Optimal Scheduling Of Power System Peak Shaving Considering Uncertainty Of Wind Power And Electric Vehicles

With the increasing attention to environmental protection and the increasing shortage of energy,the development of new energy industry has been strongly supported.The large-scale grid connection of wind power and the rapid development of electric vehicles have brought great opportunities to China’s energy industry.Wind power output is strongly uncertain due to the influence of geographical environment,climate conditions and some random events.In contrast to the peak valley characteristics of conventional load,wind power output has obvious reverse peak regulation phenomenon,which restricts the consumption capacity of new energy.The uncertainty of electric vehicle charging load has a certain impact on the power grid,which further increases the difficulty of system peak shaving and brings many challenges to power grid operation and dispatching.Therefore,considering the uncertainty of wind power and electric vehicle,this paper studies the optimal dispatching of power system peak shaving.Firstly,this paper considers the uncertainty of wind power output and electric vehicle in peak shaving optimal dispatching,and uses scenario analysis method and Monte Carlo simulation to model the uncertain wind power and electric vehicle respectively.Based on Latin hypercube sampling,the probability density function of wind power prediction error is sampled to generate the initial scene set of wind power.Combined with K-means clustering method,all the original scenes of wind power are reduced to obtain the typical scene of wind power output and its occurrence probability.The charging and behavior characteristics of electric vehicles are analyzed,and the mathematical model of disordered charging load is established based on Monte Carlo simulation.Secondly,starting from the power side and load side,the effect of thermal power units and electric vehicles participating in peak shaving optimal dispatching is studied.On the power side,the deep peak regulation of thermal power units expands the space of system peak regulation,and studies the economy of deep peak shaving operation of thermal power units.The peak shaving process is divided into three stages with different energy consumption characteristics.Considering the coal consumption,life loss,oil input and environmental additional cost of deep peak shaving,the whole process cost model of thermal power peak shaving is established.Taking 6 units as an example,the economy of thermal power deep dispatching optimization considering wind power consumption is analyzed.On the load side,the influence of electric vehicle charging load on the peak and valley of power grid under different electricity price systems is studied.Aiming at the minimum load peak valley difference and the minimum user charging cost after superposition of electric vehicle charging load,an orderly charging scheduling model is established.The elite genetic algorithm is used to optimize the solution.The example results show that the orderly charging has little impact on the peak and valley of system load,reduces the peak load of power grid,and the unit charging cost of electric vehicle is lower than that under fixed electricity price.Finally,considering the reduced economy of thermal power participating in deep peak shaving,energy storage is used to assist thermal power deep peak shaving,and an optimal dispatching scheme considering source load storage combined peak shaving is proposed.During the low load period,the charging of the energy storage unit will increase the minimum load rate of the unit;During the peak load,the stored energy supplies power to the power grid as a power supply to reduce the peak load of the system.A two-stage dispatching model of energy storage assisted thermal power deep peak shaving considering wind power consumption is established.Six units are simulated,and the influence of electric vehicle orderly charging load on the peak valley difference of power grid load is analyzed.The economy of power supply,load and energy storage combined peak shaving and the effect of energy storage assisted thermal power peak shaving are analyzed to verify the correctness and effectiveness of the strategy proposed in this paper.