Research On The Algorithms And Applications Of Optimal Power Flow Based On Interior Point Theory

Electrical power industry is an important basic industry of national economy and its development is closely related to the national economy and the people's living. Scholars have been dedicated to improving and optimizing the operating efficiency of power system so as to build a resource thrift and environment friendly society. As the increase of pressure on resources and environment and the development of power marketing course, power industry is facing the unprecedented opportunity and the challenge. To build a secure, reliable and economic power system, application of new management method and technology is the goal of power industry all around the world. Optimal power flow (OPF), as an indispensable analysis and pricing tool, is now playing more and more role in the current electricity markets environment. Among most optimization methods for OPF, interior point methods (IPMs) have enjoyed increasing popularity. The most attractive features of IPM are its speed of convergence and its robust capability of handling equality and inequality constraints; making itself a practical tool for solving large-scale optimization problems.Based on the research of primal-dual interior point methods, This dissertion brings forward the corresponding improvement algorithms in allusion to the insufficient of primal-dual corrector IPM, multiple predictor-corrector IPM and multiple centrality-corrector IPM. In addition, the dissertion also discusses the issues of the accuracy of linear programming method, the computation and decomposition of the locational marginal price with considering the composite load model and the the effect of connected wind farm on the power system optimal operation. The main contents and contributions of this dissertation are summarized as follows: (1)Primal-dual corrector interior point method (PDC-IPM) is applied to solve the optimal power flow (OPF) problem. To avoid the adverse effect of the corrector on the performance of this method, a primal-dual corrector IPM based on a filter is proposed. This algorithm combine Primal-dual corrector interior point method and filter method and design an appropriate filter criteria, which can effectively shield the adverse effect of the corrector by filter and then improve the convergence property of the PDC-IPM.(2)A weighted multiple predictor-corrector interior point method is proposed by means of the weighted corrector applied to multiple predictor corrector IPM (MPC-IPM). A two stage line-search strategy is also employed to obtain the approximate optimal composite direction to improve the convergence property of the proposed algorithm. Simulation results on test systems show that the proposed algorithm has a great advantage in the iteration times and computation time when cpmpared with predictor-corrector IPM and its variants.(3)An improved multiple centrality corrector interior point method is putted forward. The proposed algorithm combines effectively the predictor corrector and centrality correction methods, which use the predictor corrector direction after line search as the affine direction of centrality correction in order to improve the convergent features of multiple centrality corrector interior point method. Numerical results demonstrate that robustness of the proposed algorithm is strengthened. Moreover, compared with traditional high order interior point methods, the proposed algorithm has a great advantage in iteration times and calculating time.(4)Inaccuracy of OPF solution obtained by linear programming method is studied in this paper. A linear programming method is presented, which is widely used to solve optimization problem in power systems. This method applies the successive linear programming technique to convert the solution of nonlinear OPF problem into finding the solution of a series of linear sub-problem with linear step size constraint. Moreover, the Trust-Tech method is used to obtain an initial feasible point and weighted multiple predictor-corrector interior point method is then employed to calculate each linear sub-problem. By comparing the linear and nonlinear calculation results, the paper analyze the accuracy problem of linear programming method when it is used to solve OPF problem under various load conditions.(5)A new OPF formulation, which includes ZIP and induction motor load models, has been presented along with an improved LMP decomposition model. This proposed decomposition model overcomes the disadvantage of conventional decomposition model and can effectively decompose LMP into its three components when composite load models are considered in the OPF calculation. Base on the simulation calculation of two test systems under different load conditions and different load models, the paper verify the efficiency of the proposed decomposition method and analyze the effect of load model on LMPs and on its decomposition under different load conditions.(6)With the increasing impact of connected wind farm on the power system operation, this dissertation develops an optimal power flow model to research the effect of wind farm on the optimal operation of power system. Both the stable model of fixed speed wind generator and the added reserve caused by the uncertainty of wind powr generation are considered in this model. In order to make this model become more reasonable, the cost of wind power generation is added into the objective function and the real output of wind power generator is dealed with a control variable. A quadratic penalty function with variable penalty is employed to realize successive discretization of the discrete control variables in optimization process. The IEEE 118 system is used to analyze the effect of connected wind farm on the power system operation and verify the rationality of proposed optimal power flow model and the validity of proposed algorithm.