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Research On Optimal Control System For Regional Power Networks And Its Integrated Design

Posted on:2006-06-05Degree:MasterType:Thesis
Country:ChinaCandidate:J F HeFull Text:PDF
GTID:2132360182469715Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
The power system has grown rapidly in recent years, which adds the complexity of control. At the same time, users require better voltage quality and adequate security. In addition, economic issues have to be considered for the power system itself. Thus, the control of a power system is a multi-objective global optimization problem that requires more effective and robust strategies. The main task we should face now is to make a way out of how to enhance the control level in the existing conditions, to improve the voltage quality, and to make the power system operated under the optimal state. The basic concept and principle are introduced systemically. After reviewing kinds of schemes for voltage and reactive power control (VQC), a scheme and its model of optimal coordinated-correlative control for the regional power system is developed based on the home actuality of VQC. The scheme has a two-level structure, which can neatly realize optimal coordinated control and can disperse the responsibilities of control. When it is permitted by the conditions, a scheme of centralized optimization may be used, for it can realize global optimal control theoretically. The corresponding idea and the frame for regional power system are provided with the model. Hybrid method (HGA) of genetic algorithm (GA) and tabu search (TS) is used to get the solution of reactive power optimization. The application of HGA in reactive optimization is introduced in detail, and some effective improvements are proposed refer to the standard GA. At the end of the paper, a soft system for regional VQC is designed elementarily, including the function, the idea and the frame.
Keywords/Search Tags:Voltage Reactive Power Optimal Control, Regional Power System, Coordinated-Correlative Control, Hybrid Genetic Algorithm
PDF Full Text Request
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