Containing Pumped Storage With Wind Hydro And Thermal Power Joint Economic Dispatch Under The Low-Carbon Electricity Systems

Due to many factors, large-scale, combined with energy storage devices and new energy generation technologies, low-carbon electricity system has increased the complexity of the system to optimize the scheduling structure. Meanwhile, as the world increasingly nervous energy; the environment is deteriorating; how efficient implementation of low-carbon power optimization scheduling problem has become an important topic of recent research.This paper considers the optimal economic dispatch problem with pumped-storage, by analyzing the key factors of low-carbon electricity scheduling, pumped-storage power complementary constraints characteristic equation, the model of including pumped-storage, unit commitment, and multi-objective about low-carbon scheduling is established. The unit commitment; multi-objective optimization problem and pumped-storage complementary constraints problem are discussed, and by simulating the10thermal-power about24hours systems; the10thermal-power about96hours systems and expansion systems show that by taking into account the relevant factors affecting the conditions of low-carbon operation, this model through reasonable arrangements the thermal power units, effectively use pumped-storage devices load shifting role, finally achieve the low-carbon operation of system.Consider the low-carbon benefits; economic benefits and energy efficiency of new energy, including pumped-storage, unit commitment, multi-objective, wind-hydro and thermal power in low-carbon power dispatching model is established. To deal with presence of wind power randomness and volatility issues in this model, the paper mainly adopt least squares support vector machine (SVM) algorithm to calculate predicted wind speed, use features of wind speed-power equation to solve predicted power, use non-parametric method calculate predict power confidence interval and according to analyze forecast error to find out random prediction power curve. By simulating the10thermal-power about96hours systems and expansion systems, the simulation results show that this model can make full use of the role of hydropower peaking while, and can be very good adjust wind power randomness brings volatility for this grid, thus ultimately achieve low-carbon; economy; and stable operation of the power grid.