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Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China

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  • Bin Ye

    (School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China)

  • Minhua Zhou

    (School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China)

  • Dan Yan

    (School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China)

  • Yin Li

    (Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou 510275, China)

Abstract

The application of renewable energy has become increasingly widespread worldwide because of its advantages of resource abundance and environmental friendliness. However, the deployment of hybrid renewable energy systems (HRESs) varies greatly from city to city due to large differences in economic endurance, social acceptance and renewable energy endowment. Urban policymakers thus face great challenges in promoting local clean renewable energy utilization. To address these issues, this paper proposes a combined multi-objective optimization method, and the specific process of this method is described as follows. The Hybrid Optimization Model for electric energy was first used to examine five different scenarios of renewable energy systems. Then, the Technique for Order Preference by Similarity to an Ideal Solution was applied using eleven comprehensive indicators to determine the best option for the target area using three different weights. To verify the feasibility of this method, Xiongan New District (XND) was selected as an example to illustrate the process of selecting the optimal HRES. The empirical results of simulation tools and multi-objective decision-making show that the Photovoltaic-Diesel-Battery off-grid energy system (option III) and PV-Diesel-Hydrogen-Battery off-grid energy system (option V) are two highly feasible schemes for an HRES in XND. The cost of energy for these two options is 0.203 and 0.209 $/kWh, respectively, and the carbon dioxide emissions are 14,473 t/yr and 345 t/yr, respectively. Our results provide a reference for policymakers in deploying an HRES in the XND area.

Suggested Citation

  • Bin Ye & Minhua Zhou & Dan Yan & Yin Li, 2020. "Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China," Energies, MDPI, vol. 13(23), pages 1-25, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6223-:d:451479
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    1. Yuan Liu & Qinliang Tan & Jian Han & Mingxin Guo, 2021. "Energy–Water–CO 2 Synergetic Optimization Based on a Mixed-Integer Linear Resource Planning Model Concerning the Demand Side Management in Beijing’s Power Structure Transformation," Energies, MDPI, vol. 14(11), pages 1-17, June.
    2. Charles Newbold & Mohammad Akrami & Mahdieh Dibaj, 2021. "Scenarios, Financial Viability and Pathways of Localized Hybrid Energy Generation Systems around the United Kingdom," Energies, MDPI, vol. 14(18), pages 1-27, September.
    3. Jann Michael Weinand & Maximilian Hoffmann & Jan Gopfert & Tom Terlouw & Julian Schonau & Patrick Kuckertz & Russell McKenna & Leander Kotzur & Jochen Lin{ss}en & Detlef Stolten, 2022. "Global LCOEs of decentralized off-grid renewable energy systems," Papers 2212.12742, arXiv.org, revised Mar 2023.
    4. Ali, Tausif & Aghaloo, Kamaleddin & Chiu, Yie-Ru & Ahmad, Munir, 2022. "Lessons learned from the COVID-19 pandemic in planning the future energy systems of developing countries using an integrated MCDM approach in the off-grid areas of Bangladesh," Renewable Energy, Elsevier, vol. 189(C), pages 25-38.
    5. Limei Liu & Xinyun Chen & Yi Yang & Junfeng Yang & Jie Chen, 2023. "Prioritization of Off-Grid Hybrid Renewable Energy Systems for Residential Communities in China Considering Public Participation with Basic Uncertain Linguistic Information," Sustainability, MDPI, vol. 15(11), pages 1-30, May.

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