Issue |
MATEC Web Conf.
Volume 246, 2018
2018 International Symposium on Water System Operations (ISWSO 2018)
|
|
---|---|---|
Article Number | 01085 | |
Number of page(s) | 7 | |
Section | Main Session: Water System Operations | |
DOI | https://doi.org/10.1051/matecconf/201824601085 | |
Published online | 07 December 2018 |
Dynamic Economic Dispatch in Thermal-Wind-Small Hydropower Generation System
1 School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2 Hubei Key Laboratory of Digital Valley Science and Technology, Wuhan 430074, China
3 Central China Power Grid Company, Wuhan, Hubei 430077, China
* Corresponding author: jz.zhou@mail.hust.edu.cn
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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