGs) suffer from power shortages due to the loss of utility grid support when an unintentional transition occurs. This imposes a transient shock on the system voltage and frequency. To maintain the frequency stability and power balance of an islanded MMG, this paper presents an underfrequency load shedding (UFLS) strategy with adaptive variation. A comprehensive load evaluation method based on a composite least squares support vector machine (CLS-SVM) is proposed to ensure uninterrupted power for critical loads. This method considers the comprehensive evaluation influence factors (CEIFs) of loads. Then, a least squares support vector machine (LS-SVM) provides the load shedding determination factors, transforming the problem of determining critical loads into a 0-1 planning problem. A method with adaptive variation is proposed to solve the UFLS model. The effectiveness of the proposed strategy is verified for an MMG model based on a modified IEEE 33-bus system. The test results show that: 1) the average accuracy of the proposed method is 21.05% higher than that based on LS-SVM; 2) compared with UFLS strategies based on the load level alone and on an intelligent algorithm, the frequency fluctuation range of the proposed strategy is 12.50% and 19.23% lower, respectively, and the frequency recovery time is 3.90% and 5.73% shorter, respectively; 3) compared with PSO, GOA and GA, the standard deviation of the iterative mean of the proposed algorithm decreases by 36.22%, 53.42%, and 34.00%, respectively. The proposed strategy can reduce the frequency fluctuation range and frequency recovery time while maintaining strong adaptability.INDEX TERMS Adaptive solution method, comprehensive evaluation, load shedding, microgrid, power shortage.
As an important basis for the management of equipment and data assets of smart hydropower plants, the operation statistical analysis service provides a data basis for the management and analysis of the overall operation of various equipment and power plants. In this paper, the functions and business requirements of the service were analyzed, and the overall design of the system architecture and the design and software development of databases, configuration programs, statistical analysis, background data processing, etc., were carried out. With the service, the processing and calculation functions of multi-source service measurement point data were realized, which provided data support for a variety of display forms of human-computer interaction interface.
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