Publication detail

Review of higher heating value of municipal solid waste based on analysis and smart modelling

Dashti, A., Noushabadi, A.S., Asadi, J., Raji, M., Chofreh, A.G., Klemeš, J.J., Mohammadi, A.H.

Original Title

Review of higher heating value of municipal solid waste based on analysis and smart modelling

Type

journal article in Web of Science

Language

English

Original Abstract

Energy recovery from 252 kinds of solid waste originating from various geographical areas under thermal waste-to-energy operation is investigated. A fast, economical, and comparative methodology is presented for evaluating the heating values resulted from burning municipal solid waste (MSW) based on prior knowledge, specialist experience, and data-mining methods. Development of models for estimating higher heating values (HHVs) of 252 MSW samples based on the ultimate analysis is conducted by simultaneously utilising five nonlinear models including Radial Basis Function (RBF) neural network in conjunction with Genetic Algorithm (GA), namely GA-RBF, genetic programming (GP), multivariate nonlinear regression (MNR), particle swarm optimisation adaptive neuro-fuzzy inference system (PSO-ANFIS) and committee machine intelligent system (CMIS) models to increase the accuracy of each model. Eight different equations based on MNR are developed to estimate energy recovery capacity from different MSW groups (e.g., textiles, plastics, papers, rubbers, mixtures, woods, sewage sludge and other waste). A detailed investigation is conducted to analyse the accuracy of the models. It is indicated that the CMIS model has the best performance comparing the results obtained from different models. The R2 values of the test dataset for GA-RBF are 0.888, for GP 0.979, for MNR 0.978, for PSO-ANFIS 0.965, and for CMIS 0.985. The developed models with an acceptable accuracy would be followed by a better estimation of HHV and providing reliable heating value for an automatic combustion control system. The results obtained from this study are beneficial to design and optimise sustainable thermal waste-to-energy (WTF) processes to accelerate city transition into a circular economy. © 2021

Keywords

Energy recovery; Higher heating value; Municipal solid waste; Regression; Smart modelling; Ultimate analysis

Authors

Dashti, A., Noushabadi, A.S., Asadi, J., Raji, M., Chofreh, A.G., Klemeš, J.J., Mohammadi, A.H.

Released

1. 11. 2021

Publisher

Elsevier, Ltd.

Location

PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND

ISBN

1364-0321

Periodical

RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Number

151

State

United States of America

Pages from

111591

Pages to

111591

Pages count

12

URL

https://www.sciencedirect.com/science/article/pii/S1364032121008686?via%3Dihub

BibTex

@article{BUT172465,
  author="Abdoulmohammad {Gholamzadeh Chofreh} and Jiří {Klemeš}",
  title="Review of higher heating value of municipal solid waste based on analysis and smart modelling",
  journal="RENEWABLE & SUSTAINABLE ENERGY REVIEWS",
  year="2021",
  number="151",
  pages="111591--111591",
  doi="10.1016/j.rser.2021.111591",
  issn="1364-0321",
  url="https://www.sciencedirect.com/science/article/pii/S1364032121008686?via%3Dihub"
}