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Benefits of Photovoltaics in Coal Mining Sites Revealed in Study

Researchers have explored what really drives the placement of photovoltaic (PV) systems in coal-mining subsidence areas in Shanxi Province, China. Using the fuzzy DEMATEL-ISM (Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling) method, the team examined how climatic, geological, economic, social, and policy factors interact to shape PV siting decisions.

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Their analysis shows that developing PV projects in subsidence zones can serve dual purposes: expand renewable energy capacity while helping to repair landscapes damaged by decades of mining. In regions struggling with land degradation and energy transition pressures, this combination offers a compelling path forward.

Advancements in Renewable Energy Technology

Over the past decade, PV technology has become one of the most widely adopted renewable energy options worldwide. By converting sunlight directly into electricity using semiconductor materials, PV systems play a crucial role in reducing carbon emissions and promoting cleaner energy systems.

Placing PV installations in coal-mining subsidence areas adds another layer of value. These lands are often unsuitable for farming or construction, but they can be effectively utilized for hosting solar infrastructure. Repurposing degraded land in this way improves overall land-use efficiency while contributing to ecological recovery in mining-affected regions. It also aligns closely with broader carbon-neutrality and sustainability objectives.

Methodology for Assessing Influencing Factors

To untangle the complex web of influences on PV siting, the researchers applied the fuzzy DEMATEL-ISM approach to construct a multidimensional indicator system. This framework covered climatic, geological, economic, social, and policy-related dimensions. Through literature review and expert consultation, they identified 20 key factors, including solar radiation, average temperature, geological stability, project costs, and government subsidies.

Expert surveys provided qualitative assessments of how these factors influence one another. These judgments were then converted into quantitative data, allowing the researchers to map causal relationships and hierarchical structures among the variables. The structured process - spanning factor identification, expert evaluation, modeling, and synthesis - enabled the clarification of interdependencies and the identification of factors that carry the most weight in determining PV project success in subsidence areas.

Impact of Climatic and Economic Conditions

The results underscored the importance of local climate conditions. Extreme weather events and frequent dust exposure were found to directly affect PV efficiency, system durability, and maintenance requirements. On the economic side, indicators such as the levelized cost of energy (LCOE) and project payback period emerged as decisive constraints influencing investor interest and overall feasibility.

Notably, the study revealed a strong causal link between climatic risks and economic performance. Harsh weather conditions increase operating and maintenance costs, which in turn lengthen payback periods and weaken project economics.

Land-use planning and infrastructure also proved critical. Factors such as land suitability, proximity to urban centers, and access to grid connections played a major role in siting decisions.

Policy support, particularly during early project stages, was identified as a key enabler, while long-term success depended more heavily on cost control and resilience to environmental stressors.

Overall, the DEMATEL-ISM analysis emphasized that successful PV deployment in subsidence zones requires a coordinated approach that balances climate adaptation, economic viability, ecological recovery, and well-designed policy support.

Synergizing Photovoltaics with Ecological Restoration

The implications of this research extend beyond Shanxi Province. Integrating PV systems into coal-mining subsidence areas offers a practical way to pair renewable energy development with ecological restoration. This strategy improves land-use efficiency, supports carbon-neutrality goals, and can contribute to the economic renewal of communities long dependent on resource extraction.

For policymakers, the findings point to the need for clear and supportive frameworks for PV development on subsidized land. These include financial incentives to offset initial investment costs and targeted assistance for operation and maintenance in regions exposed to challenging climatic conditions. Pairing PV deployment with ecological restoration measures - such as soil stabilization and vegetation recovery - can further enhance land rehabilitation and biodiversity outcomes.

Conclusion: Insights for Sustainable Mining

The study highlights the value of integrating PV development with ecological restoration in coal-mining subsidence areas. By systematically analyzing the factors that influence PV siting, the research offers practical guidance for policymakers, planners, and investors seeking to optimize renewable energy projects under local climatic, geological, and economic conditions.

The findings suggest that coordinated strategies - bringing together technology, policy support, and environmental considerations - are essential for long-term success. When thoughtfully implemented, PV projects in subsidence zones can meet energy demands while restoring degraded land and supporting resilient, low-carbon development in mining regions.

Journal Reference

Lu, Y. et al. (2025). Study on the influencing factors of photovoltaic siting in coal mining subsidence areas-taking Shanxi Province as an example. Sci Rep 15, 43603. DOI: 10.1038/s41598-025-26672-z, https://www.nature.com/articles/s41598-025-26672-z

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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