Waste incineration and heat recovery hybridized with low-focus fresnel lens solar collectors for sustainable multi-generation; A thorough techno-economic-environmental analysis and optimization.

Biomass, including municipal solid waste, and solar energy are two of the inevitable sources for future decarbonized energy systems. Fresnel lens thermal collectors using cheap micro-structured foils is an interesting emerging medium-temperature solar thermal design that might be of high practical value, provided that its fluctuating output is managed. This study proposes a hybrid solar-waste solution using this type of collector for multi-generation via an Organic Rankine Cycle. The cycle is specially designed for supplying low-grade heat, power, and industrial heat (which is a very critical sector to be decarbonized) taking advantage of the generated stable solar-waste medium-temperature heat at zero emission level. To achieve this optimal design, the article conducts a thorough energy-exergy-economic-environment (4E) analysis of the system and employs the non-dominated sorting genetic algorithm (NSGA II) for the optimizations. A benchmarking analysis is also conducted to show the importance of industrial heat supply in this cycle. The results show that this hybridization, owing to the cheap and flexible heat delivery of the waste incinerator as well as the low cost of the solar collectors, is very effective for efficient and cheap multi-generation. Especially for industrial heat supply, the competitive levelized cost of energy (LCOE) of 23.96 €/MWh is obtained, which is way lower than today's achievable costs in the industry.

Inspection and maintenance optimization for heterogeneity units in redundant structure with Non-dominated Sorting Genetic Algorithm III.

Redundant structure has been widely deployed to improve system reliability, as when one unit fails, the system can continue to function by using another one. Most existing studies rely on the similar assumption that the heterogeneous units are subject to periodic inspections and identical in terms of their aging situations and the numbers of resisted shocks. In practice, it is often adequate to trigger a unit individually in the event of a single shock, which intensifies the degradation of that unit, accordingly, requiring a sooner inspection to ensure its safety. In this study, the stochastic dependency among units is addressed firstly by introducing a novel activation sequence. Secondly, an adaptive system-level inspection policy is proposed by prioritizing the unit with a worse state. Finally, we take advantage of Monte Carlo methods to simulate the whole process and estimate two objectives, referring to the average system unavailability and maintenance cost, in a designed service time. It is found that the two objectives are contradictory through numerical examples. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) algorithm, therefore, has been employed to find the optimal solutions in system unavailability and cost, which provide clues for practitioners in decision-making.