Authors: H. Xie, H. Liu, C. Wan,H. H.H. Goh, M. Z. Yousaf, Saifur Rahman
Publisher: IEEE Internet of Things Journal, Vol: 10, Issue: 24
Published on: 12/15/2023
DOI: https://doi.org/10.1109/JIOT.2023.3304644
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Abstract:

In order to reach carbon neutrality, there is growing interest in reducing greenhouse gas (GHG) and improving energy efficiency. One way to address this issue is the optimal scheduling of the integrated energy system (IES) with multiple combined cooling heating and power (CCHP) systems as proposed in this article. We model IES as a device with multiple input/output ports by the energy hub (EH) framework and propose a multiobjective optimal model to improve energy efficiency and reduce GHG emissions. The proposed model is constructed as a mixed-integer nonlinear programming (MINLP) due to considering nonlinear couplings of multiple energy flows and the unit commitment of multiple CCHP systems. To improve the computational efficiency, the proposed MINLP model is transformed into a nonlinear programming (NLP) model by a fast unit commitment technique based on the approximation of the aggregated online capacity. Finally, simulation results show the effectiveness of the proposed approach in reducing GHG emissions and improving energy efficiency as well as computational efficiency.

Keywords:
Combined cooling heating and power (CCHP) , energy hub (EH) , integrated energy system (IES) , mixed-integer nonlinear programming (MINLP) , optimal scheduling