Robust Environmental-Economic Dispatch Incorporating Wind Power Generation and Carbon Capture Plants

Significance Statement

Due to the proliferation of renewable power generation and the adoption of carbon capture technologies aiming to reduce carbon dioxide emissions and alleviate environmental pollution, various uncertainties accompany the use of environmental-economic dispatch method. A two-stage robust optimization framework affords one of the best approaches used for coping with these uncertain factors. However, this approach has handiest been applied in optimization problems with sole objective. As a way of providing the most desirable and efficient control of carbon emissions, high generation cost as a result of energy consumption in carbon capture plants needs to be considered also.

A group of researchers led by Dr. Wei Wei from Tsinghua University and in collaboration with Dr. Jianhui Wang from Argonne National Laboratory in USA and professor Tiejiang Yuan from Xinjiang University in China proposed a robust environmental-economic dispatch method which provides both energy optimization and reverse scheduling while considering the operation of carbon capture plants and volatility of large-scale wind power generation. Additionally, they made use of a Nash bargaining criterion to strike a balance between generation cost and carbon emission without a clear carbon tax or emission cap for building a single-objective optimization model with clear physical meaning. The research work is now published in the journal, Applied Energy.

The authors devised a non-parametric scalarization model for the environmental-economic dispatch problem, which is shown to be equivalent to a second-order cone program, and suggested an adaptive scenario generation algorithm to solve the robust model in a tractable manner. The computations of the Pareto front could be achieved by using the ɛ-constraint method since both of the objectives under investigation are convex functions.

With the provision of the formulated environmental-economic dispatch model incorporating carbon capture plants and volatile wind generation, PJM 5-bus system and IEEE 118-bus system were used as case studies.

Simulation results from the PJM 5-bus system with a robust environmental-economic dispatch and absence of capture facilities gave a generating cost of $39,085 and carbon dioxide emission of 1166 tons, while the inclusion of contrived capture facilities led to a generating cost of $42, 123 and carbon dioxide emissions of 921 tons. The included capture facility led to an increase of 7.77% generating cost and a reduction of 26.6% carbon emission compared with the situation without capture facilities.

The carbon capture plants were also found to increase the system operating flexibility and enlarge the dispatchable region of wind power, as the energy consumption in capture facilities plays the role of spinning reserve capacity. Simulation results from the case studies of IEEE 118-bus system similarly verified the efficiency of the proposed methodology to perform the assigned task.

The proposed methodology in this study confirms that the combination of wind generation and carbon capture technology could provide an economic and environmental friendly operation for power systems, and the resulting dispatch problem can be solved in a theoretically sound manner.

About the author

Wei Wei received the B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 2008 and 2013, respectively.
He was a Postdoctoral Researcher with Tsinghua University from 2013 to 2015. He was a Visiting Scholar with the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA, in 2014, and with the School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA, in 2015. He is currently an Assistant Professor with Tsinghua University.

His research interests include applied optimization and energy economics. He has authored more than 40 peer-reviewed journal papers, with special emphasis on the integration of large-scale renewable generation. Most of them are published in IEEE Transaction journals and Elsevier energy related periodicals. He is currently focusing on the operation and market issues of the networked energy systems, including the electric power grid, natural gas pipeline network, district heating network, and electrified transportation network.

About the author

Feng Liu received the B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 1999 and 2004, respectively.

He is currently an Associate Professor of Tsinghua University. His research interests include power system stability, control, and distributed optimization.

About the author

Jianhui Wang received the Ph.D. degree in electrical engineering from Illinois Institute of Technology, Chicago, IL, USA, in 2007.

Dr. Jianhui Wang is the Section Manager for Advanced Power Grid Modeling in the Energy Systems division at Argonne National Laboratory. Dr. Wang is the Principal Investigator for a multitude of energy-related research projects focused on smart grid, microgrids, power system operation and control, renewable integration, grid resilience and cyber-security. He currently manages a group of 12 research staff and postdocs and 14 visiting students and scholars. In addition, he is a Fellow of the Computation Institute at The University of Chicago, an Adjunct Professor at the University of Notre Dame and an Affiliate Professor at Auburn University. He has also held visiting positions in Europe, Australia and Hong Kong including a VELUX Visiting Professorship at the Technical University of Denmark (DTU). He has been invited to give tutorials and keynote speeches at major conferences including IEEE SmartGridComm, IEEE SEGE, IEEE HPSC and IGEC-XI.

Dr. Wang is the secretary of the IEEE Power & Energy Society (PES) Power System Operations committee. Before being promoted and elected to this position, he was the chair of the IEEE PES Power System Operation Methods Subcommittee for six years. He is also the recipient of the IEEE Chicago Section 2012 Outstanding Young Engineer Award.

Dr. Wang has authored and/or co-authored more than 200 journal and conference publications, which have been cited for more than 5,000 times by his peers. He is an associate editor of Journal of Energy Engineering and an editorial board member of Applied Energy. He served as guest editor for a special issue of the IEEE Power and Energy Magazine on Electrification of Transportation, which won an APEX Grand Award. Dr. Wang also served as the editor of Artech House Publishers’ Power Engineering Book Series, and as the Technical Program Chair of the 2012 IEEE PES Innovative Smart Grid Technologies conference.

Dr. Wang is the Editor-in-Chief of the IEEE Transactions on Smart Grid and an IEEE PES Distinguished Lecturer. He is the recipient of the IEEE PES Power System Operation Committee Prize Paper Award in 2015.

About the author

Shengwei Mei received the B.Sc. degree in mathematics from Xinjiang University, Urumqi, China, the M.Sc. degree in operations research from Tsinghua University, Beijing, China, and the Ph.D. degree in automatic control from Chinese Academy of Sciences, Beijing, China, in 1984, 1989, and 1996, respectively.

He is currently a Professor of Tsinghua University and a Fellow of the IEEE. His research interests include power system analysis and control, game theory and its application in power systems.

Journal Reference

W. Wei1, F. Liu1, J. Wang2, L. Chen1, S. Mei1, T. Yuan3, Robust Environmental-Economic Dispatch Incorporating Wind Power Generation and Carbon Capture Plants, Applied Energy 183 (2016) 674–684.

Show Affiliations
  1. Department of Electrical Engineering, Tsinghua University, 100084 Beijing, China
  2. Argonne National Laboratory, Argonne, 60439 IL, USA.
  3. Department of Electrical Engineering, Xinjiang University, 830046 Urumqi, China


Go To Applied Energy

Check Also


Bio-Inspired Modeling for H2 Production