Stochastic Optimal Dispatch Of Power System Based On V2G Technology

With the development of new energy technology and the implementation of China’snational energy saving policy, it is increasingly important attached importance to thepower system with the application of wind power and electric vehicles. With the rapiddevelopment of smart grid especially the charging and discharging base facilities ofelectric vehicle, wind power and electric vehicle co-scheduling problem has arousedwidespread concern. The randomness of the wind farm output and electric vehiclecharging and discharging becomes more and more outstanding for the power system.So research on the stochastic optimization problem of the power system consideringthe uncertainty of wind power output and electric vehicle charging and dischargingoutput has a very important theoretical and practical significance.The Weibull distribution is used to describe randomness of the wind speed,combined with the relationship between the wind speed of wind turbine and the windpower output to analysis the uncertainty of wind power output. The statistical modelof electric car charging and discharging power is established by assuming that thestart time of the electric vehicle charging and discharging were as the law of uniformdistribution and the daily mileages were as the law of normal distribution.The stochastic optimization dispatch model of grid-connected wind farms based onV2G (vehicle-to- grid) is proposed in this paper. The conventional unit fuel costs,electric car charging and discharging costs were added to the model of optimalscheduling and using the cost-optimal for the target. Using Monte Carlo samplingaverage approximation of the chance constrained stochastic factors to describe theuncertainty of wind power output and electric vehicle charging and discharging powerconstraints into deterministic constraints. The improved particle swarm algorithm isused to solve the stochastic optimization dispatch model. The simulation of theIEEE-14 bus system demonstrates that the proposed model is reasonable and effectivesex and the proposed stochastic optimization dispatch is more economic compared todeterministic optimization method.The stochastic optimization dispatch model based on V2G considering theemissions from the penalty cost are established by increasing the emissions penaltycost function of conventional unit to the model and using the probability in the formof chance constraints to describe the uncertainty of the charge and discharge power ofelectric vehicles and wind power output. The improved particle swarm optimization is used to solve the stochastic optimization dispatch model, and Monte Carlo sample isused to average approximation of the random factors. The simulation of the IEEE-14bus system shows that when considering the emissions from the penalty cost althoughthe cost of power generation increased slightly, but significantly improve theutilization of wind power and electric vehicle charging and discharging power, reducethe emissions of polluting gases. It demonstrates the rationality and effectiveness ofthe model proposed in this paper, and it is more conducive for the realization of thepower system of the traditional optimal scheduling change to the optimization of theenergy saving operation mode.