Evidence map›Paper›PMID 41444389›Full record

ArticleScientific reports2025

Assessment and economic analysis of photovoltaic power generation potential on highway slope: a case study of Guangxi, China.

Jiyong Li, Yide Peng, Xiaoping Xiong, Zhiliang Cheng, Chen Ye, Hao Huang, Kaiyue Wang

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jiyong LiSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Yide PengSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Xiaoping XiongSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Zhiliang ChengSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Chen YeSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Hao HuangSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.
Kaiyue WangSchool of Electrical Engineering, Guangxi University, Nanning, 530004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highway slope photovoltaic (HSPV) systems represent a significant approach to achieving transportation-energy integration and reducing carbon emissions, as well as a crucial utilization method for renewable energy. Given the complexity of assessing the installable area of photovoltaic (PV) panels on highway slopes across large spatial scales, a regression assessment analysis was conducted using Random Forest. The results demonstrated that as of 2024, the total installable PV area on highway slopes across 14 cities in Guangxi is 0.989 km2. Furthermore, accounting for regional variations in PV system efficiency, the power generation efficiency of HSPV systems in different areas was evaluated by integration of the Analytic Hierarchy Process (AHP) and Entropy Weight Method. Based on these assumptions, the estimated installed capacity of HSPV in Guangxi reaches 155.93 MW, with an annual power generation potential of 169.03 GW · h. After conducting an economic analysis, the project is economically feasible, as evidenced by a net present value > 0, an internal rate of return > 8%, a benefit-cost ratio > 1, and a payback period < 10 years. The proposed integrated framework—combining random forest-based slope-area extrapolation with AHP-entropy efficiency evaluation—remains reliable even without high-resolution imagery, offering replicability and scalability for highway-slope PV assessments. The findings provide actionable guidance for PV siting and economic appraisal in other provinces or linear infrastructures (e.g., railways, transmission corridors).

Indexed as

Economic analysisInstallable area assessmentRandom forestSlope photovoltaicSystem efficiency assessment

Identifiers

PMID41444389
PMCPMC12830716

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.