Abhijith SivaprasadanM.Sc. candidate at KTH · Stockholm, Sweden
Energy Modelling / Portfolio
Modelling energy. Informing decisions.
I build and analyse models of heat, power, storage and industrial energy use. My work connects technology assumptions, network constraints and operating decisions through optimisation, scenario analysis and transparent reporting.
An open-source two-boiler steam-and-power twin with a carbon-aware Pyomo/HiGHS scheduler, OpenModelica FMI 2.0 simulation and a local Streamlit advisory GUI. Synthetic and uncalibrated; not an ABB product or live control system.
Local electricity-investment GUI and shared Pyomo/HiGHS planner, with audited market coverage and 175 extracted public input references. Synthetic and uncalibrated; normalization, price-target decisions and weather conversion still gate historical fitting.
How do corridor limits and flexibility change dispatch? A Netherlands-inspired screening model with hand-checkable congestion and storage tests. Synthetic topology; not a validated Dutch grid.
Electricity, hydrogen and heat dispatch (Pyomo/HiGHS) on a real fetched year of ERA5 wind, with independent verification on every run and an interactive Streamlit GUI.
Developed and independently validated a quantitative methodology for industrial energy performance mapping, covering KPI/EnPI design, load-driver logic, metering-gap assessment, deviation detection from noisy operational data and regulatory comparison. The work was desk-based method development and decision-support framing rather than hands-on plant execution, with electrical utilities and compressed air treated as relevant electrification pathways. Proprietary site detail is not republished.
Python · ISO 50001 · EU EED · KPI/EnPI Design · Energy Performance Mapping · Industrial Energy Analysis · Structured Reporting
Contributed to KTH plastic pyrolysis research by reviewing reactor concepts and cost-analysis drivers for oil extraction from polymer waste, supporting early-stage technical and economic feasibility evaluation.
OpenSteamOpt is a synthetic educational steam/power twin, not live control or an ABB product. GB-FLEXABM is synthetic and uncalibrated; PyPSA-NL uses a synthetic topology. None is a validated operational or national-system model. PyNEXUS has a synthetic 168-hour reference, not an annual-run claim. Alleima work was desk-based methodology, not implemented plant savings. Python applications run locally, not on GitHub Pages.
Source case studies remain authoritative. Private inputs and restricted project details are not published.
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For energy-system modelling, optimisation and energy-analysis roles.