Energy Systems Modelling

Agus Samsudin

I build open-source energy system models, optimisation tools, and interactive dashboards that inform investment decisions in renewable energy and power infrastructure. Specialising in capacity expansion, dispatch modelling, and techno-economic analysis.

LP Optimisation
PyPSA · HiGHS
Power Systems
Energy Economics
Python · Pandas
Resolution
8,760hrs
Full-year hourly modelling
Solver
LP/ MILP
HiGHS via linopy · PyPSA
Technologies
13+types
VRE · storage · thermal · grid
Objectives
3modes
LCOE · CO₂ · Diversified
Case Studies

Interactive LP capacity expansion and hourly dispatch dashboards — each case study is a full 8,760-hour optimisation of a real or representative island/microgrid energy system.

Capabilities

Core modelling competencies and the technical stack behind the work.

Capacity Expansion
Linear programming to optimise least-cost technology portfolio sizing under resource and reliability constraints.
PyPSAHiGHSlinopy
Dispatch Optimisation
8,760-hour economic dispatch with storage cycling, VRE curtailment, and grid congestion analysis.
PythonNumPyPandas
Techno-Economic Analysis
LCOE, LCOS, NPV, and carbon cost modelling across technology lifetimes with full cost decomposition.
LCOELCOSCRF
Interactive Dashboards
Full-stack browser dashboards with Chart.js and Plotly — Sankey flows, heatmaps, and scenario comparison.
Chart.jsPlotlyHTML/CSS/JS
Storage Modelling
Battery, pumped-hydro, and hydrogen storage with SoC constraints, round-trip efficiency, and cycling analysis.
BESSPHSH₂
Emissions & Carbon
CO₂ intensity tracking, carbon tax modelling, and multi-objective optimisation for decarbonisation pathways.
CO₂Carbon TaxNet-Zero
Projects & Tools

Open-source repositories and standalone tools supporting energy system analysis.