Optimizing the process of sewage sludge collection for bioenergy generation and biofertilizer production.

The conversion of sludge from sewage treatment plants (STPs) into bioenergy is a promising approach to sustainable energy generation and effective waste management. This process occurs through anaerobic digestion in the biodigesters, resulting in biogas production. However, given that the sludge comes from various STPs in different cities, identifying the ideal locations requires careful selection due to the complexity of sludge management, associated costs, and transportation logistics. In this context, this work aims to formulate a mathematical optimization model to determine the best locations for the installation of sludge processing centers, considering the minimization of the economic, environmental, and social costs. The model is implemented in MATLAB software, and geospatial analysis of the regions of interest is performed using QGIS software. For model validation, three distinct instances are considered. The results obtained demonstrate significant potential in terms of biogas and electricity production, with the highest values for the third instance being 61,997,501 Nm³/year and 149,275 MWh/year, respectively. The proposed methodology represents a crucial step toward sustainability, as it promotes the generation and use of bioenergy from STP sludge and contributes to improved waste management and the prevention of air, soil, and water pollution. • A mixed NLP model is proposed to assist in the process of utilizing sewage sludge. • A genetic algorithm is proposed as a metaheuristic for optimization model solution. • Focus is given to minimizing economic, social, and environmental costs. • Computational experiments with real instances are conducted. [ABSTRACT FROM AUTHOR]