Research On Cross-regional Consumption Of Renewable Energy With Consideration Of Time Series Correlation Between Renewable Energy And Load

General secretary Xi Jinping,at the ninth meeting of the Central Committee of Finance and Economics,emphasized the need to build a new power system with new energy as the main body,which means that renewable energy power generation will replace traditional thermal power generation as the main energy source.During the 13 th Five Year Plan period,the average annual increase of wind power and photovoltaic power installed capacity in China was about 72 million kilowatts.With the continuous increase of renewable energy grid capacity,renewable energy output exceeds the regulation range of the system,resulting in the abandonment of renewable energy.The randomness and volatility of renewable energy also affect the safe and stable operation of the power grid.Renewable energy installed capacity and load in China are in reverse distribution,and the renewable energy consumption conditions in some areas are insufficient.Therefore,cross-provincial and cross-regional transactions are currently an important way to consume renewable energy.This paper mainly focuses on cross-regional consumption methods and strategies of renewable energy.The main research contents are as follows:(1)This paper analyzes the basic principles and influencing factors of renewable energy consumption.Combined with load characteristics and renewable energy power generation characteristics,we expound the influence of renewable energy output at receiving end on cross-regional consumption of renewable energy,which make a stable theoretical foundation for the subsequent establishment of cross-regional consumption model of renewable energy.(2)Taking the whole year as the time scale,the constraints of system operation,unit operation,renewable energy output,power grid security and DC tie-line operation are considered.Then,a cross-regional consumption model targeting with renewable energy maximization is established based on time series simulation method.A cross-regional system example reconstructed from the actual data in China is used to verify the validity of the model.Compared with the renewable energy consumption results of typical daily method,the practicability and accuracy of time series simulation method are verified.(3)In order to reflect the time series coordination characteristics of power grid dispatching and operation plan,a cross-regional short-term consumption model of renewable energy is established.Then,combined with the previous model,the cross-regional consumption strategy of renewable energy under multi-time scales is proposed in four stages: long-term,medium-term,short-term and real-time.Firstly,the equivalent operation model of DC line is constructed to reflect DC tie-line operation constraints accurately,then the cross-regional day-ahead consumption model of renewable energy is established.Secondly,based on this,the transmission power adjustment plan on DC line is put forward,then the cross-regional intra-day consumption model of renewable energy is established.Finally,based on the typical daily data of power grid,four optimization methods are proposed to compare and analyze the results of renewable energy consumption,which verifies the validity of the equivalent operation model of DC line and cross-regional short-term consumption model of renewable energy.(4)On the basis of the above research,in order to describe the renewable energy output characteristics more accurately,a scenario clustering model of daily power generation of renewable energy is established to evaluate the consumption capacity of renewable energy at single area,which takes account of the time series correlation between power source and load.Firstly,the typical daily load curve is divided into three periods: peak load period,medium load period and low load period.Based on this,the evaluating index system and calculating method of the time series correlation between power source and load are proposed.Secondly,the improved k-means algorithm is used to cluster the daily output curve of renewable energy,and the scenario reduction technology based on KD distance is used to obtain the representative scenario of renewable energy output.Finally,the shape characteristics and change trends of the representative scene are analyzed.Then,the renewable energy consumption results are compared with the results of time sequence simulation method,which verifies the necessity of considering the time series correlation between power source and load.(5)In order to further reduce the data and result deviation caused by the uncertainty of renewable energy output,combined with the evaluation index and clustering model in the previous paper,a renewable energy consumption model based on discrete probability distribution is established to evaluate the consumption capacity of renewable energy at two areas.Firstly,the Spearman correlation coefficient is used to calculate the correlation of renewable energy output and load between sending ends and receiving ends.Then,the scenario characteristic indexes set of cross-regional renewable energy output is established.Secondly,based on the improved Monte Carlo method,the probabilistic optimal power flow model targeting with abandoned power minimization of renewable energy is established,which consider the constraints of multiple scenarios.Finally,the correlation and complementarity of the typical representative scenarios of renewable energy output and load at two areas are analyzed.The prime-dual interior point method is used to calculate the consumption index of renewable energy,and the results are compared with time series simulation method,typical daily method and average method.The practicability of considering the correlation of renewable energy output in cross-regional system and the validity of the model are verified.The main results of this paper provide a theoretical reference for the dispatching department to study renewable energy consumption evaluation method and formulate the cross-regional consumption strategy of renewable energy.It is helpful to improve the cross-regional consumption capacity of areas with high proportion of renewable energy in the new power market environment.At the same time,it can be used to guide the power grid planning and operation,and ensure the safe and stable operation of the system.