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GP-CH-0Y67NVJChemicalOpen for request

Indian green-hydrogen economics simulator

A techno-economic simulator for comparing green-hydrogen production configurations under Indian renewable profiles, electricity costs, electrolyser performance, storage, and utilisation assumptions.

  • Nuxt
  • Vue
  • FastAPI
  • PostgreSQL
  • Python
  • NumPy
  • Pandas
  • Docker

Project definition

Problem statement

Green-hydrogen cost depends on renewable availability, grid use, electrolyser loading, efficiency, degradation, water treatment, compression, storage, financing, and annual utilisation.

The engineering problem is to connect time-resolved plant operation with transparent mass, energy, and economic calculations so that scenario comparisons do not hide important assumptions.

Project objectives

  • Model selected alkaline or PEM electrolyser performance, turndown, efficiency, capacity, and degradation.
  • Simulate hourly renewable, grid, storage, curtailment, water, hydrogen, and auxiliary-energy flows.
  • Calculate levelised hydrogen cost and its capital, electricity, replacement, water, and operating components.
  • Compare renewable-only, grid-assisted, storage, sizing, location, and utilisation scenarios.
  • Measure sensitivity to the assumptions that most strongly affect output and cost.

System design

System modules

01

Plant configurator

Defines electrolyser, renewable source, grid, water treatment, compression, storage, and delivery boundary.

02

Operations simulator

Balances hourly electricity and hydrogen while enforcing capacity, efficiency, turndown, storage, and availability.

03

Degradation model

Tracks operating hours, starts, efficiency change, stack life, and replacement under documented assumptions.

04

Economic engine

Calculates capital recovery, operating cost, replacements, energy cost, annual output, and levelised cost.

05

Scenario dashboard

Shows power and hydrogen flows, utilisation, curtailment, storage, cost breakdown, and sensitivity charts.

Methodology

System workflow

  1. 01
    Define plant

    The student selects a prepared Indian location profile and defines plant capacity and process boundaries.

  2. 02
    Load assumptions

    Hourly renewable data, grid price and emissions, performance, costs, financing, and component life are recorded.

  3. 03
    Simulate operation

    The model resolves each hour’s power, electrolyser, storage, auxiliary, and hydrogen balances.

  4. 04
    Calculate economics

    Annual output, replacements, cash-flow components, and levelised hydrogen cost are computed.

  5. 05
    Compare sensitivity

    Sizing, electricity, utilisation, degradation, financing, and storage assumptions are varied systematically.

Demonstration scenario

A prepared solar and wind profile supplies an electrolyser at an Indian location. Renewable-only and grid-assisted configurations are simulated with and without hydrogen storage. The dashboard compares utilisation, curtailment, annual output, stack replacement, and the complete levelised-cost breakdown.

Engineering

Technical architecture

Web application
Nuxt and Vue for plant configuration, profiles, flow charts, economics, scenarios, and exports.
Simulation API
FastAPI for component data, time-series jobs, cost calculations, sensitivity runs, and results.
Data layer
PostgreSQL for profiles, components, assumptions, scenarios, hourly balances, and economic metrics.
Process model
Python, NumPy, and Pandas for hourly mass and energy balances, part-load efficiency, storage, and degradation.
Economics model
Versioned capital, operating, replacement, discount, lifetime, and boundary assumptions with full cost breakdown.

Testing

Evaluation

Evaluation measures

  • Electricity, water, and hydrogen mass and energy balance closure
  • Agreement with manually calculated steady and annual reference cases
  • Electrolyser utilisation, renewable use, curtailment, storage cycling, and annual output
  • Levelised cost and component contribution under each scenario
  • Sensitivity to electricity price, capacity factor, efficiency, stack life, capital cost, and discount rate
  • Simulation time across hourly horizons and sensitivity grids

System boundaries

  • The simulator is a pre-feasibility educational model and not an investment, bidding, or plant-design tool.
  • Costs, tariffs, financing, incentives, emissions, and technology data are dated assumptions and must be updated for real use.
  • Detailed process safety, materials, compression design, permitting, transport, and grid studies are outside scope.
  • Hydrogen facilities require specialist engineering, safety analysis, codes, approvals, and certified equipment.

Included

  1. 01Plant, renewable, storage, and economics interface
  2. 02Hourly operation, balance, degradation, and cost modules
  3. 03Hydrogen output, utilisation, energy, cost, and sensitivity dashboards
  4. 04Prepared Indian renewable and tariff scenarios with results
  5. 05Complete source code in a private GitHub repository
  6. 06Complete project documentation with synopsis, abstract, methodology, process-flow diagrams, economic results, screenshots, and conclusion
  7. 07Setup and usage guide

Project record

No buyer information is collected on this page.

Permanent project ID
GP-CH-0Y67NVJ
Catalogued
21 Aug 2026
Completed
Pending
Verified
Pending
Demonstration
Added when ready

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.