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Optimal Capacity Allocation for Life Cycle Multiobjective Integrated Energy Systems Considering Capacity Tariffs and Eco-Indicator 99

Author

Listed:
  • Jiyong Li

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Zeyi Hua

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Lin Tian

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Peiwen Chen

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Hao Dong

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

Traditional energy systems pose a significant threat to human social development due to fossil fuel depletion and environmental pollution. Integrated energy systems (IESs) are widely studied and applied due to their clean and low-carbon characteristics to achieve sustainable development. However, as integrated energy systems expand, their impact on ecosystems becomes more pronounced. This paper introduces the concept of the ecological damage index (EDI) to promote the sustainable development of integrated energy systems. Moreover, the introduction of a capacity tariff mechanism will impact the energy structure, making it essential to consider its effects on capacity allocation within integrated energy systems. This paper proposes a multiobjective optimization framework for constructing a capacity planning model for integrated energy systems, focusing on achieving a multidimensional balance between the economy, environment, and ecosystem using the life cycle assessment (LCA) method. Finally, the nondominated sorting genetic algorithm-II (NSGA-II) is employed to optimize the three objectives and obtain the Pareto frontier solution set. The optimal solution is selected from the solution set by combining the technique for order preference by similarity to ideal solution (TOPSIS) and Shannon entropy method. In comparison to scenarios with incomplete considerations, the multiobjective capacity optimization model proposed in this study exhibits significant improvements across the three metrics of cost, carbon emissions, and the ecological damage index, with a 19.05% reduction in costs, a 26.24% decrease in carbon emissions, and an 8.85% decrease in the ecological damage index. The study demonstrates that the model abandons traditional single-objective research methods by incorporating a multidimensional balance of the economy, environment, and ecosystems. This approach forms a foundational basis for selecting the optimal energy mix and achieving sustainable development in integrated energy systems. The life cycle assessment methodology evaluates impacts across all stages of integrated energy systems, providing a comprehensive basis for assessing and planning the sustainable development of the systems. The study offers guidance for the rational allocation of the integrated energy system capacity and advances the sustainable development of such systems.

Suggested Citation

  • Jiyong Li & Zeyi Hua & Lin Tian & Peiwen Chen & Hao Dong, 2024. "Optimal Capacity Allocation for Life Cycle Multiobjective Integrated Energy Systems Considering Capacity Tariffs and Eco-Indicator 99," Sustainability, MDPI, vol. 16(20), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8930-:d:1499387
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    References listed on IDEAS

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