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Journal article ยท Ahead of Print article

Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power

In Energy โ€” 2020, Volume 193, pp. 116826
From

South China University of Technology1

Department of Electrical Engineering, Technical University of Denmark2

Center for Electric Power and Energy, Centers, Technical University of Denmark3

Electric Power Systems, Center for Electric Power and Energy, Centers, Technical University of Denmark4

The random wind power that accounts for a growing proportion in power systems imposes higher challenge on the reliable operation of power system under uncertain circumstances. Since forecasted values of wind speed are accessible to system operators in advance, the corresponding calculated pre-schedule can be regarded as a reference for the stochastic economic dispatch (SED) problem.

Existing methods seldom take the pre-schedule into account when determining an optimal dispatch solution, and the resulting dispatch solutions generally differ greatly from the pre-schedule. In this paper, aiming to readjust from the reference schedule as little as possible, the mean-tracking model is proposed for the first time to search for optimal dispatch solutions with the minimal expectation of generation cost and the minimal tracking errors, among which the tracking errors is implemented to each generator unit in terms of minimizing the deviation in generation cost between the trial solution and the pre-schedule.

Moreover, the affine decision rule is applied in this paper to distribute the uncertain wind power proportionally to each generator unit. To guarantee the stable operation of power systems, the voltage operating limits are considered to ensure the voltage on each bus remains within the security margins of voltage.

Numerical experiments are carried out on a modified IEEE-30 bus system, and simulation results demonstrate the effectiveness of the proposed mean-tracking model for the SED problem.

Language: English
Year: 2020
Pages: 116826
ISSN: 18736785 and 03605442
Types: Journal article and Ahead of Print article
DOI: 10.1016/j.energy.2019.116826
ORCIDs: Wu, Qiuwei , 0000-0002-8194-3515 and 0000-0001-7044-1782

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