An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem.

The dispatching of hydro-thermal system is a nonlinear programming problem with multiple constraints and high dimensions and the solution techniques of the model have been a hotspot in research. Based on the advantage of that the artificial bee colony algorithm (ABC) can efficiently solve the high-dimensional problem, an improved artificial bee colony algorithm has been proposed to solve DHTS problem in this paper. The improvements of the proposed algorithm include two aspects. On one hand, local search can be guided in efficiency by the information of the global optimal solution and its gradient in each generation. The global optimal solution improves the search efficiency of the algorithm but loses diversity, while the gradient can weaken the loss of diversity caused by the global optimal solution. On the other hand, inspired by genetic algorithm, the nectar resource which has not been updated in limit generation is transformed to a new one by using selection, crossover and mutation, which can ensure individual diversity and make full use of prior information for improving the global search ability of the algorithm. The two improvements of ABC algorithm are proved to be effective via a classical numeral example at last. Among which the genetic operator for the promotion of the ABC algorithm's performance is significant. The results are also compared with those of other state-of-the-art algorithms, the enhanced ABC algorithm has general advantages in minimum cost, average cost and maximum cost which shows its usability and effectiveness. The achievements in this paper provide a new method for solving the DHTS problems, and also offer a novel reference for the improvement of mechanism and the application of algorithms.

Modeling assessment for ammonium nitrogen recovery from wastewater by chemical precipitation.

Chemical precipitation to form magnesium ammonium phosphate (MAP) is an effective technology for recovering ammonium nitrogen (NH4(+)-N). In the present research, we investigated the thermodynamic modeling of the PHREEQC program for NH4(+)-N recovery to evaluate the effect of reaction factors on MAP precipitation. The case study of NH4(+)-N recovery from coking wastewater was conducted to provide a comparison. Response surface methodology (RSM) was applied to assist in understanding the relative significance of reaction factors and the interactive effects of solution conditions. Thermodynamic modeling indicated that the saturation index (SI) of MAP followed a polynomial function of pH. The SI of MAP increased logarithmically with the Mg2+/NH4+ molar ratio (Mg/N) and the initial NH4(+)-N concentration (CN), respectively, while it decreased with an increase in Ca2+/NH4+ and CO3(2-)/NH4+ molar ratios (Ca/N and CO3(2-)/N), respectively. The trends for NH4(+)-N removal at different pH and Mg/N levels were similar to the thermodynamic modeling predictions. The RSM analysis indicated that the factors including pH, Mg/N, C(N), Ca/N, (Mg/N)x (CO3(2-)/N), (pH)2, (Mg/N)2, and (C(N))2 were significant. Response surface plots were useful for understanding the interaction effects on NH4(+)-N recovery.