Dispatching Optimization Method For Distribution Network With Renewable Energy

As a source of power for human production and life,fossil energy such as coal,oil and natural gas is decreasing with the greed of people.Human beings are facing not only the energy crisis caused by the depletion of fossil energy,but also the great pollution of the environment on which human beings depend.In order to solve the problem of energy crisis and environmental pollution,people devote themselves to the research of new energy power generation,hoping to replace traditional fossil energy with clean energy such as wind power and photo electricity.With the vigorous support of national policy and the unremitting efforts of experts and scholars,the technology of new energy power generation is becoming more and more mature,and its share in the distribution network is growing.Because of the remarkable periodicity and randomness of new energy generation,its large number of access to the grid will bring great challenges to the stable operation of the grid.How to optimize the dispatch of distribution network to improve the ability of distribution network to absorb new energy has become an urgent problem to be solved.In this paper,a series of research on the scheduling optimization method of source-network-load distribution network is carried out,and a stochastic chance-constrained programming method is proposed to deal with the stochastic problem of distribution network with new energy sources.A stochastic chance-constrained model of "source-network-load" distribution network is established.Because the complex stochastic chance-constrained model can not be transformed into a deterministic model,an intelligent algorithm combining stochastic simulation and genetic algorithm is adopted to solve the problem.In order to improve the ability of distribution network to absorb new energy sources,an energy storage system is proposed to be connected to the distribution network to form a "source-network-load-storage" distribution network.Aiming at the uncertainty of power supply and load in distribution network,a fuzzy programming model of "source-network-load-storage" distribution network is established by using the method of fuzzy programming.Because the complex fuzzy programming model cannot transform it into a deterministic model,a genetic algorithm based on fuzzy simulation is used to solve the problem.Because electric vehicles do not need to burn gasoline and have the characteristics of zero pollution and zero emission,the market of electric vehicles has been vigorously developed with the support of national policies.With the popularity of electric vehicles in life,its large-scale disorderly charging will affect the stable operation of the power grid.It is necessary to incorporate electric vehicles into distribution network dispatching.Therefore,a dispatching optimization method of "source-network-load-storage-vehicle" distribution network is proposed.In order to solve this problem,the method of fuzzy random chance constrained programming is proposed to establish the optimal dispatching model of "source-network-load-storage-vehicle" distribution network,because the output and load of each power supply often contain both fuzziness and randomness.The fuzzy optimization model,neural network and multi-objective genetic algorithm are used to solve the scheduling optimization model.Finally,the model and solution method are validated by using the IEEE-33 bus distribution network system.