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Guo R.,Zhejiang University | Chiang H.-D.,Cornell University | Wu H.,Zhejiang University | Li K.,Fujian Power Dispatch and Telecommunication Center | Deng Y.,Fujian Power Dispatch and Telecommunication Center
IEEE Power and Energy Society General Meeting | Year: 2012

A two-level system-wide AVC system based on optimal reactive power flow (ORPF) is proposed. The architecture of this two-level system-wide AVC system is different from the popular three-level hierarchical structure in that it is implemented centralized. One distinguished feature of the described AVC system is that it does not require the need of performing zone division and it can automatically adapt to structural changes in power systems. Another feature of the described AVC system is that it works even when the state estimation function of the underlying control center fails. To achieve a close-loop automatic voltage control, the two-level system-wide AVC system has two optimization-based voltage control modules: an optimal reactive power flow module and a corrective voltage control (CVC) module. At present, the proposed AVC system has been commissioned and put into a close-loop mode in four provincial power grids in China. The performance of the two-level system-wide AVC system has been very encouraging. © 2012 IEEE. Source


Wang X.,Zhejiang University | Guo R.,Zhejiang University | Cao Y.,Zhejiang University | Yu X.,Fujian Power Dispatch and Telecommunication Center | Yang G.,Fujian Power Dispatch and Telecommunication Center
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2011

An efficient algorithm of power systems reliability evaluation named separate importance sampling (SIS) taken from different contingencies order state subspaces was presented. With the SIS, the system state space is partitioned into one contingencies free state subspace (CFSS) and different contingencies order state subspaces (DCOSS). State enumeration method is used for handling lower order contingencies state subspaces, for the number of states in these subspaces is smaller. And SIS is applied to higher order contingencies state subspaces, for the number of states in them is larger. Because sampling the CFSS is avoided and DCOSS are considered separately, the SIS is efficient and can be applied to reliable power system. Compared to other methods, the results of the IEEE-RTS test system show that the proposed algorithm is correct and effective. © 2011 Chin. Soc. for Elec. Eng. Source


Wang X.,Zhejiang University | Guo R.,Zhejiang University | Cao Y.,Zhejiang University | Yu X.,Fujian Power Dispatch and Telecommunication Center | Yang G.,Fujian Power Dispatch and Telecommunication Center
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2011

A new method for power system reliability evaluation called self-adapting stratified and importance sampling (SASIS) is presented. With the SASIS, the system state space is partitioned into one contingency-free state subspace and various contingency order state subspaces. As contingency-free state subspace sampling is completely avoided, the SASIS converges fast in the system with high reliability. The number of sampling is optimally allocated among the contingency order state subspaces and the probability density function is steadily rectified. This method will markedly increase the calculating efficiency while eradicating the problem of low efficiency with the Monte Carlo method in high efficiency systems as reported in the past. Compared with other Monte Carlo methods, the results of the IEEE-RTS test system show that the method proposed is rational and highly effective and free from degradation. © 2011 State Grid Electric Power Research Institute Press. Source


Huang J.,Zhejiang University | Guo R.,Zhejiang University | Zhao F.,Zhejiang University | Yu X.,Fujian Power Dispatch and Telecommunication Center | Yang G.,Fujian Power Dispatch and Telecommunication Center
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2013

In view of the low efficiency of power system reliability evaluation, an efficient power system reliability evaluation algorithm was presented to maximize the computational efficiency. The system fault states were divided into sorting fault subset and sampling fault subset and thus efficiency degradation was avoided. Simultaneously the number of sampling times of various faults was optimally allocated. The sampling covariance was efficiently reduced and the convergence was accelerated. Compared with Monte Carlo simulation and importance sampling method, the results of the IEEE-RTS79 test system and revised system show that the proposed algorithm has higher calculation efficiency and is feasible in the reliability evaluation of large-scale power systems. Source

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