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Abstract
Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems. For soft computing applications, nature-inspired techniques have several advantages, including scope for parallel computing, dynamic behavior, and self-organization. This paper presents a comprehensive review of such techniques and their application in anaerobic digestion modeling. We compiled and synthetized the literature on the applications of nature-inspired techniques applied to anaerobic digestion. These techniques provide a balance between diversity and speed of arrival at the optimal solution, which has stimulated their use in anaerobic digestion modeling.
Highlights
With the onset of urbanization, waste management has become a global crisis
First: Which is the best algorithm for the given problem? Second: Which problems can be solved with the chosen algorithm? This paper analyzed the existing recent artificial intelligence techniques, keeping in mind their computational ability, shortcomings, adaptability to work in parallel with other algorithms, and processing time
Nature-inspired algorithms are a preferred area of computing, as anaerobic digestion deals with large number of variables and has non-linearity, and traditional modeling techniques cannot handle such diversity
Summary
With the onset of urbanization, waste management has become a global crisis. Keeping in mind the growing energy requirement, the need of the hour is to concentrate on low-carbon technologies that do not exacerbate the global warming problem. Anaerobic digestion (AD) is one such process, which reduces waste and produces energy in the form of biogas. The aim of using this technology for waste treatment is to put the energy content of biogas, methane, into uses such as combined heat and power (CHP), vehicle fuel, boilers, kitchen stoves, or injection into the natural gas grid. Municipal sewage sludge has a low nitrogen content, and has a higher C/N ratio of 40–70 [9], which makes it a good source for biogas generation. The high moisture content in the sludge leads to lower methane yield [11], which calls for co-digestion with organic wastes with highly degradable carbon content. Anaerobic digestion being a very sensitive process, long-term use of a single substrate can lead to nutrient deficiency. The objective of this paper was to evaluate various modeling techniques for anaerobic digestion
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