Many-Objective Optimal Power Dispatch Strategy Incorporating Temporal and Spatial Distribution Control of Multiple Air Pollutants

Abstract

Traditional economic/environment dispatch usually aims to reduce emission, but neglects air pollutant dispersion and lacks target-oriented control. This paper proposes a many-objective optimal power dispatch (MaOOPD) strategy incorporating temporal and spatial distribution (TSD) control of multiple air pollutants. Ground level concentration, i.e., the TSD, of air pollutant is estimated by a novel air pollutant dispersion model specifically constructed for thermal power plants. A MaOOPD model is developed to cut generation cost, reduce CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission, and control the TSD of PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> , SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , and NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> simultaneously. To determine a compromise solution, a decision-making method which exploits atmospheric environmental capacity margin is employed, so that actual needs of atmospheric environmental protection are captured. Case studies indicate that not only can the strategy reduce air pollution effectively, but also it can achieve a dynamic tradeoff among the objectives as weather conditions and background pollution vary, leading to an authentic economic environmental power dispatch.