Techno-economic and environmental analysis of biogas-based hybrid renewable energy systems: A case study for a small-scale livestock farm


AKARSU R. T., KAYATAŞ DEMİR N.

Process Safety and Environmental Protection, cilt.191, ss.1968-1981, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 191
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.psep.2024.09.062
  • Dergi Adı: Process Safety and Environmental Protection
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, Environment Index, Food Science & Technology Abstracts, Greenfile, INSPEC, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1968-1981
  • Anahtar Kelimeler: Anaerobic digestion, Biogas, Dairy farm, Hybrid renewable energy systems
  • Erciyes Üniversitesi Adresli: Evet

Özet

Biogas technology offers a significant benefit in enabling energy generation from distributed sources of biomass through its easy scalability. This study aimed to conduct the technical, economic, and environmental analysis of biogas-based hybrid renewable energy systems in a small-scale livestock farm located in the rural area of the Central Anatolia region in Türkiye. The HOMER software was used to analyze a total of five scenarios. These scenarios are hybrid combinations of a biogas generator, PV panels and wind turbines. The hybrid scenarios were evaluated by comparing them to each other and to the base scenario, which only has a grid connection. The optimal system has been determined to be the grid-connected Biogas/PV panel hybrid configuration, with an energy cost of 0.0688 $/kWh and a net present cost of $70,777. The optimal system has a renewable fraction of 89.9 % and a CO2 emissions mitigation potential of 13,066 kg/year compared to the base scenario. Furthermore, sensitivity analysis for various input parameters such as grid sellback rate, interest rate and load demand was performed to assess the impact of changes in these parameters on the system. Sensitivity analysis results show that increased grid sellback rates can significantly enhance financial metrics and reduce the payback period from 13.13 years to 6.63 years.