Study And Application Of Whole Process Optimization Of Active Coal Blending For Power Plant

The supply for coal-fired thermal power plants is extremely complex in our country. Most plants utilize multi-coals blending technology to stabilize coal quality. The past domestic studies for coal blending were limited to passive blending. While as the domestic coal supply market situation changes, the plants have get rid of coal tight supply situation, hence the plants can actively select suitable coals according to the requirements of environment, economic and safety for themselves, By adopting the whole supply chain active coal blending method, the power plants can achieve collaborative optimization for environmental, economic and safety index, explore the environmental, economic and safety potential of coal-blending, enrich blended coal combustion technology.This article proposes a whole supply chain management and decision-making model of active coal blending for coal-fired power plants. The management model contains coal ship transportation management, fuel acceptance, unloading management, and spontaneous combustion management in coal yard; the decision-making model includes purchasing decision model, intelligent stacking/coaling model, intelligent blending model, and dynamic bunker monitoring model.This paper researches the calculation model of decision-making in whole supply chain active coal blending for power plants. Firstly, a coal blending "coal – emissions- boiler" coupled mathematical model was established, based on the coal quality and emission requirements of boilers, and described in three objectives functions target for environmental, economic, and safety. Secondly, genetic algorithm is adopted into the solving process. The results show genetic algorithm is highly efficient in solving, but often accompanied with errors. Therefore, appropriate optimization algorithm should be selected based on the size of the solution space in practical application. Taking a 600 MW opposed firing boiler for the study, oxygen optimization is conducted under coal blending condition. The result shows that CO concentration in flue gas decreases significantly after oxygen optimization, thermal efficiency increases 0.5 to 1.0% correspondingly. In addition, the experimental result shows that the effect of HT-NR3 low NOx swirl burner is too significant; therefore, optimization and adjustment are needed for overfire air proportion during combustion.Based on the model and experimental research, a thermal power plant coal blending whole supply chain system is developed. First, the system framework is built based on MVC architecture, combined with the whole supply chain process to design the workflow of the system; then, advanced programming technology is adopted to develop detailed functional modules, forming a package of software systems; and finally, the system is applied to Guangdong Red Bay Generation Company, creating a considerable economic benefits, management and social benefits.