Usman Y.

Solar photovoltaic (PV) data analyst and researcher with hands-on experience across monitoring, simulation, and tooling. I work at a PV testing center in Bangkok where I manage servers, build data pipelines, and turn raw plant data into clean, usable information for operations and research. Available for remote freelance projects in wind and solar resource assessment, PV data analytics, monitoring pipelines, quality control (QC/validation) of reanalysis/satellite datasets, web development, PV yield simulations and related topics. What I do • Build and maintain data workflows for PV plants: ingest, clean, validate, store, visualize. • Develop web apps and databases for monitoring and reporting. • Configure Modbus data loggers (RS-485/TCP) with slave devices and connect devices to backend services. • Quality-check irradiance and plant data according to BSRN, IEA PVPS Task 16 guidelines. • Model PV performance (pvlib-python), plane-of-array conversions, and simple yield studies. • Time-series forecasting (Prophet) and analysis of data granularity effects. • Create tools for degradation and anomaly detection using plant monitoring data. • Validate satellite/reanalysis solar data with ground measurements (pyranometer). • Managed Oracle and CentOS Linux servers for the center; taught junior staff Linux basics. • Built Python services to push logger data to a central server and a real-time (1-min) transfer app. • Enabled a web application to communicate to data loggers and write to SQL tables. • Daily monitoring and reporting of rooftop PV electrical profiles. • Trained five interns; led daily “R&D Morning Brief” stand-ups and wrote minutes. • Supported outdoor consultancy visits to PV plants in Thailand. • Results presented at an international conference served as technical staff for a PV module failure workshop. Academic background (M.Sc. thesis): Solar Energy Potential and its Relationship with Climate and Atmospheric Pollution for Central Thailand • Set up a Linux (Fedora) environment and toolchain: C shell, R, Python, CDO, Panoply, libRadtran, QGIS, pvlib. • Worked with ERA5, MERRA-2, CAMS datasets; extracted NetCDF subsets via CDO/R/C-shell. • Computed cloud microphysics (effective radius) and aerosol properties (e.g., single scattering albedo). • Built libRadtran inputs (including atmospheric height from gravitational potential energy) and simulated hourly GHI/DNI/DHI for different sky conditions; ran pvlib for POA and PV output. • Quantified cloud and aerosol impacts on PV power; presented findings; thesis submitted and paper in preparation.