Fuel gas control plan for energy enterprises taking into account emissions stability disorders

Abstract

This study focuses on planning and forecasting the control of flue gases of large energy-consuming enterprises.  The occurrence of random technological violations provokes randomness of emissions, violation of environmental standards, economic sanctions and fines, leading to environmental degradation. A mathematical model of planning and forecasting extreme emissions in random processes of flue gas pollution of energy companies with a correction for non-stationarity of processes has been developed. A procedure for parametric testing of a multicomponent process of contamination in the case of multi-parameter control with regard to its extrapolated values is described. The use of an adjusted, in the direction of increasing the mathematical expectation, a model of extrapolation of the 2nd order, reduces the risk of control of the 2nd order, with parametric testing of the results of multidimensional extrapolation. Reducing the risk of control increases the power of the decision rule and makes the application of the described adjusted extrapolation procedure statistically justified and preferable to other extrapolation procedures. It is advisable when planning and predicting the control of emissions and discharges of energy-intensive enterprises to use testing based on the decision rule based on the developed criterion, which ensures the specified accuracy. Evaluation of the stationarity and spectral features of the contamination processes under study will reduce the a priori uncertainty and provide an opportunity to improve the flue gas control procedure. The choice of the decision rule based on the criterion that ensures the specified accuracy of the control will allow to investigate the correlation connectivity of the monitored process and to develop a statistically based method for choosing the interval of its discretization. This approach ensures the minimization of those risks that determine the level of economic losses in case of violations of stationarity. The proposed control model can be used for environmental monitoring of emissions of energy-intensive enterprises into the atmosphere.