Research On Optimization Of Wind-photovoltaic-pumped Storage Combined Operation Based On Multiobjective Planning

At present,the problem of environmental pollution and fossil energy shortage is increasingly serious.In order to response the calling of "energy conservation and emission reduction,sustainable development".Using new energy is very important.The wind and solar power generation technology has been very mature.However,with the large-scale grid connection of wind power and photovoltaic power generation.The output volatility,instability of wind power generation and photovoltaic power generation have a more serious impact on the power grid,which will aggravate the phenomenon of wind power and photovoltaic power in the system.Therefore,To make full use of wind and solar power generation is an urgent problem.In order to alleviate the fluctuation of wind power generation and photovoltaic power generation,and reduce the impact on the grid when connected to the grid,According to the complementarity of wind power generation and photovoltaic power generation,then add the pumped storage power generation,they are regarded as a whole to form the wind power generation system.Firstly,the structure and working principle of wind turbine,photovoltaic array and pumped storage unit are introduced.This paper introduces the working principle of the wind energy extraction and storage combined power generation system.The multi-objective optimization problem and Pareto optimal solution set are introduced.The advantages and disadvantages of each intelligent algorithm are analyzed.In this paper,genetic algorithm is selected to solve the optimization problem,The genetic algorithm based on non dominated scheduling of competition mechanism(NSGA-2)is used to solve the optimal scheduling of combined power generation system and compared with the previous multi-objective particle swarm optimization(MOPSO).Then,for the equivalent load that the combined power generation system fails to bear,the thermal power unit is required to bear.The genetic algorithm(GA)is used to optimize the scheduling of thermal power unit.In order to maximize the benefit of grid connected power generation and track the change of load curve,the model is established.Considering the output constraints of each power generation system and the power balance constraints of the combined power generation system,the non dominated sequencing genetic algorithm(NSGA-2)based on competition mechanism is used to optimize the solution.The optimization results show that according to the established model,the combined generation system can track the changes of load curve well,at the same time,it can alleviate the output fluctuation of the combined system and reduce the impact on the power grid.Based on the results of optimal dispatching of wind turbine pumped storage combined power generation system,the equivalent load that needs to be regulated by thermal power unit is calculated by the output and daily load prediction data of the combined power generationsystem.Considering the output constraint,climbing constraint and rotating reserve of the unit,the day ahead optimal dispatching model of the power system with wind turbine pumped storage combined power generation system is established with the minimum coal consumption of the thermal power unit as the goal Type.Genetic algorithm is used to optimize the model.The optimized results show that the combined system can effectively reduce the regulation pressure of thermal power units after wind power generation and photovoltaic power generation are connected to the grid.