Model Predictive Control Based Ramp Minimization in Active Distribution Network Using Energy Storage Systems

Abstract

The growing integration of renewable energy sources, especially the residential photovoltaic (PV) systems, in the distribution networks (DNs) aggravates the ramp-events in transmission system. To address this issue, we propose a novel look ahead dispatch model for the ramp minimization in DNs using distributed energy storage systems (ESSs). The dispatch problem considering the scheduling of ESSs is modeled as a finite-horizon optimization problem and is carried out using model predictive control (MPC) method that takes both current and future information into account. In addition, the optimal power flow in DN is formulated as a second-order cone programing problem to guarantee the global optimality. Numerical results on IEEE 37-bus distribution network show that our proposed model not only brings about 74% reduction of maximum ramp but also yields the near-minimum system operating cost.

Keywords:

• active distribution network
• photovoltaic systems
• ramp-event
• energy storage system
• model predictive control

Additional information

Funding

This work was partially supported by Hong Kong RGC Theme Based Research Scheme under Grant No. T23-407/13N and T23-701/14N and partially supported by the Science and Technology Projects of Hunan Province under Grant 2017WK2050.

Notes on contributors

Jiayong Li

Jiayong Li received the B.Eng. degree from Zhejiang University, Hangzhou, China, in 2014, and the Ph.D. degree from The Hong Kong Polytechnic University, Hong Kong SAR, in 2018. He is currently an Assistant Professor with the College of Electrical and Information Engineering, Hunan University, Changsha, China. He was a Postdoctoral Research Fellow with The Hong Kong Polytechnic University and a Visiting Scholar with Argonne National Laboratory, Argonne, IL, USA. His research interests include power economics, energy management, distribution system planning and operation, renewable energy integration, and demand-side energy management.

Zhao Xu

Zhao Xu received the B.Eng, M.Eng, and Ph.D. degrees from Zhejiang University, Hangzhou, China; National University of Singapore, Singapore; and the University of Queensland, Brisbane, QLD, Australia, in 1996, 2002, and 2006, respectively. From 2006 to 2009, he was an Assistant and later Associate Professor with the Center for Electric Technology, Technical University of Denmark, Lyngby, Denmark. Since 2010, he has been with The Hong Kong Polytechnic University, Hong Kong, where he is currently a Professor with the Department of Electrical Engineering and Leader of Smart Grid Research Area. He is also a foreign Associate Staff of Center for Electric Technology, Technical University of Denmark. Dr. Xu is an Editor for the Electric Power Components and Systems, the IEEE PES Power Engineering Letters, and the IEEE Transactions on Smart Grid. His research interests include demand side, grid integration of wind and solar power, electricity market planning and management, and AI applications.

Jian Zhao

Jian Zhao received the B.Eng. degree from Zhejiang University, Hangzhou, China, in 2013, and the Ph.D. degree from Hong Kong Polytechnic University, Hong Kong, in 2017. He is currently with the Department of Electrical Power Engineering, Shanghai University of Electric Power, Shanghai, China. He was a Research Assistant with Hong Kong Polytechnic University and a Visiting Scholar with Argonne National Laboratory, Argonne, IL, USA. His research interests include distribution network operation and planning, grid integration of electric vehicles and renewable energies.

Songjian Chai

Songjian Chai received the Ph.D. degree from The Hong Kong Polytechnic University, Hong Kong SAR, in 2018. He is currently a Postdoctoral Research Fellow with The Hong Kong Polytechnic University. His research interests include variable renewable generation forecasting, electricity price forecasting, power system uncertainty analysis, electricity market, and machine learning application in power engineering.

Yi Yu

Yi Yu received the B.Eng. degree in electrical engineering from Wuhan University, Wuhan, China, in 2012, where he is currently pursuing the Ph.D. degree. He was a Research Assistant with Department of Electrical Engineering, Hong Kong Polytechnic University. His research interests include distribution network planning and operation, distributed generation integration, and demand side management.

Xu Xu

Xu Xu received the B.Eng. degree in electrical engineering from Qingdao University of Technology, Qingdao, China, in 2015 and the M.Eng. degree in electrical engineering from The Hong Kong Polytechnic University, Hong Kong, in 2016. He is currently working toward the Ph.D. degree at the Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong. His research interests include transmission & distribution system planning and operation, renewable power integration, and energy management.