Research On Multi-regional And Multi-objective Low-carbon Economic Dispatch Model And Method Considering Wind Power Uncertaint

Economic dispatch plays a significant role in the operation and planning of power systems,and is an essential cornerstone for safe,stable and economic operation of them.It is considered that all generators in the power system as a whole in an area.However,as the scale of power systems continues to expand,it is now common to divide large systems into multi-areas and realize the exchange and transmission of energy through the interconnection of tie lines between them.In addition,the previous dispatching mainly focused on the goal of economy,which was slightly single and lacked diversity,making it difficult to provide decision makers with a more comprehensive dispatch solution with multiple dimensions and levels.Therefore,the dispatch model is also progressing from traditional single-area to multi-area,and is evolving from single to multi-objective.In this paper,we mainly study the traditional economic dispatch,multi-area economic dispatch,multi-area dynamic economic dispatch with carbon tax and wind power uncertainty and multi-area multi-objective environmental economic dispatch,and the main research contents are as follows.1.The comprehensive learning particle swarm optimizer is improved based on several strategies such as forgetting velocity,and the FV-ICLPSO algorithm is proposed to overcome the shortcoming of slow convergence of the basic comprehensive learning particle swarm optimizer.It is first applied to 30 CEC2014 benchmark functions to verify the effectiveness and performance of the modified strategy,and then it is applied to six conventional economic dispatch cases with different characteristics together with six more advanced intelligent optimization algorithms proposed in recent years for simulation comparison to verify its effectiveness and applicability.2.Build the model of traditional multi-area economic dispatch,which adds the regional power balance constraint and the transmission capacity constraint of the tie line in addition to the constraints of traditional economic dispatch.Apply the proposed FV-ICLPSO algorithm to two typical multi-area economic dispatch cases,and finally verify the effectiveness of the algorithm and its feasibility for this type of model.3.In order to solve the problem of poor convergence of comprehensive learning particle swarm optimizer,based on a current research hotspot of fractional order theory,the enhanced optimizer learning particle swarm optimizer AFOCLPSO with fractional order theory and two-stage operation is proposed.considering carbon tax and grid connection of wind farms,the Monte Carlo method is used to generate massive wind power scenarios for backward a reduction to generate typical scenarios,and finally,a multi-area dynamic economic dispatch with carbon tax and wind power uncertainty is built.The proposed AFOCLPSO algorithm and several advanced comparison algorithms are simultaneously applied to two cases of this model,and the rationality of its improvement and the effectiveness of its solution are finally verified.4.A multi-area environmental economic dispatch model is constructed,and one of the most popular multi-objective optimization algorithms,NSGA-II,and four other multi-objective algorithms are applied to the 4-area 40-unit case together.Finally,the quality of the solution,performance evaluation index,Pareto front and computation time show that the algorithm is extremely competitive in solving this type of model,and it is worthy of subsequent attempts to improve and promote it.