Advanced wattless power compensation method of power transformation engineering

Abstract

The invention discloses an advanced wattless power compensation method of power transformation engineering and relates to the power distribution engineering field. The advanced wattless power compensation method includes the following ten steps of initialization, coding, power flow calculation, fitness value calculation, selection operation, crossover operation, mutation operation, local optimal judgment, catastrophe strategy execution and termination criteria execution. The method is an improved type power grid wattless power optimization compensation method based on a genetic algorithm. According to the method, the selection operation, the crossover operation and the mutation operation are further improved, and therefore, premature convergence of the algorithm to obtain a local optimal solution can be avoided, and convergence can be speeded up; and the defect of proneness to falling into a dead cycle by using a heuristic method can be eliminated. With the advanced wattless power compensation method adopted, the difficulty to obtain an optimal solution can be greatly decreased; guarantee can be provided for the execution of the algorithm; active power loss of a power grid system can be effectively decreased; the time of iteration is short, and the frequency of the iteration is low; and efficiency is high.

Description

technical field [0001] The invention relates to the field of power distribution engineering, in particular to an advanced reactive power compensation method for power substation engineering. Background technique [0002] In recent years, my country's electric power industry has developed rapidly. With the advancement of science and technology, the improvement of people's living standards and the rapid development of the national economy, the power grid is developing in the direction of ultra-high voltage, long transmission distance and increasing capacity. The modern power system requires its operation to be both economical and safe, because of its large-scale construction, complex construction structure, and higher and higher voltage level requirements. If there is an accident in the operation of the power system, it will cause immeasurable losses to the economy and safety of our country. The application number is CN201010281582.7, which discloses a reactive power optimizat...

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Problems solved by technology

If there is an accident in the operation of the power system, it will cause immeasurable losses to the economy and safety of our country. The application number is CN201010281582.7, which discloses a reactive power optimization method for enterprise distribution networks based on genetic algorithms, including the following Steps: (1) Establish a reactive power optimization model of the enterprise distribution network; (2) Determine the final reactive power optimization point to be compensated for the enterprise distribution network; (3) Compensate the compensation capacitance, The transformation ratio of the transformer and the terminal voltage of the generator are chromosomally coded to form an initial population; (4) Calculate the fitness value of the individual in the initial population that meets the constraint test; (5) According to the fitness value of each individual in the initial population Values ​​are selected, adaptively crossed and mutated to generate a new generation of population; (6) If the maximum fitness value of individuals in the new generation population and the maximum fitness value of individuals in the previous generation population satisfy the relation Then, the chromosome decoding is performed on the individual with the largest fitness value in the new generation population, and the reactive power optimization result of the enterprise distribution network model is obtained and output; otherwise, return to the execution step (4). The inventive method has a fast calculation speed and strong versatility. It has high theoretical significance and application value for the reactive power optimization of the enterprise distribution network, but this method does not effectively reduce the active network loss of the power grid system, and the iteration time and times of the algorithm have not improved much, and the efficiency is not high

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