Research On Economic Optimal Scheduling Of Virtual Power Plant Based On Improved Pigeon Swarm Algorithm

Energy of nature is provided by energy,and human production and life are closely related to energy.At the present stage,the green and efficient development of energy and how to get along with energy development and environmental protection are issues that all countries in the world,and even the entire human society,are concerned about.For a long time,traditional fossil energy has been the main form of energy utilization in the world,but its reserves are limited,and to a certain extent,it has caused irreversible damage to the environment.Therefore,clean energy has received extensive attention from all walks of life.Among them,distributed energy has been favored by scholars at home and abroad because of its clean and environmentally friendly characteristics,and has achieved strong development.In order to improve the utilization efficiency of distributed energy,virtual power plants have entered people’s field of vision.Virtual power plants can effectively alleviate the impact of the grid connection of distributed energy on the safe and stable operation of the power grid,and while improving the ability to absorb distributed energy,it can also improve the economy of the system to a certain extent.Therefore,how to use virtual power plants to reduce the impact of grid-connected distributed power has extremely important theoretical value and practical significance.The main research contents of this thesis are summarized as follows:(1)Aiming at the problem that the traditional pigeon flock algorithm is easy to fall into the local optimum,an improved pigeon flock algorithm with adaptive parameter adjustment is proposed.First,the working principle of the traditional pigeon flock algorithm is comprehensively introduced.Then,improve on the shortcomings of the algorithm.And a series of tests are carried out on the pigeon flock algorithm before and after the improvement through the test function,and it is verified that the proposed algorithm exhibits good convergence and stability when dealing with function optimization problems.(2)Aiming at the problem that the uncertainty of wind turbine output is not considered in the traditional virtual power plant optimization problem,chance-constrained programming theory is introduced to deal with this uncertainty,and a power system scheduling model considering the uncertainty of wind turbine output is established.Finally,using the improved pigeon swarm algorithm to solve the model.The calculation example results show that in the power system scheduling problem,by processing the uncertainty of wind power generation,it can not only enhance the reliability of the system operation,but also improve a certain economy.(3)Taking into account the uncertainty of wind power generation,in order to further improve the absorbing ability of distributed energy,a two-layer economic optimization model of virtual power plant is established,and the best access location for the involved distributed energy is determined.The upper-layer optimization model takes the minimum total power generation operation cost of the main grid as the optimization goal,determines the output of each unit,and takes it as the initial condition of the lower-layer optimization model.On the basis of the upper-layer optimization model,the lower-layer optimization model is optimized with the maximum economic benefit of the virtual power plant as the objective function,and the optimal solution that satisfies the lower-layer objective function is determined.The upper and lower models are iterated repeatedly through the improved pigeon flock algorithm to achieve double-layer optimization eventually.The simulation analysis of examples shows that the two-layer dispatching model can reduce pollution and realize the low-carbon,high-efficiency and safe operation of the power system while improving the consumption capacity of distributed energy.