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mbax0009/README.md

Muhammad Bin Asad — building explainable energy-decision systems for Pakistan

I am a student entrepreneur and product builder working at the intersection of energy modelling, financial analysis and decision software. I turn complex questions about renewable-energy investment into transparent tools that show users what a system could produce, what it may cost, how risk changes the result and why a recommendation was made.

Featured systems

GreenInvest Pakistan

Converts electricity use, bills, budget, available space and backup needs into an explainable solar, battery and inverter recommendation. It also audits installer quotations and supports residential, commercial and industrial screening up to 4 MW of solar.

Open the live application · View source · Download for Windows

Pakistan Energy Simulator

Screens utility-scale solar PV, onshore wind and wave-energy projects using location-aware resource modelling, project economics, scenario ranges, sensitivity analysis and seeded Monte Carlo simulation.

Explore the repository · Download the latest release

Core capabilities

  • Energy systems: solar PV, batteries, inverters, wind and wave-resource modelling
  • Project economics: cash flow, NPV, IRR, LCOE, payback and break-even analysis
  • Decision intelligence: tariff-aware recommendations, scenario analysis, sensitivity testing and uncertainty modelling
  • Product engineering: Python, FastAPI, NumPy, pandas, React, JavaScript, Vite and automated testing
  • Deployment: web applications, local-first Windows releases and reproducible GitHub Actions workflows

How I build

  1. Explain the verdict. Important recommendations should be traceable to inputs, assumptions and calculations.
  2. Keep uncertainty visible. A useful model shows ranges, sensitivities and downside cases—not only a single attractive number.
  3. Design for local reality. Tariffs, resource quality, budgets, grid behaviour and practical constraints belong inside the model.
  4. Build for decisions. Technical depth matters most when it helps someone choose what to do next.

Current direction

I am continuing to strengthen the validation, scale and usability of both platforms while exploring how transparent quantitative tools can improve renewable-energy investment decisions across Pakistan.

Pinned Loading

  1. GreenInvest-Pakistan GreenInvest-Pakistan Public

    Pakistan solar calculator for homes, businesses and industry — solar, battery and inverter sizing, bill forecasts, quote checks and Monte Carlo risk.

    2

  2. mbax0009.github.io mbax0009.github.io Public

    Portfolio of Muhammad Bin Asad — explainable energy modelling, financial analysis and decision software for Pakistan.

    JavaScript

  3. Pakistan-Energy-Simulator Pakistan-Energy-Simulator Public

    Techno-economic renewable energy simulator for Pakistan — solar PV, wind and wave modelling, LCOE, NPV, IRR, sensitivity and Monte Carlo risk.

    Python 2