Optimal Environmental Economic Power Dispatch Considering Carbon Footprint And Meteorological Diffusion Of Air Pollutants

Global warming and air pollution are two major threats to human existence in the world today.Large amounts of greenhouse gases and air pollutants are emitted from thermal power generation by burning fossil fuels.The former is represented by CO₂,while the latter PM2.5?SO₂ and NO₂.As one of the most major sources,electricity industry acts an important part in low-carbon and low-air pollution development.Recently,economic/environmental power dispatch has drawn an increasing attention from researchers due to its significant merits of high efficiency and not requiring additional construction costs.The amount of emitted CO₂ directly effects atmosphere's ability to absorb the long wave radiation and to warm the ground surface,so that the emission limitation strategy is indeed effective for the global warming mitigation.But for the air pollutants such as PM2.5?SO₂ and NO₂,it is not the emission but the ground level concentration?GLC?that really matters.This paper focuses on this essential difference and tries to mitigate global warming and atmospheric pollution caused by electric power industry from the perspective of emission control and GLC control,respectively.As for the optimal EED considering carbon emission reduction,the generated electricity and carbon emission are determined by consumers'demand and power loss at the transmission and distribution side?i.e.,the power grid companies?.Therefore,the responsibility of carbon emission reduction should be allocated to the generation side,power grid companies and the consumers fairly,although CO₂ is appears to be emitted from the generation side.To handle this issue,a carbon-energy combined-flow model is constructed which incorporates carbon footprint tracing,to study the carbon emission reduction responsibility lying in the power grid companies and thus simulate their potential.As for the optimal EED considering GLC,air pollutants experiences complex physical and chemical changes after being emitted.Atmospheric conditions also exert a tremendous influence on the GLC of air pollutants.Besides,the atmosphere itself has a capacity to accommodate a certain amount of air pollutants.Thus,an EED model is constructed in this paper considering air pollutant dispersion,which can identifies the most dangerous thermal power plants by analyzing the dispersion of the air pollutants they emitted and thus conduct a target-oriented control.In addition,the space-varying atmospheric environmental capacity is utilized,to make an adaptable generation plan in the presence of various weather condition.As a result,a trade-off between economy and environmental protect can be achieved which can help to accelerate the low-carbon and low-air pollution development.Besides,in order to solve the above models efficiently,this paper explores the fields of reinforcement learning,transfer learning and many-objective evolutionary algorithm.Novel algorithms are proposed specifically,whose performance are tesed by conducting case studies on benchmark models and practical models.Finally,multiple novel strategies are provided for EED in practical power system,which have important theoretical significance and practical value.