A Many-Objective Optimization for an Eco-Efficient Flue Gas Desulfurization Process Using a Surrogate-Assisted Evolutionary Algorithm
| Autor: | Ziting Wang, Cui Wang, Shitong Peng, Quande Dong, Conghu Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Optimization problem
Power station Computer science Geography Planning and Development Evolutionary algorithm NSGA-III TJ807-830 Management Monitoring Policy and Law TD194-195 Renewable energy sources Surrogate model many-objective optimization GE1-350 Process engineering Environmental effects of industries and plants Renewable Energy Sustainability and the Environment business.industry Process (computing) Kriging model TOPSIS eco-efficiency Flue-gas desulfurization Environmental sciences data-driven modeling business Efficient energy use |
| Zdroj: | Sustainability Volume 13 Issue 16 Sustainability, Vol 13, Iss 9015, p 9015 (2021) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su13169015 |
| Popis: | The flue gas desulfurization process in coal-fired power plants is energy and resource-intensive but the eco-efficiency of this process has scarcely been considered. Given the fluctuating unit load and complex desulfurization mechanism, optimizing the desulfurization system based on the traditional mechanistic model poses a great challenge. In this regard, the present study optimized the eco-efficiency from the perspective of operating data analysis. We formulated the issue of eco-efficiency improvement into a many-objective optimization problem. Considering the complexity between the system inputs and outputs and to further reduce the computational cost, we constructed a Kriging model and made a comparison between this model and the response surface methodology based on two accuracy metrics. This surrogate model was then incorporated into the NSGA-III algorithm to obtain the Pareto-optimal front. As this Pareto-optimal front provides multiple alternative operating options, we applied the TOPSIS to select the most appropriate alternative set of operating parameters. This approach was validated using the historical operation data from the desulfurization system at a coal-fired power plant in China with a 600 MW unit. The results indicated that the optimization would cause an improvement in the efficiency of desulfurization and energy efficiency but a slight increase in the consumption of limestone slurry. This study attempted to provide an effective operating strategy to enhance the eco-efficiency performance of desulfurization systems. |
| Databáze: | OpenAIRE |
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