Biomass Selection Method to Produce Biogas with a Multicriteria Approach
| Autor: | Edward Seabra Júnior, Aldo Braghini Junior, João Carlos Colmenero |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
Environmental Engineering Renewable Energy Sustainability and the Environment Computer science Process (engineering) 020209 energy Biomass 02 engineering and technology Agricultural engineering 01 natural sciences Consistency (database systems) Biogas Ranking Waste production 010608 biotechnology 0202 electrical engineering electronic engineering information engineering Selection method Waste Management and Disposal Selection (genetic algorithm) |
| Zdroj: | Waste and Biomass Valorization. 12:3169-3177 |
| ISSN: | 1877-265X 1877-2641 |
| Popis: | The first step in the biogas production process consists of analyzing how biomass alternatives are available in the locality and in the surroundings of the region where the biodigester is installed to make a selection that serves as an input for the system or food. Each biomass has different sources of nutrients, energy potential, chemical composition, processing, and ways of management that require decision making, which will be the option selected. This is often a problem for handlers, to safely decide which will be the best option for their reality. As a way to contribute to the solution of this problem, this study aimed to propose a mathematical method able to list the main criteria for selecting biomass, establishing a ranking ranging from the most preferable to the least preferable one. For the application of the multicriteria mathematical model (AHP–TOPSIS), the biomass of cattle (bovine), pigs (swine), sheep (ovine), chicken and horses (equine) were used as alternatives, taking into account the following criteria: (1) logistics cost, (2) potential for waste production from each herd, (3) the volume of biogas, and (4) energy capacity of each biomass. It was found a ranking for the alternatives and the consistency of the method was tested through sensitivity analysis. |
| Databáze: | OpenAIRE |
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