We conjecture that the existing U.S. energy system could be operated with significantly increased efficiency, reliability, and environmental safety if industry participants were provided with an empirically based model of an integrated energy system permitting comprehensive assessments of production, storage, transportation, conversion, and delivery alternatives. Over 76% of electric energy in the U.S. is supplied by coal, gas, or water. These three raw energy forms, together with electricity, have the common characteristic that they can be moved in bulk quantities via a transportation system from their source of production to where they are used. Coal is mainly moved by train and barge; gas by pipelines; water by rivers and reservoir systems; and electricity by transmission lines. The pattern of movement from raw energy source to power plants to electric distribution substations of the many different U.S. load centers is determined by a complicated decision-making process comprised of many different organizations. Our research objective, therefore, is to develop decision models to address three related areas of questions: (1) What energy flow patterns would yield significantly improved energy system performance? What operational production and/or transportation changes need to be made to realize these improvements? (2) What infrastructure weaknesses exist? What infrastructure enhancements would realize the most performance benefit? (3) How well can we predict the influence of market design changes on energy system performance? We will develop two types of models to answer these questions. A structural-optimization model will enable mid-term (1 month to 2 years) simulation of the energy systems, their physical infrastructure, and their associated market flows. A behavioral model will focus on the market network overlaying the structural model. Market participants are modeled as strategic energy traders having the ability to act autonomously and learn from the influence of their previous decisions. These two models interact through energy price/quantity/location/time bids and offers generated by the trader-agents. We will use a participatory model development process in which we repeatedly loop through fieldwork, model design and development, and computational experiments. Of particular interest are structural and social factors constraining and shaping the decision-making processes of raw-fuel production and transportation firms as well as firms engaged in electricity generation, transmission, and distribution. This knowledge will be used to guide the development of the structural and market models and hence to improve the ability of these models to provide accurate system performance assessments. We will thereby gain better understanding of the social and structural factors affecting the decision-making processes of system participants and the willingness of system participants to adopt new structures and procedures to improve the efficiency of the energy transmission system. The modeling developed and analysis performed in this research will enable systematic examination of nationwide bulk energy production and transportation decisions and consequently reveal efficiencies in operational and facility investment having very large national economic impact. In addition, it will expose energy system vulnerabilities, leading to an energy system design and analysis approach that accounts for uncertainties and disruptions to steer reliability enhancement and market design. These efforts will result in characterization of energy system human decision processes at organizational and cognitive levels, extending knowledge of human dynamics in decision-making related to high-stress situations affecting a national critical infrastructure, while deepening the understanding of practical and conceptual relations between advanced network optimization and software agents. The culmination of this work will include a sound and robust suite of models and accompanying modeling methods for study, analysis, and design of the integrated energy system, together with its markets. Such public domain, open-source availability of tools and methods will have significant effect on stimulating and encouraging further university-based research and education in this area, bridging separate fields (power systems, sociology, decision-science, and economics) in new ways that will contribute to enriching education and research in each of the areas.
