Optimal Dispatch Of Wind Power System Considering Carbon Tradin

Energy is the material basis for the survival and development of human society.However,the consumption of large amounts of fossil fuels leads to energy shortages,and at the same time,it causes serious environmental pollution problems.With the strategic goal of "carbon peaking and carbon neutrality" proposed in my country,joint dispatching that takes into account the economy and the environment has become the focus of research in the power industry.On the one hand,clean energy is actively developed.As one of the most promising green and clean energy sources in the 21 st century,wind power has been widely used,but the uncertainty of wind power output increases the difficulty of power system dispatching;With coal as the main energy resource,it is necessary to strictly control the emission of carbon dioxide and take the road of low-carbon economic development.The establishment of a carbon trading market has become one of the most effective incentives for carbon emission reduction.In this context,this thesis studies the optimal dispatch of wind power systems considering carbon trading.Firstly,this thesis introduces the optimal dispatch model of the traditional power system and the impact of wind power grid integration on the system;secondly,it elaborates the basic knowledge of carbon trading from the aspects of carbon trading principle and initial allocation method of carbon emission allowances,and analyzes the effect of carbon trading.Introduce the impact on dispatching of power systems with wind power.In order to actively respond to the national call for energy conservation and emission reduction,a dynamic optimal dispatch model for the power system that does not take into account the cost of wind power is established under the background of the introduction of carbon trading.In the model,the predicted values of wind power and load power are taken as known deterministic variables,the forecast errors of wind power and load are taken as random variables,and thermal power and CSP are taken as optimization decision variables.In order to solve the uncertainty of wind power and load forecasting,consider increasing the positive and negative spinning reserve capacity.In view of the fact that large-scale wind power grid connection makes it impossible to meet the system spinning reserve demand only by thermal power,it is proposed to use the combination of thermal power and solar thermal power to provide spinning reserve.On this basis,the operating risk cost is defined,and the positive and negative spinning reserves are constrained by the probabilistic form of the chance-constrained programming,and the constraints are equivalently deterministically transformed.In the carbon transaction cost modeling,only considering the carbon transaction cost modeling of thermal power,the carbon dioxide emission problem can be better solved.The environmental hazards caused by sulfur dioxide and nitrogen oxides are considered in the pollutant emission objective function to further promote the low-carbon emission reduction of system dispatch.The multi-objective particle swarm algorithm is used to solve the model.Next,establish a dynamic optimal dispatch model for the power system that takes into account wind power costs.The model takes the predicted values of wind power and load power as known deterministic variables,and both thermal power and wind power output are used as optimization decision variables.Different from the model built above,in the uncertainty treatment of wind power output,the probability density function of wind speed is considered to be converted into a probability analytic model of wind power output active power.Excess wind abandonment penalty cost.In the carbon transaction cost modeling,the carbon trading process of thermal power and wind power is considered separately,and the uncertainty of wind power leads to the increase of thermal power rotating reserve capacity and thus increases carbon emissions,and makes corresponding carbon emissions issues for thermal power and wind power.compensation and punishment.The example simulation uses the IEEE-30 node system to verify the feasibility and superiority of the two scheduling models proposed in this study.