(372p) Optimal Design and Operation of Biomass Waste Gasification for Energy and Biochar Production

Authors: 
He, X., National University of Singapore
Wang, C. H., National University of Singapore
Yao, Z., National University of Singapore
In recent years, rising interest has been received on applications of waste biomass for energy production due to its renewability and carbon neutrality features. Gasification, which coverts the biomass waste to clean synthesis gas (i.e. syngas), has a high potential in waste processing due to its acceptance of wide variety inputs and attractive product outputs when compared to other existing techniques such as incineration and land-fill. In particular, thermochemical gasification has been proved to be an attractive approach to convert carbonaceous biomass waste to power, heat, cooling and biochar, which has a huge carbon sequestration capability. To explore the best potential of the proposed gasification approach, global optimization for system operation is critical.

In this work, a downdraft gasifier, which has been proved to be a standout choice for medium size throughputs [1], is considered for biomass waste gasification approach. To facilitate the optimization of greenhouse-gas mitigation and economic feasibility of gasification approach, first-principles fix-bed gasification has been developed in MATLAB to simulate the syngas and biochar production. The model employs a three-region assumption based on different fluid velocity profiles, which divided the gasifier into a natural convection region, a forced convection region, and a mixed convection region. The predicted outputs have been validated by experimental data, with a general deviation of less than 10% [2].

Based on the high-fidelity gasification model, a stochastic radial basis function-based global optimization algorithm [3, 4] will be employed to optimize the process operating conditions. In this presentation, a number of decision variables will be considered for optimization, such as biomass feed, moisture content and the equivalence ratio. A multi-objective framework will be considered to maximize energy output and minimize greenhouse gas emission, tackling the trade-off between economic and environmental aspects.

References

  1. You, S., Wang, W., Dai, Y., Tong, Y. W., & Wang, C. H. (2016). Comparison of the co-gasification of sewage sludge and food wastes and cost-benefit analysis of gasification-and incineration-based waste treatment schemes. Bioresource technology, 218, 595-605.
  2. Yao, Z., You, S., Ge, T., & Wang, C. H. (2018). Biomass gasification for syngas and biochar co-production: Energy application and economic evaluation. Applied Energy, 209, 43-55.
  3. Regis, R. G., & Shoemaker, C. A. (2007). A stochastic radial basis function method for the global optimization of expensive functions. INFORMS Journal on Computing, 19(4), 497-509.
  4. Akhtar, T., & Shoemaker, C. A. (2016). Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection. Journal of Global Optimization, 64(1), 17-32.