Supply And Demand Side Joint Economic Dispatch Of Power System With Wind Farms Considering Flexible Load

The non-renewability of fossil energy and its contradiction with environmental demand have made more and more people pay attention to the development and utilization of new energy.As a representative of clean energy,wind energy has become the focus of new energy development and research.With the large-scale access of wind power,its randomness and uncertainty pose great challenges to the security and stability of traditional power grids.For the above characteristics of wind power resources,combined with dispatch of demand side,the joint dispatch of supply and demand sides with wind farms are studied:Firstly,the probability distribution function of load and wind speed prediction error is introduced to describe the uncertainty factor of the system,Then based on the flexible load excitation/compensation mechanism,the flexible load is introduced into the dynamic economic dispatch to participate in peak shaving,and the supply-demand side joint economic dispatching model with wind farm considering flexible load is established.In order to ensure the safety and reliability of the system,based on the chance constrained programming,the risk caused by the randomness of spinning reserve demand can not meet the actual wind power output and the negative charge fluctuation is estimated,thermal power unit output,wind power plan output,flexible load plan value and unit spinning reserve demand are optimized.For the solution of the above model,a Bi-strategy Co-evolution in Genetic Algorithm is proposed.Evolution is divided into elite population evolution and diversity population evolution through different selection strategies.Start-stop mutation operator is added to improve the efficiency of the algorithm furtherly.The simulation experiment is carried out.The comparative analysis shows that Bi-strategy Co-evolution in Genetic Algorithm effectively maintains the diversity of the population,and improves the optimization speed.The classical IEEE10 system is used as an example to study the simulation.Compared with the traditional genetic algorithm,the algorithm effectively guarantees the diversity of the population,and has certain improvements and improvements in the convergence speed and global search ability.The simulation results also verify feasibility and effectiveness of the proposed model.Then,based on the above model,the carbon emission is introduced into the objective function,and a multi-objective model of joint and dispatching of the supply and demand side with wind farm considering flexible load is established.The multi-objective model was solved using the NSGA-II.A multi-objective constrained optimization method is adopted,and the sum of its constraint violations is added as a target to the objective function.Based on the fuzzy satisfaction decision method of maximum satisfaction,the optimal compromise solution is selected in the Pareto optimal solution.Through the simulation experiment,the rationality and effectiveness of the model and algorithm are verified from the perspectives of economic and environmental benefit.