Techno-economic analysis of a biogas-fueled micro gas turbine cogeneration system with seasonal thermal energy storage

•An integrated energy system for meeting electricity and heating demand in a small hotel was investigated.•The models of the core components, including micro gas turbine, seasonal thermal energy storage, and heat pump were developed and validated.•Modelica/Dymola modeling framework was employed to assess techno-economic performance over system's lifetime.•Taguchi method and ANOVA analysis were adopt to reveal significant influence of borehole design factors on energy consumption and NPV. In this study, the techno-economic performance of an integrated energy system, which consisted of a biogas-fueled micro gas turbine, seasonal thermal energy storage using a borehole heat exchanger, and a heat pump for meeting the electricity and heating demand of a small hotel, was carried out. In this proposed system, excess heat from the MGT was charged into the BHE. During the periods of high heating demand, stored waste heat in the ground was extracted by a heat pump. A data-driven model of the MGT based on feed-forward neural networks was developed and validated to provide fast and accurate prediction results. A Modelica/Dymola modeling framework was then established to evaluate the techno-economic performance of the integrated energy system over its lifetime. An L16 orthogonal array given by the Taguchi method was employed to assess the influences of the number of the borehole, the length of the borehole, the distance between boreholes, and the flow rate in the BHE on the energy consumption of the heat pump system, and the NPV of the integrated energy system. First, single objective optimization was performed for both the energy consumption and the NPV separately. The importance order and contribution ratios of the design factors on the performance indicators were determined using the Taguchi and ANOVA methods. Afterward, GRA was used to perform multi-objective optimization of energy consumption and NPV simultaneously. The results showed that, in descending order of importance, the most significant design factors for overall performance were the flow rate in BHE, the length of the borehole, the number of the borehole, and the distance between boreholes. These factors contributed around 68%, 17%, 13%, and 2%, respectively, to the overall results. The optimal combination of parameter levels when considering the multiple performance characteristics was determined as A1B1C1D4, and the optimized energy consumption and NPV were found as around ∼15 GWh and 4 million NOK, re