Abstract
Air pollution is one of the main environmental issues. This paper proposes an environmental-economic unit commitment model (EEUC) incorporating a novel robust diffusion control of gas pollutants. The control mode evaluates the space-time diffusion of gas emissions, and then reduces the contribution of the thermal power generation to the gas pollutant concentration. To handle the meteorological condition uncertainty in the gas diffusion, the proposed EEUC is derived as a constraint-based robust optimization problem. The strategy optimizes the expected objective of the empirical distribution, together with a limitation on the worst objective induced by the uncertainty set, such that the overall effectiveness is prioritized with an adjustable robustness. To tackle the nonconvex gas diffusion, an improved scenario-based uncertainty set composed of both the historical observation and sampled scenarios is developed, using a Nataf conversion-based data-driven method. Finally, a tailored column-and-constraint generation solution is developed to solve the uncertain problem. Case studies demonstrate that, the robust diffusion control can reduce the air pollution in the meteorological condition uncertainty, and the overall effectiveness and robustness are balanced by the constraint-based robust optimization.
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