Day-Ahead and Intra-Day Optimal Scheduling Considering Wind Power Forecasting Errors

Dagui Liu, Weiqing Wang (), Huie Zhang, Wei Shi, Caiqing Bai and Huimin Zhang
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Dagui Liu: Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Control, Xinjiang University, Urumqi 830047, China
Weiqing Wang: Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Control, Xinjiang University, Urumqi 830047, China
Huie Zhang: College of Energy Engineering, Xinjiang Institute of Engineering, Urumqi 830023, China
Wei Shi: State Grid Urumqi Electric Power Supply Company, Urumqi 830001, China
Caiqing Bai: Inner Mongolia Extra-High Voltage Power Supply Bureau, Hohhot 010080, China
Huimin Zhang: Inner Mongolia Extra-High Voltage Power Supply Bureau, Hohhot 010080, China

Sustainability, 2023, vol. 15, issue 14, 1-17

Abstract: The aim of this paper is to address the challenges regarding the safety and economics of power system operation after the integration of a high proportion of wind power. In response to the limitations of the literature, which often fails to simultaneously consider both aspects, we propose a solution based on a stochastic optimization scheduling model. Firstly, we consider the uncertainty of day-ahead wind power forecasting errors and establish a multi-scenario day-ahead stochastic optimization scheduling model. By balancing the reserve capacity and economic efficiency in the optimization scheduling, we obtain optimized unit combinations that are applicable to various scenarios. Secondly, we account for the auxiliary service constraints of thermal power units participating in deep peak shaving, and develop an intra-day dynamic economic dispatch model. Through the inclusion of thermal power units and energy storage units in the optimization scheduling, the accommodation capacity of wind power is further enhanced. Lastly, in the electricity market environment, increasing wind power capacity can increase the profits of thermal power peak shaving. However, we observe a trend of initially increasing and subsequently decreasing wind power profits as the wind power capacity increases. Considering system flexibility and the curtailed wind power rate, it is advisable to moderately install grid-connected wind power capacity within the power system. In conclusion, our study demonstrates the effectiveness of the proposed scheduling model in managing day-ahead uncertainty and enhancing the accommodation of wind power.

Keywords: scenario generation; stochastic optimization; unit combination; deep peak regulation; dynamic economic dispatch (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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