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Multi-Objective Distributed Reactive Power Optimization Based On Subarea Division Of Power System

Posted on:2009-06-16Degree:MasterType:Thesis
Country:ChinaCandidate:X H YueFull Text:PDF
GTID:2132360245996353Subject:Power system and its automation
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In the operation of power system, voltage and reactive power optimization is one of the key issues and an important means for power resources configuration and improvement of system security and economic profit. It plays an important role in modern Energy Management System (EMS). This dissertation discusses the voltage and reactive power optimization algorithm, and its practicability and application scheme. The research includes following contents:1. Distributed parallel reactive power optimization algorithm based on sub-area division of the power systems. For the single objective optimization, the decomposition and coordination method is adopted to build the decomposition and coordination model according to the existing sub-area division conditions of power networks. Then using the Augmented Lagrange method, the minimization problem of decomposition and coordination model can be changed to the saddle point problem of augmented Lagrangian function. Finally, the so called auxiliary problem principle (APP) is selected to decompose variables as well as the functions. This transforms the voltage and reactive optimization problem of the whole networks to some sub-problems in some sub-areas. As for the multi-objective reactive power optimization, the decomposition and coordination method is conducted to change the original problem into some related multi-objective optimization sub-problems in some sub-areas. Then trapezoid fuzzy membership functions are used to process every object. The multi-objective voltage and reactive power optimization problem of each sub-area, is reformulated as a single objective problem, which is to maximize minimal membership of the object functions. The multi-area multi-objective distributed parallel optimization can be concluded due to the integration of the sub-objects. The auxiliary problem principle decomposes the primal problem into several sub-problems solving parallel which reduces the size and complexity of the optimization problem and establishes a frame for distributed and parallel optimization. Each sub-area has its self determination to choose the optimization algorithm for its own area. This dissertation uses the direct nonlinear primal-dual interior point algorithm.2. The consistency formulation of global reference bus angle in the multi-area distributed and parallel reactive power optimization. When the decomposition-coordination model and Auxiliary Problem Principle are used in the distributed and parallel reactive power optimization, local reference bus angles are introduced, and multi-reference buses are brought out in the whole power system. In order to make the optimization results accord with the need of global optimization, it is necessary to coordinate the multi-reference buses of sub-areas and make only one real reference bus in the whole power system. By finding the relationship between the local bus angle, global bus angle and local reference bus angle, the consistency problem of reference bus angle is solved. The APP is employed to separate the local variables and the local reference bus angle.3. The distributed and parallel reactive power optimization algorithm based on sub-area division of the power systems is combined with the multi-agent technology according to its characteristics. The multi-agent system based distributed voltage and reactive power system is discussed in this dissertation. The multi-agent system is of hierarchical and distributed structure. The functions and operation mechanism are introduced. Some instructive work about the multi-agent system based distributed voltage and reactive power system in this dissertation lays a foundation for further research and discussion in this aspect.
Keywords/Search Tags:distributed and parallel optimization, voltage and reactive power optimization, decomposition and coordination method, auxiliary problem principle, multi-agent technology
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