Economic Optimal Scheduling Of Microgrid Considering Uncertainty Of Wind Power Photovoltaic Output

With the continuous development of human society and the increasing urgency of energy demand,on the one hand,the application of high-permeability renewable energy systems is the general trend,and the diversified power generation model has played a significant role in changing the energy framework.On the other hand,the large amount of renewable energy has also brought huge challenges to the optimal scheduling of power systems.In recent years,the micro grid system,which is mainly based on wind power and photovoltaic power generation,has been greatly developed at home and abroad.However,more and more power system problems have emerged.Affected by environmental factors,wind power and photovoltaic output have strong volatility and uncertainty.Therefore,whether it is a grid-connected or off-grid power generation model,there are no small challenges to the safety and reliability of load power in the power system,and it also reduces the ability to absorb renewable energy,which is not good for renewable energy The promotion and development of power generation,while also reducing the economics of optimal dispatching of power systems.Therefore,predicting the output of wind and photovoltaic can be able to energy dispatch reasonably and then prepare a power consumption coordination plan in advance,which is conducive to maintaining the safety and reliability of power system operation.On this basis,optimizing the dispatch strategy is conducive to improving the economics of system operation,reducing the cost of power generation and improving the quality of power consumption.Therefore,it is of great significance for the future power system security,stable operation and new energy promotion to study the renewable energy generation prediction and optimization of system energy scheduling.Aiming at the problems of power forecast and dispatch,this paper researches and summarizes many related literatures at home and abroad.Based on the research that has been done,a new forecasting algorithm is proposed to improve the accuracy of power forecast,and multiple algorithms are used to combine forecasting methods.Analysis of prediction errors based on improved accuracy,and considering the uncertainty of wind and solar power output,a grid-connected model of wind and solar storage combined operation in microgrid is established,then an intelligent optimization algorithm is used to optimize the energy scheduling problem so that the economic cost of microgrid operation is optimal.Based on the above issues,the main research results of this article are as follows:Firstly,considering the adverse impact of wind power photovoltaic output uncertainty on the power system,a combination forecasting algorithm model is proposed.Based on the existing empirical modal decomposition algorithm model,it conducts in-depth research on it and uses the advantages of this method to decompose the original power generation data into multiple intrinsic mode function with stationary characteristics.And then using the autoregressive moving average algorithm to analyze the decomposed components,and training the data to establish a more accurate autoregressive moving average model.It reconstruct the obtained prediction components to obtain the final forecast data of winde and photovoltaic output.The feasibility of the model is verified by simulation experiments,and the calculation of model prediction indicators shows that the proposed method effectively improves the accuracy of wind and photovoltaic output prediction.Secondly,on the basis of improving the prediction accuracy of wind-solar power generation,the prediction error and wind-solar output characteristics are analyzed.By analyzing the mathematical model of wind-solar power generation,it is beneficial to take corresponding measures to improve its output uncertainty and other issues.By further analyzing the output characteristics of the wind and photovoltaic power data in this paper and describing the prediction error of the wind-solar hybrid output model with a probability function,the power system stability to deal with the uncertainty of renewable energy output can be effectively improved.It also provides theoretical support for the microgrid grid-connected dispatching system that takes into account the uncertainty of renewable energy output in the next chapter.Finally,considering the problem that the uncertainty of new energy power generation and other factors,a large number of wind-solar power generation scenarios are generated using the normal distribution function.In order to reduce the complexity of the model,eliminating similar and small probability output scenarios.Establish a hybrid grid-connected model,with the target of thermal power output cost and operating cost of energy storage in the microgrid when the microgrid interacts with the grid.Considering that the main cost of the gird system is targeted because the improved particle swarm algorithm is mainly used to optimize the output timing and power generation of thermal power units,the charging and discharging timing of energy storage systems,and the power of charging and discharging.Considering many constraints simultaneously,intelligent algorithms are used to optimize the scheduling so that the system can operate economically.In the last,a case study can confirm the rationality of the model,the feasibility and economics of the method.