Research On Multi-source Peak Regulation Mechanism And Game Strategy Of High Proportion Renewable Energy Grid

With the rapid development of renewable energy around the world,the new power system based on high proportion of renewable energy has gradually become the main force of development.The optimal dispatching technology and trading mode of its power system are the necessary conditions for building a new generation of power system with renewable energy as the core,and also a powerful tool to realize the complementary utilization of multiple energy sources between regions.In terms of improving the peak-shaving capacity of the regional power grid and improving the problem of large peak-valley difference,the optimal dispatching technology and trading mode of electric power will play a role.In this context,it is of great significance to study the multi-source peak shaving mechanism and game strategy for a high proportion of renewable energy grids.Firstly,this thesis studies the basic theory of multi-source peak shaving mechanism and game strategy,analyzes the different characteristics of day ahead dispatching and real-time dispatching according to the different characteristics of power grid operation dispatching,and determines the multi-source joint peak shaving dispatching system of high proportion renewable energy grid based on day ahead dispatching.The cost model of each type of power supply and the power characteristic model of the DC tie line are established.Based on the cooperative game,the allocation strategy of the cooperative game is analyzed,and the benefit allocation method based on the overall cooperation of regional multi-source entities is determined.Secondly,the regional multi-source peak shaving mechanism for high proportion of renewable energy access is designed,and the DC tie line is introduced into the multi-source peak shaving mechanism for high proportion of renewable energy access.The two regions are connected through tie lines.As a whole region,the economic model of regional multi-source peak shaving scheduling considering high proportion of renewable energy access is established with the goal of minimizing the total cost of peak shaving of the system.The CPLEX solver in MATLAB is used to solve the dispatching economic model,and the dispatching results,economy and unit operation of the individual dispatching scheme and the overall joint dispatching scheme are compared.The calculation example shows that the combined operation of peak-shaving dispatching has promoted the significant consumption of wind power,reduced the operating cost of the system,and improved the utilization rate of high proportion of renewable energy while ensuring the economy.Finally,a regional multi-source game strategy of high proportion of renewable energy access is proposed.Considering the impact of high proportion of renewable energy access on the operation and power supply capacity of regional power grids and the increasing gap in benefit distribution,based on the idea of cooperative game,a game alliance is designed with two regional power grids as the main body,wind power,pumped storage power stations and power grid companies in a single region.Under the framework of collaborative cooperation,determine its regional multi source peak shaving benefit allocation strategy.Based on the characteristics of regional power grids,analyze the applicability of the improved Shapley model to regional multi source joint peak shaving benefit allocation,establish a revenue model for multiple power sources,and on this basis,construct a benefit allocation model based on the improved Shapley.The calculation example shows that the benefit distribution strategy is applied to two regional power grids,and the results and economy of the benefits of each subject of joint operation before and after allocation are compared and analyzed.The benefit distribution strategy can effectively ensure the economy of all types of units,alleviate the low peak shaving income of some units,ensure the maximum benefit,and promote the fairness of benefit distribution.