Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion

Air pollution problems are attracting increasing attention, especially among the developing countries with frequent haze events. Renewable energy sources such as wind power are expected to help relieve such environmental concerns. However, air pollution issues under such a changing energy structure receive inadequate attention. Mostly, constraints for total pollutant emissions are considered in unit commitment (UC) and economic dispatch problems. In this paper, we propose a UC model with wind power that considers the dispersion of air pollutants. The dispersion process is described by models involving meteorological conditions and the system's geographical distribution, to estimate the spatial distribution of air pollutants, i.e., the concentration of ground-level air pollutants at monitored locations, such as load centers. A penalty cost is introduced based on this estimation. Particulate matter 2.5 μm or less in diameter, the major air pollutant concerning most developing countries, is selected as the focus of this paper. To properly estimate and sufficiently utilize the benefits of wind power for air pollutant dispersion control, robust optimization is applied to accommodate wind power uncertainty. Case studies justify this consideration of air pollutant dispersion, and demonstrate the effectiveness of the proposed model for improving load centers' air pollution control and utilizing wind power benefits.