Research On Multi-objective Dynamic Optimal Dispatch Of Large-scale Power Systems Considering Wind Power Integration

With energy and environmental issues becoming more prominent, renewable energy suchas wind power has been developing rapidly and more and more wind power has integratedinto the power grid. However, the intermittence and randomness of wind power has adverseeffect on generator optimal dispatch of power systems. Multi-objective dynamic optimal dis-patch considering economic and environmental protection of large-scale power systems withwind power integration is analyzed in this dissertation.A multi-objective dynamic optimal dispatch model aiming at minimizing fuel consump-tion, emission of atmospheric pollutants and power purchase of large-scale power systemsconsidering wind power integration is proposed. In this model, the up/down spinning reserveconstraints are introduced to deal with the randomness of wind power, and the influence ofactual operation characteristics of pumped storage generator units on optimal dispatch is takeninto account. At last, the wind power is modified in order to make the maximum use of windpower on condition that the conventional unit could provide the needed reserve capacity toensure system reliability.Normal boundary intersection (NBI) method and prime-dual interior point method areused to solve the model. Firstly, NBI method is introduced to transform this multi-objectiveproblem into a series of single objective optimization problems, and hence a series of uniformdistributed Pareto optimal sets are obtained by means of the prime-dual interior point method.Secondly, entropy-weighted double base points method is applied to get a comprehensive op-timal solution to provide a guidance decision for operators. At last, computational results on areal provincial power system demonstrate that the multi-objective dynamic optimal dispatchproblem can be solved efficiently based on combining NBI method,prime-dual interior pointmethod and entropy-weighted double base points method and the comprehensive optimal so-lution that obtained has a higher overall benefit of the above three objectives.It takes a lot of time to obtain the Pareto optimal sets for large-scale power systems withthe above algorithm because of the large-scale model and high-dimension matrix. In order toimprove the computing speed, a multi-objective decomposition algorithm and parallel compu-ting based on NBI method and prime-dual interior point method is proposed. The proposedalgorithm transforms a multi-objective optimization problem into a series of single objectiveoptimization problems based on NBI method, and decouples static and dynamic variables bydecoupling and reducing these single objective optimization problems’ correction equationsbased on the special structure of their coefficient matrices. Finally, a series of uniform distrib- uted Pareto optimal sets are obtained rapidly using the parallel computing technique conduct-ed by Matlab parallel computing platform. Computational results on a real provincial powersystem demonstrate that the Pareto optimal sets to the multi-objective dynamic optimal dis-patch problem can be obtained rapidly and efficiently using the proposed algorithm which isof great practical value.