Research On The Total Transfer Capacity Based On Immune Genetic Algorithm

In the power system, fast and accurate calculation of the total transfer capacity isan effective way to ensure system security and economic operation, conducive to therational allocation of resources, improve resource utilization, also conducive to thefield of power generation combine with the market.Therefore, the study of powersystem total transfer capacity, has not only theoretical significance but also practicalvalue.This paper first summarizes the research status total transfer capacity, and thencalculates the total transfer capacity of several algorithms for a detailed descriptionand summary of the advantages and disadvantages. These algorithms have a pooraccuracy and low efficiency convergence. To solve these problems, this article usesthe immune genetic algorithm to calculate the total transfer capacity.this algorithmcan protect the diversity of individuals, can effectively strengthen the local searchability, have immunological memory function, can improve the search speed, aself-regulatory function, can improve the global search ability.The total transfer capacity of power system is a multi-variable, multi-constraintmixed nonlinear programming problem, the optimization process is quite complex.This article uses the sum of the load active power incremental as the objectivefunction to create a mathematical model, for the generator group with powerconstraints, node voltage constraints and inequality constraints problem, to join thepenalty function to make it the problem of to becomes no-constraint conditions.Programme studied optimization methods using MATLAB, functions of eachmodule of the program are described; the basic flow based on immune geneticalgorithm to calculate the total transfer capacity of the power system is given. In orderto verify the proposed in this paper the correctness of the model and algorithm. UsingIEEE-30node system as an example verifies the effectiveness of authentication, andcalculates the total transfer capacity of a grid line, the practicality of the proposedmethod was validated. Simulation results show that the total transfer capacity,immune genetic algorithm has stronger global optimization capability and fastercomputing speed and accuracy verified mathematical model and algorithm proposedin this study is practical, reliability and superior.