Smart energy solution for an optimised sustainable hospital in the green city of NEOM

Dhaifallah M Alotaibi,Mohammad Akrami,Mahdieh Dibaj,Akbar A Javadi

doi:10.1016/j.seta.2019.05.017

Dhaifallah M Alotaibi, Mohammad Akrami + Show 2 more

Open Access

https://doi.org/10.1016/j.seta.2019.05.017

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Abstract

Hybrid optimisation of multiple energy resources has been performed on a micro grid model of a hospital to investigate the capability of a standalone energy system and simultaneous mitigation of hospital waste. The main objectives of this study were to collect renewable energy resource data of a hybrid hospital, use the average amount of hospital waste from the literature and NASA surface meteorology in addition to the solar energy database from HOMER Pro software to construct a hybrid model for a conceptual hospital in the new green city in Saudi Arabia, NEOM. The hybrid model consisted of biogas cofire and diesel generators, PV solar array and batteries. Simulations were performed to analyse the load requirements of a standalone hospital. The mechanism of energy storage was designed based on Tesla batteries. Then, the hybrid hospital model was tested with NEOM’s natural resources, load demand of 250 kWh/day and the average amount of daily hospital waste of 0.6 tons based on the literature data. This condition allows the smart hospital to be tested with real features. The outcome of the COE, NPC and the amount of reduction of carbon dioxide in the hybrid hospital were analysed. Many of the hybrid properties and constraints that define the hospital were adopted from previous literature concentrating on similar domains. The optimal solution of a hybrid micro grid consisted of biogas cofire, PV array, and batteries. Of the total load demand, 32.3% and 67.6% were produced by PV array and biogas cofire generators, respectively, together with eight Tesla PowerWall2.0 batteries. The cost of energy was 0.21 USD/kWh and the net present cost was 243,699.17 USD. In this study, we compared renewable energy with conventional energy and found that the optimal solution would be able to reduce carbon emission and diesel consumption by almost 84% and 81%, respectively. The results were verified through a sensitivity study and compared with other studies.

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