A multi-paradigm modeling approach for energy systems analysis
Energy plays a vital role in the world today, driving industry and allowing for technologies ingrained throughout the routines of daily life. The complex interactions, evolution, long time scales of change, and critical nature of the energy system makes modeling and analysis crucial to developing insight on how the evolution of energy systems can be shaped. What is needed is not the development of a uniform model, but a flexible, open framework that allows for the integration of existing and future models. The framework should be flexible to allow the evolution of the questions examined with the model and open to allow sub-model reuse and refinement. The multi-paradigm modeling framework presented here offers this capability. The goal of this modeling framework is to create a dynamic and flexible modeling environment that allows for the level of abstraction of each sub-system to differ and evolve, creating a model which can be used to evaluate how changes in one system can affect other linked systems at differing time-scales and levels of aggregation. The framework is particularly useful for modeling systems that are not yet fully defined due to the flexibility inherent in the approach and the concept of technology pipelines for modeling endogenous technological change has also been introduced to model technological progression. The introduction of PHEVs to the transportation system will provide a strong link between it and the electricity system, dramatically changing both systems. Before policies that regulate this transformational technology are enacted it is critical that the limits of the system are examined to prevent the propagation of unintended consequences. Detailed electricity supply and demand models have been developed and combined with a transportation simulator in order to gauge the impact of PHEV introduction on electricity load profiles and vehicle emissions. In addition, the ability of a complementary technology, vehicle-to-grid power systems, to aid in the integration of large amounts of wind power into the electricity system has been examined. Finally, since the intermittency of wind energy is the chief obstacle towards expanded wind power integration, statistical methods for wind forecasting over large geographic areas have been investigated.
Pekny, Purdue University.
Chemical engineering|Industrial engineering|Energy|Operations research
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