An enviro-economic RAM-based optimization of biomass-driven combined heat and power generation

Abstract

AbstractInherent uncertainties of biomass-driven systems including seasonality, supply chain problems, and energy conversion limitations put reliability and availability of such systems under question. The optimization of the energy systems taken into account the reliability, availability and maintainability (denoted by RAM), parameters, and constraints can dramatically change the system design, configuration, and operation. An enviro-economic optimization of biomass-powered energy systems, considering the impact of the reliability and maintainability parameters in the final optimal cost of the energy generation and after-commissioning operation, is pinpointed in this study. The objective function was developed as an explicit function to provide the system performance parameters such as rated capacities and utilization times and reliability elements such as maintenance intervals and mean time to failure (denoted by MTTF) as independent parameters for the multivariable nonlinear optimization problem. Such parameters are then used for deriving maintainability and availability parameters such as mean time to repair (denoted by MTTR) to assure the required availability levels. Developing a methodology to be used for performing the same analysis for other configurations using distinguished energy systems, storage or biomass fuel is another problem that was considered in this research. The results showed that integrating RAM parameters to optimization analysis still keeps the biomass-fueled systems competitive economically with other energy systems. The study showed that a biomass-powered system is more sensitive to electrical module performance parameters than to thermal module and biomass types. Furthermore, thermal module requires more frequent maintenance activities in comparison with electrical module in order to retain a system reliability level above the thresholds. Moreover, reliability can be integrated as a nonlinear constraint into the above-mentioned optimization problem, resulting in optimal rated capacities closer to maximum nominal capacities in case of electrical module. RAM integration to optimization changes the performance parameters of an enviro-economic optimization analysis. The sensitivity to parameters and approaches could be high, and other fuels, technologies, or system configurations shall be considered to deliver more confident results.