Scheduling Model for a Trigeneration System With Energy Storage Unit: A Hospital Application

Dogan A., Güven D., Kayalıca M. Ö., Bayar A. A.

IEEE Transactions on Engineering Management, cilt.71, ss.6146-6159, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 71
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1109/tem.2023.3267797
  • Dergi Adı: IEEE Transactions on Engineering Management
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Public Affairs Index, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.6146-6159
  • Anahtar Kelimeler: Hospitals, Microgrids, Costs, Batteries, Optimization, COVID-19, Energy management, Decision support systems, energy issues in technology management, optimization, renewable energy, scheduling
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Over the last three COVID-19 effective years, it was evident that healthcare has been the most sensitive sector to electricity failures. Therefore, if well developed and implemented, a microgrid system with an integrated energy storage system (ESS) installed in hospitals has great potential to provide an uninterrupted and low-energy cost solution. In this article, we target to show the importance of the installed ESS against the problems that will arise from power outages and energy quality problems in hospitals. Besides, it aims to construct an energy management system (EMS) based on the scheduling model to meet the lowest cost of a system containing solar panels, microturbine, gas boiler, and energy storage units that are repurposed lithium-ion batteries from electric vehicles and thermal storage tank. EMS is a mixed-integer linear program to meet the hospital's electricity, heating, and cooling demands with the lowest cost for every hour. The established scheduling model is run for a hospital in Antioch, Türkiye, with 197 beds, 4 operating rooms, 2 resuscitation units, and 9 intensive care units for every hour based on the data in 2019. With the EMS, approximately 25% savings were achieved compared to the previous energy cost. Furthermore, as the result of the net present value calculation, the payback period of the proposed system is estimated to be approximately seven years.