Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity

Abstract

Conventional environmental-economic power dispatch methods constrain the total amount of emissions of power plants, and they succeed in reducing emissions from the power sector. However, they fail to address the mismatch between emission reductions and the resulting changes in regional air quality. This paper proposes an ecology-and security-constrained unit commitment (Eco-SCUC) model considering the differentiated impacts of generation-associated emissions on regional air quality. A Gaussian puff dispersion model is applied to capture the temporal-spatial transport of air pollutants. Additionally, an air pollutant intensity (API) index is defined for assessing the impacts of emissions on the air quality in regions with differentiated atmospheric environmental capacities. Then the API constraints are formulated based on air quality forecast and included in SCUC model. Moreover, the stochastic optimization is employed to accommodate wind power uncertainty, and the Benders decomposition technique is used to solve the formulated mixed-integer quadratic programming (MIQP) problem. Case studies demonstrate that the Eco-SCUC can cost-effectively improve air quality for densely-populated regions via shifting generation among units and can significantly reduce the person-hours exposed to severe air pollution. Furthermore, the benefits of wind power for air quality control are investigated.

Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis

“…In the study and application of the Gaussian model [17][18][19], some focus is done on the issue of gas diffusion with the known emission source. The default coordinate system is set up taking the emission source as the origin, and the wind direction, and its vertical relations as axes.…”

Dispatch for Urban Integrated Heat and Power System Considering Secondary PM2.5 Under Smart Environmental Sensing

“…The operation of the SCR system is mainly based on the catalyst. When the units are running at low power output, the catalyst is degraded due to the low temperature [28]. At this time, the SCR system needs to be shut down, resulting in a significant increase in emissions.…”

“…To this end, some scholars have established a temporal and spatial distribution (TSD) model of pollutant emissions from power systems, shifting research focus from total pollutant control to optimization of GLC [26] uses the Gaussian plume diffusion model to simulate the diffusion of PM2.5 generated by the power system and incorporates it into the unit combination through differentiated environmental capacity costs. The Gaussian puff model used in [27], [28] is an extension of the Gaussian plume model, which is more suitable for small calm wind weather, and can improve the accuracy of pollutants TSD in haze weather [29] further considered the influence of atmospheric boundary layer (ABL) and attenuation benefits on pollutant dispersion, established a TSD model for various pollutants, and proposed a high-dimensional multi-objective optimization method; Based on this model, [30] developed a multi-objective EED strategy for the power-natural gas integrated energy system. However, the research using pollutant diffusion models to study the environmental benefits of CHP units has not been reported.…”

Sustainable Energy Development under Climate Change

“…The central theme of the Guo et al paper [15] involves the mismatch between emission reductions and the resulting changes in regional air quality. The authors propose an ecology-and security-constrained unit commitment (Eco-SCUC) model that integrates both air quality intensity (API) and stochastic wind power constraints to improve emissions modeling.…”