Energy and Air Pollution Modeling for Cities: A Case Study on Cuba

Nowadays, energy consumption is dominated by fossil fuels. This situation leads to a large number of environmental problems intensifying climate change and human health risks. Scenario analysis through modeling can help design less-pollutant energy strategies. A general assessment is that there is a potential for these risks to be managed by a wider integration of renewable resources. The concern with renewable systems stems in the fact that resources such as wind and solar are characterized by a large degree of intermittency driven by natural variability of climate factors.

In this poster, we present the implementation of an energy and air pollution modeling system which allows to study energy strategies of a given region, including penetration of intermittent resources. It includes a simplified approach usually referred to as source-receptor relationship that forecasts air pollution impacts with a good level of accuracy considering annual average concentrations of PM25, NOx and ozone. Time series simulations that include an intermittent electricity supply coupled with storage and backup utilities allow for rapid estimations of a progressive intermittent deployment. The modeling sizes the components and offers an outlook on how to manage such an energy system, with indices of maximum backup and storage capacity required, as well as the conventional resources required at any given penetration level of intermittent resources.

The developed modeling system is implemented in Cuban cities, and general design features toward a reliable energy transition are revealed.