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Calculating Wind Variability Costs with Considering Ramping Costs of Conventional Power Plants

  • Xuemei Dai
  • Kaifeng ZhangEmail author
  • Jian Geng
  • Ying Wang
  • Kun Yuan
Original Article
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Abstract

Due to the variability of the wind power, conventional power plants are required to ramp more frequently to mitigate the imbalance of generation and supply, which increase the total cost of power systems. The increase of the cost is termed the “variability cost” of wind power. Generally, it includes the additional ramping cost, reserve cost and fuel cost of conventional plants. In this paper, we propose an alternative scenario construction method to calculate the “variability cost” of wind power from the viewpoint of the power system schedule. Firstly, in the alternative scenario, a new energy proxy with zero wind variability costs is constructed. Then, a unit commitment optimization model considering ramping costs is developed. The operation costs of power systems under two scenarios (alternative one and real one) are calculated and the difference between two costs is the variability cost. Furthermore, we apply the proposed method to calculate the variability costs of the wind farm cluster. The simulations show that the variability cost increases with higher penetration and higher variability of wind power. Meanwhile, it is found that the variability cost of the wind farm cluster as a whole is lower than the sum of variability costs of each wind farm.

Keywords

Variability costs Alternative scenario construction method Optimal scheduling model Wind power 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 51477157) and State Key Laboratory of Smart Grid Protection and Control (Analysis of Response Characteristics of Load Resources and Frequency Control Technology of Source-Grid-Load Coordination).

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Copyright information

© The Korean Institute of Electrical Engineers 2019

Authors and Affiliations

  • Xuemei Dai
    • 1
  • Kaifeng Zhang
    • 1
    Email author
  • Jian Geng
    • 2
  • Ying Wang
    • 1
  • Kun Yuan
    • 1
  1. 1.Key Laboratory of Measurement and Control of CSE, Department of AutomationSoutheast UniversityNanjingChina
  2. 2.Department of Electricity MarketChina Electric Power Research InstituteNanjingChina

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