“Photovoltaic +” Multi-Industry Integration for Sustainable Development in “Desert-Gobi-Wilderness” Region: Geospatial Suitability Simulation and Dynamic Site Selection Decision Optimization

Zhaotong Song, Jianli Zhou (), Cheng Yang, Shuxian Wu, Zhuohao Chen, Jiawen Sun and Yunna Wu
Additional contact information
Zhaotong Song: School of Economics and Management, Xinjiang University, Urumqi 830046, China
Jianli Zhou: School of Economics and Management, Xinjiang University, Urumqi 830046, China
Cheng Yang: School of Economics and Management, Xinjiang University, Urumqi 830046, China
Shuxian Wu: School of Economics and Management, Xinjiang University, Urumqi 830046, China
Zhuohao Chen: Strategy and Decision-Making Research Center of Xinjiang Energy Carbon Neutrality, Xinjiang University, Urumqi 830046, China
Jiawen Sun: School of Computer Science and Technology, Xinjiang University, Urumqi 830046, China
Yunna Wu: Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China

Land, 2025, vol. 14, issue 7, 1-29

Abstract: Driven by global climate change and sustainable development, the coordinated development of multiple industries based on photovoltaic energy in the “Desert-Gobi-Wilderness” region has become the key to achieving sustainable development, as well as transforming and upgrading the energy structure. However, the site selection decision for “Photovoltaic +” multi-industry integration, which takes into account economic, social and ecological benefits in a complex ecological environment, is still a key difficulty that restricts the feasibility and scalability of the project. This study first identified and systematically analyzed six “PV +” multi-industry integrations suitable for development in China, including “PV + sand control”, “PV + agriculture”, “PV + agriculture + tourism”, “PV + animal husbandry”, “PV + animal husbandry + tourism”, and “PV + tourism”. Then, a site selection decision framework for “PV +” multi-industry integration consists of three parts. Part 1 establishes a multi-dimensional suitability assessment system that takes into account heterogeneous data from multiple sources. Part 2 uses an integration method based on BWM-CRITIC-TODIM for priority ranking analysis, which first uses a Geographic Information System (GIS) to carry out suitability simulation for the entire region of China—identifying six alternative regions—then uses the interactive and multi-criteria decision-making (MCDM) method to prioritize the alternative areas. Part 3 carries out further sensitivity analyses, scenario analyses, and comparative analyses to verify the dynamics and scientific nature of the site selection decision framework. Finally, this study identifies regions of high suitability for development corresponding to the six multi-industry integrations. The framework is designed to help decision stakeholders achieve precise site selection and benefit optimization for “PV +” multi-industry integration and provides a replicable planning tool for achieving industrial synergy and sustainable development in the “Desert-Gobi-Wilderness” region driven by green energy.

Keywords: “Desert-Gobi-Wilderness” region; “Photovoltaic +”; multi-industry integration; sustainable development; suitability assessment; decision optimization (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/7/1410/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/7/1410/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:7:p:1410-:d:1694937

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().