Combined municipal solid waste and biomass system optimization for district energy applications
Rentizelas, A.A. and Tolis, A.I. and Tatsiopoulos, I.P. (2014) Combined municipal solid waste and biomass system optimization for district energy applications. Waste Management, 34 (1). 36–48. ISSN 1879-2456 (https://doi.org/10.1016/j.wasman.2013.09.026)
Preview |
PDF.
Filename: WM_manuscript_with_title_page_REVISED_Clean_PURE.pdf
Accepted Author Manuscript Download (1MB)| Preview |
Abstract
Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.
ORCID iDs
Rentizelas, A.A. ORCID: https://orcid.org/0000-0002-5110-2467, Tolis, A.I. and Tatsiopoulos, I.P.;-
-
Item type: Article ID code: 45855 Dates: DateEventJanuary 2014Published17 October 2013Published OnlineSubjects: Technology > Engineering (General). Civil engineering (General) Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 13 Nov 2013 10:03 Last modified: 11 Nov 2024 10:33 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/45855