Precise Ammonia Injection Optimization Method for SCR Denitrification System Based on DE-SQP Hybrid Algorithm

To enhance the uniformity of$\text{NO}_{\mathrm{x}}$concentration at the selective catalytic reduction (SCR) denitrification system outlet in coal-fired power plants and improve the response performance of the precise ammonia injection process, a DE-SQP hybrid optimization method combining differential evolution (DE) algorithm and sequential quadratic programming (SQP) algorithm is introduced for the precise ammonia injection optimization problem of SCR denitrification system under multi-constraint conditions. Based on the stochastic distribution control theory, the probability density function (PDF) description framework of$\text{NO}_{\mathrm{x}}$concentration distribution at the SCR denitrification system outlet is constructed, and a fast and stable PDF weight prediction model is established by using Extreme Learning Machine (ELM). Combining the advantages of strong global optimization ability of DE algorithm and strong local accurate search ability of SQP algorithm, DE algorithm is used to generate high-quality initial solution, and then SQP algorithm is used to realize local accurate solution. The optimal valve opening of each partition of ammonia injection grille (AIG) is obtained, and the optimal solution of precise ammonia injection in SCR denitrification system is realized. The simulation results show that the relative standard deviation (RSD) of NO concentration at the outlet of SCR denitrification system is reduced from 26.6269% to 14.9374% after the precise ammonia injection optimization of SCR denitrification system by DE-SQP hybrid optimization method, which effectively improves the uniformity of$\text{NO}_{\mathrm{x}}$concentration at the SCR denitrification system outlet, and provides an efficient and feasible scheme for the optimization of precise ammonia injection of SCR denitrification system.