Research On Power System Distributed Voltage/Var Optimization And Control

Voltage and reactive power optimization is an important means for power resources configuration and improvement of system security and economic profit. This dissertation discusses the voltage and reactive power optimization algorithm, and its practicability and application scheme. To overcome the shortcomings of existing algorithms, the distributed parallel reactive power optimization algorithm based on sub-area division of the power systems is proposed according to the distributed and decentralized characteristics of the power system. Here, multi-objective function and soft constraints are modeled using fuzzy sets, and the multi-objective reactive power optimization problem is solved by the direct nonlinear primal-dual interior point algorithm. Combined above methods with the multi-agent technology, a multi-agent system based distributed voltage and reactive power system is proposed. The research includes following contents:1. Distributed parallel reactive power optimization algorithm based on sub-area division of the power systems. The merits and shortcomings of the existing optimization algorithms are summarized. According to these summarizations, optimization algorithm is required to be adaptive to the distributed and decentralized characteristics of power systems, thus leads to a fast convergence property, minimum data transfer and easy application. So the sub-area division based distributed and parallel reactive power optimization is proposed for the above requirements. 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 wholenetworks 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 the above single objective method is used to deal with each sub-object. The multi-area multi-objective distributed parallel optimization can be concluded due to the integration of the sub-objects. The auxiliary problem principle establishes a frame for distributed and parallel optimization, and each sub-area has its self-determination to choose the optimization algorithm for its own area. This algorithm decomposes the primal problem into several sub-problems solving parallel which reduces the size and complexity of the optimization problem. Simulation results show that this algorithm is effective with faster convergence property and less data transfer than other algorithms.2. Trapezoid fuzzy membership functions are used to process every object. Then 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. Using the direct nonlinear primal-dual interior point algorithm, the single objective problem can be solved The way of solving the multi-objective reactive power optimization of a sub-area with fuzzy sets theory and interior point algorithm is deduced in detail here.3. The practical application research of the distributed parallel reactive power optimization algorithm based on sub-area division of the power systems is studied in this dissertation.(1) As the local reference bus is defined in each sub-area in the algorithm, 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. A—variable idea is introduced to solve this problem. Here, every bus voltage phase is a A—variable which can be expressed by the local phase plus the local reference phase. The new iteration formulae of auxiliary problemprinciple are deduced with new kernel function constructed in the light of this idea.(2) The soft constraints of optimization problem are handled with fuzzy sets in the dissertation. Firstly all the constraints variables are classified. Secondly soft constraints are modeled with trapezoid fuzzy membership functions. Then slack variables are introduced to transform the inequality constraints into equation ones. Thirdly the non-negative restrictions with respect to the slack variables are eliminated by the logarithm barrier functions. Last the new optimization model is solved by direct nonlinear primal-dual interior point algorithm. As for the discrete control variables, a fictitious cost function created by quadratic penalty function is appended to the original objective function. In order to handle the discrete variables effectively and prevent them from converging at some local optimal solution, the discrete control variables are treated as continuous ones in early iterations in the optimization process. When the binding inequality constraints are essentially determined and the changes of the discrete variables in two consecutive iterations are less than a given tolerance in late iterations, a quadratic penalty function should be introduced to drive the discrete variables toward their neighborhood centers.4. The distributed and parallel reactive power optimization algorithm based on sub-area division of the power systems is firstly combined with the multi-agent technology according to its characteristics. The multi-agent system based distributed voltage and reactive power system is proposed in this dissertation. On one hand, The distributed and parallel characteristic of the algorithm is suitable for multi-agent system, On the other hand, the multi-agent technology can coordinate the decentralized logical or physical systems to solve a problem in parallel. The multi-agent system provides a flexible intelligent platform for application of the algorithm. The multi-agent system proposed in this dissertation is of hierachical and distributed structure. The functions and operation mechanism are introduced. The two-level scheme is put forward for power system secondary voltage contingency control. Several key problems in practical applications are also discussed. Some instructive work about the multi-agent system based distributed voltage and reactive...