Research On Reactive Power Optimization Of Power Market Based On The Advanced Immune Algorithm

The reactive power optimization is essential for power system operating safely andeconomically. With developing of power market, refresh of reactive power optimization areneeded. The paper studies on reactive power optimization of power market based on theImmune Algorithm, which includes: fixing a price of reactive power optimization, creatinga 5 node system to emulational calculating. The result shows that the price accord the ruleof power market, and it also can incarnate the value of reactive power. According toreactive power price, the model of unilateral dynamic price reactive power optimizationbased on real-time price is given. The model can indicate the all-around benefits effectively.Compared with GA, Simulant Anneal, and Tabu searching, we found that all theseintellective algorithms have weakness, just like tend running into partial searching.Immune Algorithm can avoid these problems effectively and enhance the ability ofsearching best solution. Through the merge application on Multi-colony ImmuneAlgorithm, Diploid Immune Algorithm; and Self-Adaptive Immune Algorithm, we bringforward a new Immune Algorithm; we called it Advanced Immune Algorithm (AIA). Itimproves on some aspect. The new Immune Algorithm is used to find best solution of themodel of dynamic price reactive power optimization which mentioned before. The steps ofthe process of AIA is given on the paper in detail, and realized by C++. Finally, we provecorrectness and effectiveness of the proposed model and algorithm by the solution of aIEEE-30 system compared with GA, IA and AIA.