Conference paper Open Access
Royo, Patricia; Acevedo, Luis; Arnal, Alvaro J.; Diaz-Ramírez, Maryori; García-Armingol, Tatiana; Ferreira, Victo J.; Ferreira, Germán; López-Subirón, Ana M.
Waste heat recovery is one of the solutions included in the roadmap for reducing both energy consumption and the carbon footprint. Its high replication capacity in steel, ceramics, pulp and paper, and other energy-intensive industries favours the efficiency of the process and, consequently, achieves reductions in consumption, pollution and the equipment size and cost. As a result, the large-scale deployment of those innovative technologies is determinant for achieving energy efficiency and climate changes objectives in an effective and efficient manner. In this vein, VULKANO and RETROFEED projects implements and validates an advanced retrofitting solution to improve the overall efficiency and reduce emission in intensive sectors. On this route, a novel high-temperature Phase Change Materials (PCMs)-based thermal energy storage system (TES) for industrial furnaces is evaluated to increase the energy and environmental efficiency by recovering waste heat from the combustion gases. Design details such as preliminary sizing, costs and conceptual design configuration is presented as an example of integration at industrial scale, adapted to the plant operational requirements, by searching the best conceptual design and a proper selection of core materials. A multicriteria analysis is developed and applied to select the most profitable system configuration. The methodology is based on technical indicators, that is, life cycle assessment, life cycle cost, and techno-economic analysis, to assess both the status quo of existing gas furnaces and their modification after incorporating the PCM-TES. The potential for improving efficiency, reducing environmental impact and cost savings is determined by implementing the waste heat recovery system. Consequently, this methodology considers and integrates the analysis of horizontal and vertical value chain that can be used as a prefeasibility analysis based on a decision support tool for defining reproducibility and replicability.
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