New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations

Significance The production of electricity from coal, natural gas, petroleum, and biomass releases air pollutants with significant impacts on ecosystems and human health. Pollutant exposure depends not only on the pollutant source emissions rate and the relative location of the power plant to population centers but also on temperature, wind velocity, and other atmospheric conditions, all of which vary by hour, day, and season. We have developed a method to evaluate fluctuating pollutant formation from source emissions, which we integrate within an electricity production model. In a case study of the state of Georgia from 2004 to 2011, we show how to reduce air pollutants and health impacts by shifting production among plants during a select number of hourly periods. Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004–2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.