Abstract
With the large-scale wind power integration, the uncertainty of wind power poses a great threat to the safe and stable operation of the system. This paper proposes dynamic economic dispatch problem formulation in thermal power system incorporating stochastic wind and small-hydro (run-in-river) power, called thermal-wind-small hydropower system (TWSHS). Weibull and Gumbel probability density functions are used to calculate available wind and small-hydro power respectively. An improved differential evolution algorithm based on gradient descent information (DE-GD) is proposed to solve the dynamic economic dispatch (DED) problem considering uncertainty of wind power and small-hydro power, as well as complicated constraints in TWSHS. Based on the traditional differential evolution algorithm, the gradient information of the objective function is introduced after the mutation process to enrich the diversity of the population, thus increasing the possibility of convergence to the global optimization. Generation scheduling is simulated on a TWSHS with the proposed approach. Simulation results verify feasibility and effectiveness of the proposed method while considering various complex constraints in the thermal-windsmall hydropower system.
Highlights
Classical economic power dispatch problem is formulated with only thermal generators
An improved differential evolution algorithm based on gradient information (DE-GI) is proposed to solve the dynamic economic dispatch (DED) problem considering uncertainty of wind power and small-hydro power, as well as complicated constraints in thermal-wind-small hydropower system (TWSHS)
Aiming at the non-differentiable point of the cost function in DED problem, this paper adopts the piecewise gradient method to obtain the gradient of the objective function, and considers that the nondifferentiable point of the objective function is just the local optimum
Summary
Classical economic power dispatch problem is formulated with only thermal generators. Dynamic economic dispatch (DED) is a method to schedule the online generator outputs with the predicted load demands over a certain period of time so as to operate an electric power system most economically [1]. It is a dynamic optimization problem taking into account the constraints imposed on system operation by generator ramping rate limits. Based on the previous studies, this paper proposes dynamic economic dispatch problem formulation in thermal power system incorporating stochastic wind and small-hydro (run-in-river) power, called thermal-windsmall hydropower system (TWSHS). An improved differential evolution algorithm based on gradient information (DE-GI) is proposed to solve the dynamic economic dispatch (DED) problem considering uncertainty of wind power and small-hydro power, as well as complicated constraints in TWSHS. Simulation results verify feasibility and effectiveness of the proposed method while considering various complex constraints in the thermal-wind-small hydropower system
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