Use of Thermodynamics, Engineering Economics and Probabilistic Risk Assessment in Evaluating Climate Change Decisions

Climate change is often considered in terms of its macroscale implications. For example, many governments and non-governmental organizations are engaged in the development of policy frameworks that could influence different societal actions and behavioral scenarios. But such macroscale policy decisions may also significantly impact the localized design of products and services in different business ecosystems. Unfortunately, products and services are generally designed only taking into account local influences. An approach that ties macroscale frameworks to localized product- or system-level design metrics is lacking. For example, the cost of upgrading the entire U.S. electrical system has been estimated to be on the order of $200 billion, and recent U.S. policy discussions in the area outline options such as “smart” grid upgrades, distributed and/or on-site renewable energy systems including solar and wind energy, infrastructural support for plug-in of electric and hybrid vehicles etc. But most existing electricity generation and thermal performance models of power generating stations or cogeneration plants fail to provide any indication of the environmental impacts associated with distributing electricity from generator to point-of-use. It is thus not intuitive how the direction of localized plant or system design should be altered given the different macro-level initiatives. This paper attempts to fill this gap by exploring a methodology that combines engineering economics, probabilistic risk assessment, and thermodynamic (2^nd Law) analysis to evaluate different policy choices. Specifically, a framework that could allow quick estimation of the comparative consumption, operational power requirements, relative thermal performance and environmental footprint associated with different proposals on upgrading the grid is developed. The approach is demonstrated in the context of a representative segment of a hypothetical electrical grid distribution system located between two electric power generating stations (EPGS) facing overload as additional customer demands are projected to be integrated with renewable sources in the near-term future.