New Power System Source Network Load Storage Collaborative Optimization Technology with Embedded Demand Response
In order to improve the complex diversity and stochastic uncertainty of parameters in the new power system source network load storage collaborative optimization technology,reduce the grid operation cost,and realize the balance of power consumption between the user side and the demand side,a new power system source network load storage collaborative optimi-zation with embedded demand response and technology is studied.Based on the new power system source network load storage structure,a user side demand response model including load resource and energy storage resource is constructed,which is con-venient to consider the user demand response to adjust the user side electricity consumption mode,so that the interruptible load is generated or the load is transferred to the demand side response.The objective function provides users with the lowest subsi-dy cost and the smallest system loss.Combined with the load side,energy storage equipment,controllable distributed power supply,and grid power balance constraints,a source network load storage collaborative optimization model is constructed,and the genetic algorithm is used to obtain the co-optimization result with the lowest demand response subsidy cost and the smallest system loss through the crossing and mutation operation.The experimental results show that under different scenarios,using the collaborative optimization of the method proposed in this paper,the thermal power output can be reduced,the wind power consumption space of the system can be increased,and the load from the period of high electricity price can be transferred to the low period.It improves wind power consumption space,improves power supply efficiency,and reduces cost losses and demand response costs.
万方数据
维普
