Considering the Differentiating Health Impacts of Fuel Emissions in Optimal Generation Scheduling

Thermal power generation could exhibit a considerable level of fuel emissions with a significant threat to human health. Due to variations in weather and atmospheric conditions, the time, the location, and the level of fuel emissions could determine emissions' differentiating impacts on ambient air pollutant concentration (AAPC). The densely populated regions are more vulnerable to changes in AAPC because the associated health impacts can scale up log-linearly with AAPC and linearly with affected population sizes. This paper proposes an approach to evaluate the differentiating impacts of fuel emissions on AAPC and human health. The proposed approach applies the day-ahead hourly generation scheduling for reducing AAPC in densely populated regions. We employ a Gaussian puff model to address the source-receptor relationship among fuel emissions and resulting AAPC increments (ΔAAPC). We formulate a penalty cost for fuel emissions, which reflects the marginal health impacts of individual fuel emissions and differentiates the emission dispatch by shifting the electricity production away from power plants with high marginal health impacts. The proposed approach captures the ΔAAPC response to changes in generation scheduling and incorporates the marginal health impacts of fuel emissions into daily decision-making processes. Case studies demonstrate the effectiveness of the proposed model in which differentiating environmental benefits of wind power generation and energy storage are illustrated in power generation scheduling.