Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6860765 | International Journal of Electrical Power & Energy Systems | 2013 | 10 Pages |
Abstract
In restoring a power system after a major disturbance, system operators often encounter an excessive standing phase angle difference (SPA) between two buses of a circuit breaker when a transmission line is energized and results in a loop closure. Under such a condition, there is high risk of damage to nearby generators and other equipments for the breaker/loop closure operation. Since the SPA value is a function of the restoring system topology, load and generation injections, the SPA reduction becomes an important problem in system restoration. Presently, generation rescheduling is adopted as a primary control means and load shedding is used as the final resort to reduce the SPA. In fact, there remains a lot of unserved load in the system throughout the restoration process. Since the unserved load that can help reduce the SPA is not picked up and selected as a control means, the existing control strategy for SPA reduction is not optimal for a system under restorative state. In this paper, a new method that incorporates load pickup as a control means is proposed to address the SPA reduction problem. Firstly, a general principle for SPA reduction is established, i.e., a smaller SPA can be achieved by lowering the total active power flow transmitted from the sending-end to the receiving-end subsystem. Based on which, the pickup of load in the sending-end subsystem and the increased active power generation in the receiving-end subsystem are combined as control means. Then a mixed integer nonlinear programming (MINLP) algorithm and an alternative two-stage decoupled (TSD) algorithm are proposed to develop specific control strategies. The algorithms can help restore some unserved load during the process of SPA reduction and, thus, are more effective in achieving the goal of power system restoration. Simulation results on the New England test system demonstrate the effectiveness of the proposed algorithms.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hua Ye, Yutian Liu,