Multi-period multi-objective optimisation model for multi-energy urban-industrial symbiosis with heat, cooling, power and hydrogen demands
Hydrogen is seen as the future energy that will help decarbonise the emissions of global energy use. Hydrogen-related technologies have recently attracted considerable attention due to their relatively low emissions and high energy yield. Even then, little attention was given to hydrogen's use...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/106734/ http://dx.doi.org/10.1016/j.energy.2022.125201 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Hydrogen is seen as the future energy that will help decarbonise the emissions of global energy use. Hydrogen-related technologies have recently attracted considerable attention due to their relatively low emissions and high energy yield. Even then, little attention was given to hydrogen's use in energy distribution networks. A renewable-based multi-energy system (RMES) considers power, cooling, heating, and hydrogen energy as utility systems for integrated urban and industrial areas to achieve urban-industrial symbiosis. This paper formulates the RMES as a multi-period mixed-integer nonlinear programming (MINLP) model to optimise the RMES, which minimises the financial implications and environmental impacts. Renewable solar energy is provided to the system using the photovoltaic solar system for electrical generation and the solar thermal collector for heat generation. Thermal, battery and hydrogen energy storages are integrated into the RMES to mitigate the energy supply and demand fluctuations and intermittency. A comparative analysis is conducted to individually identify the performance of different energy storage systems for economic and environmental objective functions. The comparison findings indicate that ESS performs better with 45% usage increases under objective environmental functions. The multi-objective optimisation using the ?-constraint method obtains the Pareto optimal solutions to the proposed multi-objective problem, which the 4th solution (ATC: 782,500 USD/y, ACE: 2,777.03 kg CO2-eq/y) appears to be the most viable. The solution maintains a high-profit level without sacrificing many opportunities for carbon emissions reduction while satisfying both objective functions simultaneously to a degree of satisfaction of 0.75. Overall, the proposed RMES is proven economical and environmentally friendly for implementation, however, the model is needed to optimise the system based on the specific situation. This study provides the optimisation model for energy recovery and technology optimisation in the multi-energy system for urban-industrial symbiosis, which minimises carbon emission and energy cost. This could lead the energy sector to achieve the Sustainable Development Goals, considering the economically and environmentally viable. |
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