Selection of waste-to-energy technology for distributed generation using IDOCRIW-Weighted TOPSIS method: A case study of the City of Johannesburg, South Africa

Abstract Waste-to-energy has evolved as a promising solution for sustainable power generation as well and waste management. To effectively harness the potential of the waste-to-energy technologies in a sustainable manner, an optimal choice among the diverse technologies is highly essential. The multi-dimensional nature of waste management makes selection of appropriate waste-to-energy option a complex problem. Therefore, a simple and computationally efficient decision tool is required to aid decision making. In this paper, a novel hybrid multi-criteria method based on IDOCRIW and TOPSIS are proposed for optimal selection of the appropriate waste-to-energy technologies for distributed generation. Fourteen criteria were considered spanning through technical, economic, environmental and social factors. Five technologies such as anaerobic digestion, landfill gas recovery, incineration, pyrolysis and gasification were selected due to their level of maturity and availability. The proposed model was tested using the City of Johannesburg, South Africa as a case study. The overall results indicated that anaerobic digestion is the most attractive technology with a relative closeness of 0.9724 to the ideal solution while incineration is ranked worst with a closeness of 0.6474 to the ideal solution. The result also revealed that the integration of anaerobic digestion and gasification could be more promising in terms of waste management. It could also be a good candidate for distributed generation in a microgrid application by serving as a local power generator when integrated to waste management systems of the City of Johannesburg.

[1]  Imran Khan,et al.  Waste-to-energy generation technologies and the developing economies: A multi-criteria analysis for sustainability assessment , 2020 .

[2]  P. Jeetah,et al.  Energy recovery from municipal solid waste in Mauritius: Opportunities and challenges , 2020 .

[3]  R. Prasad,et al.  Assessing the sustainable municipal solid waste (MSW) to electricity generation potentials in selected Pacific Small Island Developing States (PSIDS) , 2020 .

[4]  Nizar Bel Hadj Ali,et al.  Comparing Multi-Criteria Decision aid methods through a ranking stability index , 2013, 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO).

[5]  Temitope Raphael Ayodele,et al.  Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria , 2020 .

[6]  Valentinas Podvezko,et al.  Integrated Determination of Objective Criteria Weights in MCDM , 2016, Int. J. Inf. Technol. Decis. Mak..

[7]  Lyes Benyoucef,et al.  A consensus based group decision making methodology for strategic selection problems of supply chain coordination , 2013, Eng. Appl. Artif. Intell..

[8]  S. Chowdhury,et al.  Technical and economic assessment of power generation from landfill gas in South Africa , 2011, 2011 IEEE Power and Energy Society General Meeting.

[9]  A. Abedian,et al.  Introducing a novel method for materials selection in mechanical design using Z-transformation in statistics for normalization of material properties , 2009 .

[10]  Deborah Panepinto,et al.  Solid waste and biomass gasification: fundamental processes and numerical simulation , 2011 .

[11]  Haslenda Hashim,et al.  Optimal Planning of Waste-to-Energy through Mixed Integer Linear Programming , 2013 .

[12]  T. Ayodele,et al.  Effect of collection efficiency and oxidation factor on greenhouse gas emission and life cycle cost of landfill distributed energy generation , 2020 .

[13]  Ming-Shin Kuo,et al.  A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines , 2011 .

[14]  E. Dahl,et al.  Disentangling the dynamics of social assistance: A linked survey—Register data cohort study of long-term social assistance recipients in Norway , 2020, PloS one.

[15]  N. A. Adewole,et al.  Charcoal Yield from Urban-Tree Residues Generated in University of Ibadan, Nigeria using Earth Mound Method , 2016 .

[16]  Abbas Rohani,et al.  Identification of effective factors to select energy recovery technologies from municipal solid waste using multi-criteria decision making (MCDM): A review of thermochemical technologies , 2020 .

[17]  Chuan Yue,et al.  Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations , 2017, Appl. Soft Comput..

[18]  Lidia Lombardi,et al.  Evaluation of the environmental sustainability of different waste-to-energy plant configurations. , 2017, Waste management.

[19]  Roland Clift,et al.  Distributed generation by energy from waste technology: A life cycle perspective , 2015 .

[20]  Dragan Pamučar,et al.  New model for determining criteria weights: Level Based Weight Assessment (LBWA) model , 2019, Decision Making: Applications in Management and Engineering.

[21]  P. N. Mabalane,et al.  A Techno-economic Analysis of Anaerobic Digestion and Gasification Hybrid System: Energy Recovery from Municipal Solid Waste in South Africa , 2020 .

[22]  Atiq Uz Zaman,et al.  Comparative study of municipal solid waste treatment technologies using life cycle assessment method , 2010 .

[23]  D. Marinković,et al.  Objective methods for determining criteria weight coefficients: A modification of the CRITIC method , 2020 .

[24]  T. Ogwueleka.  MUNICIPAL SOLID WASTE CHARACTERISTICS AND MANAGEMENT IN NIGERIA , 2009 .

[25]  Y. Hamam,et al.  Selection of a Hybrid Renewable Energy Systems for a Low-Income Household , 2019, Sustainability.

[26]  Prasanta Kumar Dey,et al.  Evaluation of options for energy recovery from municipal solid waste in India using the hierarchical analytical network process , 2013 .

[27]  Laith A. Hadidi,et al.  A financial feasibility model of gasification and anaerobic digestion waste-to-energy (WTE) plants in Saudi Arabia. , 2017, Waste management.

[28]  S. Jafari,et al.  On Generalized Closed Sets and Generalized Pre-Closed Sets in Neutrosophic Topological Spaces , 2018, Mathematics.

[29]  Sarfaraz Hashemkhani Zolfani,et al.  A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment , 2013 .

[30]  Rosli Mohamad Zin,et al.  A hybrid approach using entropy and TOPSIS to select key drivers for a successful and sustainable lean construction implementation , 2020, PloS one.

[31]  K. Mpofu,et al.  An approach for enhancing optimal resource recovery from different classes of waste in South Africa: Selection of appropriate waste to energy technology , 2020 .

[32]  Ashok Pandey,et al.  Global Status of Waste-to-Energy Technology , 2019, Current Developments in Biotechnology and Bioengineering.

[33]  H Y Yap,et al.  A multi-criteria analysis of options for energy recovery from municipal solid waste in India and the UK. , 2015, Waste management.

[34]  M. D. Simatele,et al.  Municipal solid waste management in South Africa: from waste to energy recovery through waste-to-energy technologies in Johannesburg , 2019, Local Environment.

[35]  Temitope Raphael Ayodele,et al.  Life cycle assessment of waste-to-energy (WtE) technologies for electricity generation using municipal solid waste in Nigeria , 2017 .

[36]  Gülçin Büyüközkan,et al.  A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers , 2012, Expert Syst. Appl..

[37]  M. Marey-Pérez,et al.  Is phytoremediation without biomass valorization sustainable? - comparative LCA of landfilling vs. anaerobic co-digestion. , 2015, The Science of the total environment.

[38]  Richard D. Gill,et al.  Pearle’s Hidden-Variable Model Revisited , 2015, Entropy.

[39]  A. Abedian,et al.  A novel method for materials selection in mechanical design: Combination of non-linear normalization and a modified digital logic method , 2007 .

[40]  R. V. Rao,et al.  A subjective and objective integrated multiple attribute decision making method for material selection , 2010 .

[41]  Sakshi Kaushal,et al.  The utility based non-linear fuzzy AHP optimization model for network selection in heterogeneous wireless networks , 2018, Appl. Soft Comput..

[42]  E. Zavadskas,et al.  Optimization of Weighted Aggregated Sum Product Assessment , 2012 .

[43]  Chun-Ho Chen,et al.  A Novel Multi-Criteria Decision-Making Model for Building Material Supplier Selection Based on Entropy-AHP Weighted TOPSIS , 2020, Entropy.

[44]  Y. Oğuz,et al.  Potential evaluation of biomass-based energy sources for Turkey , 2015 .

[45]  Tausif Ali,et al.  Prioritizing the existing power generation technologies in Bangladesh’s clean energy scheme using a hybrid multi-criteria decision making model , 2020 .

[46]  Irina Vinogradova,et al.  Multi-Attribute Decision-Making Methods as a Part of Mathematical Optimization , 2019, Mathematics.

[47]  Deming Wang,et al.  Risk assessment of gas explosion in coal mines based on fuzzy AHP and bayesian network , 2020 .

[48]  T. Ayodele,et al.  Economic and environmental assessment of electricity generation using biogas from organic fraction of municipal solid waste for the city of Ibadan, Nigeria , 2018, Journal of Cleaner Production.

[49]  Ozalp Vayvay,et al.  Solid waste disposal methodology selection using multi-criteria decision making methods and an application in Turkey , 2017 .

[50]  Osman Turan,et al.  An application of fuzzy-AHP to ship operational energy efficiency measures , 2016 .

[51]  Mohammad Rehan,et al.  Effect of plastic waste types on pyrolysis liquid oil , 2017 .

[52]  Mehmet Salih Mamiş,et al.  Utilization of energy from waste potential in Turkey as distributed secondary renewable energy source , 2016 .

[53]  Umberto Arena,et al.  Process and technological aspects of municipal solid waste gasification. A review. , 2012, Waste management.

[54]  Qi Huang,et al.  Performance Analyses of a Renewable Energy Powered System for Trigeneration , 2019, Sustainability.

[55]  Abdolvahhab Fetanat,et al.  Informing energy justice based decision-making framework for waste-to-energy technologies selection in sustainable waste management: A case of Iran , 2019, Journal of Cleaner Production.

[56]  Edmundas Kazimieras Zavadskas,et al.  Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS) , 2015, Informatica.

[57]  Abdullahil Azeem,et al.  Selection of an appropriate waste-to-energy conversion technology for Dhaka City, Bangladesh , 2017 .

[58]  Yanbing Ju,et al.  A novel methodology to select sustainable municipal solid waste management scenarios from three-way decisions perspective , 2021 .

[59]  Imran Khan.  Drivers, enablers, and barriers to prosumerism in Bangladesh: A sustainable solution to energy poverty? , 2019, Energy Research & Social Science.

[60]  Jingzheng Ren,et al.  Waste-to-energy, municipal solid waste treatment, and best available technology: Comprehensive evaluation by an interval-valued fuzzy multi-criteria decision making method , 2018 .

[61]  Luis M. Camarinha-Matos,et al.  Data normalisation techniques in decision making: case study with TOPSIS method , 2018, Int. J. Inf. Decis. Sci..

[62]  Sigit Yoewono Martowibowo,et al.  SUITABLE MULTI CRITERIA DECISION ANALYSIS TOOL FOR SELECTING MUNICIPAL SOLID WASTE TREATMENT IN THE CITY OF BANDUNG , 2011 .

[63]  Valentinas Podvezko,et al.  Operating Characteristics Analysis of Rotor Systems Using MCDM Methods , 2016 .

[64]  Jonathan P. Deason,et al.  Analysis of MCDM methods output coherence in oil and gas portfolio prioritization , 2018, Journal of Petroleum Exploration and Production Technology.

[65]  Danny Simatele,et al.  From informality to formality: Perspectives on the challenges of integrating solid waste management into the urban development and planning policy in Johannesburg, South Africa , 2017 .

[66]  Arun K Narayanan,et al.  Application of SWARA and TOPSIS Methods for Supplier Selection in a Casting Unit , 2018 .

[67]  Y. Chhiti,et al.  Municipal solid waste higher heating value prediction from ultimate analysis using multiple regression and genetic programming techniques , 2019, Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA.

[68]  Valentinas Podvezko,et al.  Evaluation of quality assurance in contractor contracts by multi-attribute decision-making methods , 2017 .

[69]  H. Hashim,et al.  Economic and environmental benefits of landfill gas from municipal solid waste in Malaysia , 2012 .

[70]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[71]  Yskandar Hamam,et al.  Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review , 2020, International Journal of Energy Research.

[72]  J. Rezaei.  Best-worst multi-criteria decision-making method: Some properties and a linear model , 2016 .

[73]  A. Surjosatyo,et al.  Evaluation of Waste Energy Conversion Technology using Analitycal Hierarchy Process in Bantargebang Landfill, Indonesia , 2018 .

[74]  Nicholas E. Korres,et al.  Waste to energy potential: A case study of Saudi Arabia , 2016 .

[75]  Temitope Raphael Ayodele,et al.  Electricity generation from municipal solid waste in some selected cities of Nigeria: An assessment of feasibility, potential and technologies , 2017 .

[76]  W. Stafford.  WtE Best Practices and Perspectives in Africa , 2020 .

[77]  Atul Kumar,et al.  A review on technological options of waste to energy for effective management of municipal solid waste. , 2017, Waste management.

[78]  Yuri Lawryshyn,et al.  The environmental comparison of landfilling vs. incineration of MSW accounting for waste diversion. , 2012, Waste management.

[79]  Jiangjiang Wang,et al.  Weighting methodologies in multi‐criteria evaluations of combined heat and power systems , 2009 .

[80]  S. Friel,et al.  Modelling the Food Availability and Environmental Impacts of a Shift Towards Consumption of Healthy Dietary Patterns in Australia , 2019, Sustainability.

[81]  G. Nilay Yücenur,et al.  SWARA/WASPAS methods for a marine current energy plant location selection problem , 2021 .

[82]  Bernard W. Ikua,et al.  Selection of optimum fish oil fuel blend to reduce the greenhouse gas emissions in an IC engine—A hybrid multiple criteria decision aid approach , 2016 .

[83]  Horacio Terraza,et al.  Guidance Note on Landfill Gas Capture and Utilization , 2010 .

[85]  M. Effenberger,et al.  Environmental impacts concerning flexible power generation in a biogas production , 2019, Carbon Resources Conversion.