Research On Power Grid Expansion Planning Based On Hybrid Algorithm

With the development of society,all walks of life more and more demand for electricity,the urgent need to expand the existing power grid capacity,expansion and construction of power grid has become an important work.The development of power system,power grid increasingly large scale,improve the power system planning has become an urgent task,many experts and scholars have made in-depth research on power grid planning,but in practical application,there are still many problems.The modern heuristic algorithm because of these problems in the development of power grid planning constraints on by some obstacles,to establish a complete mathematical model accords with the actual problem is impossible,only by simplifying the model and the uncertain factors to ignore,the optimal solutions to the problem of talent.Although the modern heuristic algorithm in power network planning problem has been widely used,but it is found that the modern heuristic algorithm still has some defects.Study on the improvement of performance and the algorithm research of many scholars in recent years are also committed to setting the parameters of the algorithm.Based on the research of genetic algorithm and ant colony algorithm and simulated annealing algorithm,a detailed analysis of the advantages and disadvantages of the three algorithms,a three algorithm fusion of the genetic simulated ant colony algorithm is designed,and its application in power network planning.In this paper,the mathematical model of single stage planning.The use of DC power flow calculation and the adjacent matrix of network connectivity judgment based on early in the algorithm eliminate some of the invalid solution,to improve the efficiency of genetic algorithm.According to the power grid planning and initial operation cost is much lower than the cost of the construction characteristics,the objective function is simplified by the objective function for the expansion of the length of the shortest line.In a typical IEEE18 system,respectively,genetic algorithm,ant colony algorithm and hybrid algorithm applied to power grid planning problems,the results of the three algorithms of planning results were analyzed and compared,which prove that the proposed algorithm is better than the other two algorithms.The design of the hybrid algorithm using simulated annealing algorithm to select elite individuals,to overcome the adverse effects of genetic algorithms in the selection operation on the roulette wheel method,the best individual is not completely copied to the next generation of shortcomings;optimization algorithm using pre computed solutions of initial information generation ant colony algorithm overcomes the shortcomings of ant colony distribution lack of initial pheromone algorithm efficiency and genetic algorithm to search in the search to a certain stage,will produce a large number of redundant iteration,the optimal solution to the disadvantage of low efficiency of search.A hybrid algorithm of genetic algorithm and ant colony algorithm expands the searching space and improve the speed of global optimization.The design of the hybrid algorithm is applied to the IEEE18 node in the system planning results is the optimal solution.