An optimization framework for decision making in large, collaborative energy supply systems
Published in ASME Journal of Energy Resources Technology, 2016
Recommended citation: DuPont B, Azam R, Proper S, Cotilla-Sanchez E, Hoyle C, Piacenza J, Oryschchyn D, Zitney S, Bossart S. "An optimization framework for decision making in large, collaborative energy supply systems." ASME Journal of Energy Resources Technology. 138(5):051601 (2016) http://energyresources.asmedigitalcollection.asme.org/article.aspx?articleid=2484527
As demand for electricity in the U.S. continues to increase, it is necessary to explore the means through which the modern power supply system can accommodate both increasing affluence (which is accompanied by increased per-capita consumption) and the continually growing global population. Though there has been a great deal of research into the theoretical optimization of large-scale power systems, research into the use of an existing power system as a foundation for this growth has yet to be fully explored. Current successful and robust power generation systems that have significant renewable energy penetration—despite not having been optimized a priori—can be used to inform the advancement of modern power systems to accommodate the increasing demand for electricity. This work explores how an accurate and state-of-the-art computational model of a large, regional energy system can be employed as part of an overarching power systems optimization scheme that looks to inform the decision making process for next generation power supply systems. Research scenarios that explore an introductory multi-objective power flow analysis for a case study involving a regional portion of a large grid will be explored, along with a discussion of future research directions.