Nuri Cihat Onat
Qatar University, QTTSC, Faculty Member
- Environmental Sustainability, Sustainable Development, Life Cycle Assessment, Input-Output Analysis, Triple Bottom Line, System Dynamics Modeling, and 11 moreSystem Dynamics, Carbon Footprint, Green buildings, Net Zero Energy Buildings, Electric Vehicles, Alternative Vehicle Technologies, Sustainable Transportation, Supply Chain Management, Green Supply Chain Management, Manufacturing, and Lean Manufacturingedit
Urban passenger transportation in the U.S. has been heavily dependent on car modes, mainly due to prevailing trends in urban development. However, transportation mode choice studies are currently limited to micro-level and regional-level... more
Urban passenger transportation in the U.S. has been heavily dependent on car modes, mainly due to prevailing trends in urban development. However, transportation mode choice studies are currently limited to micro-level and regional-level boundaries, lacking of presenting a complete picture of the issues and the root causes associated with urban passenger transportation choices in the U.S. To this end, further analysis from a system perspective is required to investigate the interdependencies among system parameters more thoroughly, thus revealing the underlying mechanisms contributing or causing the low public transportation use in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships among the critical system parameters affecting public transportation ridership in the U.S. as well as to identify possible policy areas to improve public transportation ridership rates. Considering the high degree of uncertainties inherent to the problem, multivariate sensitivity analysis is utilized to explore the effectiveness of existing and possible policy implications up to the year 2050 in the terms of their potential to increase transit ridership and locating critical parameters that influences the most on mode choice and emission rates. Transportation mode choice behavior is projected to change slightly and reach up to a maximum of 7.25% of public transportation ridership until 2050. Analysis results reveal that the effects of trip length and rate are by far the most influential factors. Both parameters are 99% sensitive compared to all other factors including the effects of fuel tax policies, federal funds for public transportation, use of alternative green bus technologies, increasing private vehicle occupancy rates, etc. on negative environmental, economic, and social impacts of transportation. This finding highlights how important urban structures are to secure the future of public transportation in the U.S. as the existing urban structures and the shared-idea in the minds of the society about how urban transportation should be (the prevailing paradigm) are the root causes of excessive trip generation and increasing average trip lengths. Thus a paradigm-shift, a radical change in the shared-idea in the minds of the society about existing urban structures, is needed.
Research Interests:
Vehicle to Grid (V2G) technology for use in ancillary services is studied. A regional net revenue and life cycle emissions savings of V2G system is conducted. The future market share of electric vehicles is predicted using an Agent-Based... more
Vehicle to Grid (V2G) technology for use in ancillary services is studied. A regional net revenue and life cycle emissions savings of V2G system is conducted. The future market share of electric vehicles is predicted using an Agent-Based Model. For a single vehicle, net revenue of V2G service is highest for the New York region. However, PJM region has an approximately $97 million overall net revenue potential. a b s t r a c t Vehicle to Grid technologies utilize idle EV battery power as a grid storage tool to meet fluctuating electric power demands. Vehicle to Grid systems are promising substitutes for traditional gas turbine generators , which are relatively inefficient and have high emissions impacts. The purpose of this study is to predict the future net revenue and life cycle emissions savings of Vehicle to Grid technologies for use in ancillary (regulation) services on a regional basis in the United States. In this paper, the emissions savings and net revenue calculations are conducted with respect to five different Independent System Operator/Regional Transmission Organization regions, after which future EV market penetration rates are predicted using an Agent-Based Model designed to account for various uncertainties, including regulation service payments, regulation signal features, and battery degradation. Finally, the concept of Exploratory Modeling and Analysis is used to estimate the future net revenue and emissions savings of integrating Vehicle to Grid technology into the grid, considering the inherent uncertainties of the system. The results indicate that, for a single vehicle, the net revenue of Vehicle to Grid services is highest for the New York region, which is approximately $42,000 per vehicle on average. However, the PJM region has an approximately $97 million overall net revenue potential, given the 38,200 Vehicle to Grid-service-available electric vehicles estimated to be on the road in the future in the PJM region, which is the highest among the studied regions.
