Study On The Power System Scheduling Scheme To Improve The Capacity Of Wind-Solar Absorption

For a long time,traditional power industry conducts power generation scheduling based on fossil energy,such as coal,oil and natural gas.Renewables such as wind,photovoltaic and hydropower account for a smaller proportion of power generation.However,with the gradual maturity of power generation technology,climate warming,environmental pollution and other issues are increasingly prominent,all countries in the world are in pursuit of low-carbon and environmentally friendly development mode.Our country is rich in scenery resources,large-scale development and utilization of these new energy sources for power generation can make the environment and energy problems be well solved.However,due to the intermittency and randomness of the output power of wind-solar power generation,part of wind power and photovoltaic power have to be abandoned for the stable and safe operation of the power grid,and the utilization rate of new energy will also be reduced accordingly.Therefore,under the condition of ensuring stable and safe operation of the system,how to absorb more new energy power generation and reduce wind and light abandoning is the research focus of new energy power generation in recent years.This paper firstly summarizes the characteristics and influencing factors of wind power and photovoltaic power generation,analyzes the status quo of power prediction,and measures to promote the consumption of new energy.Through the analysis of wind power and photovoltaic power generation models and influencing factors,it is learned that wind-solar power output has strong randomness and uncertainty.Then,according to the specific influencing factors of wind power and photovoltaic,different methods are adopted to predict the output power of wind power and photovoltaic.For wind power,since wind speed is the most important factor affecting the wind power output,the wind speed time series is adopted to predict the wind speed,and then the wind power output is predicted through the wind power output curve.For photovoltaic power generation,due to the periodicity of photovoltaic power generation,this paper adopted the method of optimal similarity day and combined with the neural network to predict the photovoltaic power output.Then,on the basis of scenery prediction,a power system scheduling model with scenery output is established,and different scheduling models are solved respectively with the maximum scenery consumption and the minimum operation cost of thermal power units as the objectives.In this paper,the improved particle swarm optimization(pso)algorithm is adopted to analyze the solution of the model.The output of each unit in different scheduling schemes is given,and the advantages of the improved pso algorithm are analyzed through the results.Finally,according to the analysis of the scheduling scheme,it is concluded that when only the thermal power unit is used to adjust the peak load,the absorbing capacity of wind-view will be affected to some extent.Therefore,through the analysis of the energy storage device,the wind-view storage combined scheduling model containing the energy storage device is established in this paper.Taking the maximum wind-solar dissipation and the minimum operating cost of thermal power units as the objective function to solve the problem,the improved particle swarm optimization(pso)algorithm was adopted,and the results were compared with the scheduling results without energy storage devices.And on the basis of the single objective solution,considering the joint optimization of the two objectives,the improved MOPSO algorithm was used to solve the problem.The results of the joint optimization and the single objective optimization were analyzed,indicating that the results of the multi-objective joint optimization can better provide theoretical support for the power system scheduling.