Stochastic Short-Term Hydro-Thermal Scheduling Based on Mixed Integer Programming with Volatile Wind Power Generation

Document Type : Research paper

Authors

1 Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

2 Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

Abstract

This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to various types of uncertainties such as energy price, spinning /non-spinning reserve prices, uncertainties of RESs, such as output power of the wind power plant are also taken into account. In the proposed framework, mixed-integer non-linear  programming of the HTSS problem is converted into a MIP. Since the objective of the study is to show how GenCosʼ aim to achieve maximum profit, mixed-integer programming is used here. Therefore, to formulate the MIP for the problem of HTSS with a wind power plant in the real-time modeling, some parameters like the impact of valve loading cost (VLC) that are accompanied by linear modeling, are considered. Furthermore, in thermal units, parameters such as prohibited operating zones (POZs) and different  uncertainties  like the energy  price and wind power are included  to formulate the problem more suitably. The point that is worth noting is the use of dynamic ramp rate (DRR). Also, the application of multi-functional curves (L) of hydro plants is considered  when studying  inter-unit scheduling. Finally, the required tests are conducted  on  a modified  IEEE 118-bus system to verify the accuracy and methodology of the proposed method.

Keywords

Main Subjects

References

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Journal of Operation and Automation in Power Engineering
Volume 8, Issue 3
December 2020
Pages 195-208

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History

  • Receive Date: 23 April 2019
  • Revise Date: 19 July 2019
  • Accept Date: 14 September 2019
  • First Publish Date: 01 December 2020

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