No abstract

No abstract

No abstract

A prototype for mechanizing the asphalt roofing process was developed. In this manuscript, we present the design, manufacturing, preliminary thermal test, and operation test of the equipment. The innovation is sustained by the use of infrared radiators instead of fuel burners. Infrared heaters provide optimal clean heat transfer to asphalt rolls in comparison to fuel burner automated systems since the latter generates a significant amount of CO2, SO2, and other non-ecofriendly emissions close to workers. Moreover, the equipment has several advantages with respect to manual installation, such as roofing capacity, cleanness, safety, uniformity, and environment-friendliness. It demonstrates an installation speed of 1 m/min, on average, for 3 kg/m2 rolls, which leads to around 400–420 m2 per person a day, more than the usual manual roofing rate. However, there are some issues that need to be resolved, such as inaccurate unrolling and/or bad adhesion gaps.

In this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.