Low-Carbon Economic Dispatch Of Power System With Wind-Light Emitting Generation Based On Carbon Trade

Faced with the deterioration of the environment,wind and solar power generation as a clean energy has become a hot research topic.However,the uncertainty,fluctuation and reverse peak regulation of wind and solar power output bring great difficulties to the access of wind and solar power generation and the operation and dispatch of power grid.At the same time,the implementation of low-carbon emission reduction policy has received positive response from all countries in the world.The establishment of carbon trading market has gradually put the low-carbon economy on the right track of the times.Therefore,it is of practical significance to consider the access of wind and solar power generation and carbon trading in power system dispatching model.Firstly,this paper introduces the trading mechanism of carbon emission rights and the initial allocation scheme of carbon emission rights,and studies the dispatching mode of power system.Secondly,according to the impact of wind and solar power on power system dispatch,carbon quota of thermal power and wind and solar power generation system is redistributed based on the initial allocation of carbon quota,and a low-carbon economic dispatch model is established under the background of carbon trading,and genetic algorithm is used to solve the model.Finally,the uncertainty of load and wind power is analyzed based on the prediction error theory,and the load shedding cost and abandoned cost of the system are calculated according to the probability distribution function of wind power output The above cost and the operating cost of thermal power units are taken as objective functions.The new objective function takes into account the stability and economy of the system at the same time,and determines the new rotating reserve capacity of the system according to the objective function.Quantity.The model is solved by two layers.The outer layer determines the operation status of the unit through the economic benefits of the unit and the acceptable expected values of load shedding and abandoned light.The inner layer uses genetic algorithm to solve the model,which can effectively reduce the solving steps of the algorithm.The example shows that the safety of the system can be improved by allocating the rotating reserve capacity according to the wind power output.