Reference health

High Resolution Photovoltaic Power Generation Potential Assessments of Rooftop in China

https://doi.org/10.2139/ssrn.4129728
CiteStamped reference-health badge
13/13 checkable references clean · checked 2026-09-04

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

33 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 13 checked references that resolve
resolves10.1016/j.rser.2016.04.008
A critical review on building integrated photovoltaic products and their applications
resolves10.1016/j.enbuild.2016.11.012
A rapid evaluation method of existing building applied photovoltaic (BAPV) potential
resolves10.1016/j.rser.2017.01.154
Photovoltaic potential of the City of Požarevac
resolves10.1016/j.apenergy.2019.04.113
Urban solar utilization potential mapping via deep learning technology: A case study of Wuhan, China
resolves10.1016/j.apenergy.2018.09.176
A bottom-up approach for estimating the economic potential of the rooftop solar photovoltaic system considering the spatial and temporal diversity
resolves10.1016/j.rser.2017.05.080
State-of-the-art review of solar design tools and methods for assessing daylighting and solar potential for building-integrated photovoltaics
resolves10.1016/j.ecoinf.2019.02.004
An ArcMap plug-in for calculating landscape metrics of vector data
resolves10.1080/00031305.2018.1543615
Iterative Multiple Imputation: A Framework to Determine the Number of Imputed Datasets
resolves10.12928/telkomnika.v19i2.16738
A hybrid analysis model supported by machine learning algorithm and multiple linear regression to find reasons for unemployment of programmers in Iraq
resolves10.1016/j.apenergy.2019.114404
Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty
resolves10.3233/JIFS-201077
Towards improving machine learning algorithms accuracy by benefiting from similarities between cases
resolves10.1038/s41467-021-25720-2
High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation
resolves10.1016/j.egyr.2021.06.031
Determination of the urban rooftop photovoltaic potential: A state of the art
The 33 references without a DOI — listed, not checked
no DOI — not checkedJiang Dan The State Council issued the "14th Five-Year" energy conservation and emission reduction comprehensive work plan
no DOI — not checkedStatus, trend, economic and environmental impacts of household solar photovoltaic development in China: Modelling from subnational perspective
no DOI — not checkedref3
no DOI — not checkedref4
no DOI — not checkedStatus, barriers and perspectives of building integrated photovoltaic systems
no DOI — not checkedref7
no DOI — not checkedDiscussion on Problems and operation and maintenance of distributed photovoltaic power stations in Tibet
no DOI — not checkedAssessment of current energy consumption in residential buildings in Jeddah
no DOI — not checkedDistributed solar photovoltaic development potential and a roadmap at the city level in China
no DOI — not checkedA high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union
no DOI — not checkedref16
no DOI — not checkedThe linkage between renewable energy potential and sustainable development: Understanding solar energy variability and photovoltaic power potential in Tibet
no DOI — not checkedPotential assessment of photovoltaic power generation in China
no DOI — not checkedA method for predicting the solar photovoltaic (PV) potential in China
no DOI — not checkedref21
no DOI — not checkedref22
no DOI — not checkedref23
no DOI — not checkedref24
no DOI — not checkedref25
no DOI — not checkedref26
no DOI — not checkedHOW TO CHANGE OR TRANSFORM A COORDINATE SYSTEM INTO A MAP LAYER?THE ANSWER IS IN ARCMAP
no DOI — not checkedDeveloping the Raster Big Data Benchmark: A Comparison of Raster Analysis on Big Data Platforms
no DOI — not checkedAn analysis of the evolution, completeness and spatial patterns of OpenStreetMap building data in China
no DOI — not checkedref32
no DOI — not checkedStudy on an adaptive thermal comfort model with K-nearest-neighbors (KNN) algorithm
no DOI — not checkedref35
no DOI — not checkedThe coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
no DOI — not checkedAnalysis of CO2 emission reduction contribution and efficiency of China's solar photovoltaic industry: Based on Input-output perspective
no DOI — not checkedPhotovoltaic industry has ushered in a new era of vigorous development
no DOI — not checkedref42
no DOI — not checkedref44
no DOI — not checkedref45
no DOI — not checkedForecasting the Energy and Economic Benefits of Photovoltaic Technology in China's Rural Areas
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

checked 2026-09-04 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record

Embed this badge

Both snippets point at the live badge image and link back to this page. The badge re-renders from the daily check, so an embed never goes stale by more than a day of visits.

<a href="https://citestamp.com/citestamped/10.2139/ssrn.4129728"><img src="https://citestamp.com/citestamped/10.2139/ssrn.4129728/badge.svg" alt="CiteStamped reference-health badge" width="460" height="64"></a>
[![CiteStamped reference-health badge](https://citestamp.com/citestamped/10.2139/ssrn.4129728/badge.svg)](https://citestamp.com/citestamped/10.2139/ssrn.4129728)