With large-scale wind power integrated into power systems

the uncertainty of wind power has brought new challenges to the economic dispatch of power systems. Versatile probability distribution is used to fit the distribution of actual wind power at different forecast levels. And based on it

a stochastic day-ahead dynamic economic dispatch model is developed considering both lower and higher evaluated penalty costs of wind power. By transformation and analysis of the objective function and the constraints

a stochastic optimization model is ultimately transformed into a nonlinear convex optimization problem. Combined with quadratic programming algorithm and interior point method

a two-stage optimization algorithm is proposed to solve the economic dispatch problem. Finally

simulation is implemented on the IEEE 30-bus system with a wind farm and the results verify the effectiveness of the proposed stochastic dynamic economic dispatch method.