Tie-Line Reserve Power Probability Margin for Day-Ahead Dispatching in Power Systems with High Proportion Renewable Power Sources

Yue Chen, Zhizhong Guo, Abebe Tilahun Tadie, Hongbo Li, Guizhong Wang and Yingwei Hou
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Yue Chen: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Zhizhong Guo: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Abebe Tilahun Tadie: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Hongbo Li: Electric Power Research Institute of HITZ, Harbin Institute of Technology at Zhangjiakou, Zhangjiakou 075000, China
Guizhong Wang: Electric Power Research Institute of HITZ, Harbin Institute of Technology at Zhangjiakou, Zhangjiakou 075000, China
Yingwei Hou: Electric Power Research Institute of HITZ, Harbin Institute of Technology at Zhangjiakou, Zhangjiakou 075000, China

Energies, 2019, vol. 12, issue 24, 1-23

Abstract: In power systems with a high proportion of renewable power sources (PSHPRPSs), the power constraints of the tie-line may limit the ability of the reserve power to accommodate uncertain power generation, resulting in difficulties for the grid power balance. As uncertain power generation cannot be predicted accurately and in accordance with the law of probability and statistics, it is necessary to use a probability model to calculate the uncertain power of the tie-line. Here, day-ahead prediction error probability optimal power flow (DPEPOPF) is proposed to calculate the tie-line reserve power probability margin (TRPPM) in day-ahead dispatching. In day-ahead dispatching, TRPPM is reserved for real-time dispatching to accommodate uncertain power generation, so as to avoid tie-line power congestion. This study classifies the area of the grid based on the principle of area control error accommodation, and the DPEPOPF is divided into two categories: An inter-area day-ahead prediction error probability optimal power flow mathematical model, and an intra-area day-ahead prediction error probability optimal power flow mathematical model. The point estimate optimization algorithm was implemented in MATLAB 8.3.0.532 (R2014a) to calculate the TRPPM. The simulation results verify the accuracy of the model and effectively avoid power congestion of the tie-line.

Keywords: uncertain power generation; PSHPRPSs; day-ahead dispatching; dispatch control system; tie-line power constraint; DPEPOPF; TRPPM (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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