Study On Ant Colony Algorithm And It's Application To Electric Power System

Transmission network expansion planning is a very complex combination optimization problem,which is large-scale and nonlinear, and reasonable transmission system structure is the material foundation for the power system to operate with safety,reliable and economic circulation. With the growing scale of the grid, the dimension of the decision variable rapidly increasing,the planning problem is becoming increasingly complex. Comparing with the traditional methods,which of mathematical optimization calculate with more time and low efficiency,Ant Colony Algorithm is an efficient heuristic search technology to solve combinatorial optimization problems. It has strong robustness, well distributed calculate system,and easy to combine with other algorithm. Now it has been successfully used in many optimization problems.In this paper , the research situation of transmission network planning is introduced,and the existing methods of planning are summarized. The theory and the model of ant colony algorithm, as well as the specific implementation of ant colony algorithm are emphatically introduced. Meanwhile, it is analyzes of the advantages and disadvantages of Ant Colony Algorithm. We introduced and analyzed a number of improvements of existing algorithms (such as ant colony system (ACS), max-min ant system (MMAS) and so on). We improved the classical ACO based on the Ant Colony System (ACS), proposed a new local updating rule that make them more efficient and robust, while used the value of dynamicαand an adaptive strategy of pheromone. By those, the area of feasible solutions was expanded. This method is able to restrain stagnation during the iteration process effectively, and enhance the capability of search. We summed up the ant colony algorithm to improve the method.This paper presented a dynamic programming model to optimize the supply grid, the model takes into account "N-1"static security constrained the expansion of planning and the introduction of the "N-1" fault testing and fault sorting, greatly reduced the computer program for calculating the amount. At the same time, this article improved ant colony algorithm applied to the dynamic optimization of the planning grid, and IEEE-6 node system simulation has achieved satisfactory results.