Evaluation of Wind Energy Accommodation Based on Two-Stage Robust Optimization

Kunpeng Tian; Weiqing Sun; Dong Han; Ce Yang

doi:10.5755/j01.eie.26.3.25756

Authors

Kunpeng Tian Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China https://orcid.org/0000-0001-7267-4002
Weiqing Sun Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Dong Han Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Ce Yang Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

DOI:

https://doi.org/10.5755/j01.eie.26.3.25756

Keywords:

Economic dispatch, Wind energy accommodation, Two-stage robust optimization, Benders algorithm

Abstract

Large-scale renewable energy integration brings unprecedented challenges to electric power system planning and operation. The paper aims at economic dispatch and the safe operation of high penetration renewable energy power systems. According to the principle of power system dispatchability, the assessment of wind energy accommodation is formulated into a two-stage robust optimization problem with a min-max-min structure. Based on the benders algorithm, the intractable robust optimization problem is transformed into the form of sub-problem and master problem. Strong duality theory and big-M method are used to recast the sub problem into a mixed integer linear programming. The envelope of wind energy accommodation can be obtained by using commercial software to solve the master problem and sub problem alternately. For the realization of arbitrary wind power within the envelope, the amount of wind energy leakage and load shedding in power system operation are acceptable. An example of modified IEEE 39-bus test systems is used to verify the effectiveness and practicability of the evaluation method.

Author Biographies

Kunpeng Tian, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

KUNPENG TIAN received the M.S. degree in electrical engineering from University of Shanghai for Science and Technology, Shanghai, China, in 2018. He is currently working toward the Ph.D. degree with the same university. His research interests include power system operation and investment planning.

Weiqing Sun, Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

WEIQING SUN received the B.S., M.S., and Ph.D. degrees in electrical engineering from Shanghai Jiao tong University, Shanghai, China, in 2007, 2009, and 2013, respectively. Currently, he is an associate professor with University of Shanghai for Science and Technology, Shanghai, China. His current research interests are renewable energy, power system planning, and optimization theory.

Dong Han, Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

DONG HAN received the Ph.D. degree in electrical engineering from Shanghai Jiao tong University, Shanghai, China, in 2016. Currently, he is a lecturer with University of Shanghai for Science and Technology, Shanghai, China. His current research interests are electricity market and optimization theory.

Ce Yang, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

CE YANG received B.S. degree in electrical engineering and automation from Shanghai DianJi University, Shanghai, in 2014. He is currently pursuing the Ph.D. degree with the Department of control science and engineering, University of Shanghai for Science and Technology, Shanghai. His research interests include power system automation and energy management system.