Assessfy Industry Projects Lab Advanced 6 milestones 100 marks

Optimising EV Charging Station Locations and Utilisation with Geospatial Analytics

Industry: Energy & Utilities Industry: Energy & Utilities Function: Operations Type: Industry-vertical applied project Team: up to 4 Assessment: 6 milestones (100 marks)

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Available mentors
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Enrolled students
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Core skills
About this project

Objective: To identify optimal locations for new EV charging stations and analyse utilisation patterns to maximise network efficiency in an urban Indian context.

India's rapid adoption of electric vehicles (EVs) is limited by the availability and efficient utilisation of charging infrastructure, especially in urban centres where range anxiety and under-utilised stations hinder growth.

This project will use real-world data (traffic flows, EV registrations, power grid capacity, demographics) to analyse current usage of public charging stations and develop a siting model for optimal future deployment in a selected Indian metro city.

Deliverables include geospatial heatmaps of current demand, a predictive model for utilisation, a prioritised list of high-potential sites, and a dashboard prototype for ongoing network management. The team will analyse cost-benefit trade-offs and operational feasibility for recommended sites.

This solution will support city planners and energy companies in making data-driven decisions, improving EV adoption rates, enhancing consumer experience, and optimising capital allocation for charging infrastructure.

Milestones
1. Problem Definition & Business Case
10 marks 21d
Define the scope (city/region), stakeholders, and business objectives. Deliverable: Business case document and project plan, reviewed in a team presentation and with industry mentor feedback.
2. Domain Research & Data Gathering
13 marks 21d
Collect and validate data on existing charging stations, EV registrations, demographics, grid capacity, and traffic flows. Deliverable: Data inventory and research summary, peer and faculty reviewed.
3. Solution Design / Methodology
12 marks 21d
Develop methodology for geospatial analysis, demand modelling, and site prioritisation. Deliverable: Methodology report and review presentation to faculty and domain expert.
4. Build / Analysis & Implementation
28 marks 35d
Conduct geospatial analysis, build predictive model, and generate site recommendations. Deliverable: Analytical models, heatmaps, and draft dashboard, reviewed by faculty and industry mentor.
5. Validation & Results
22 marks 28d
Test model accuracy, validate recommendations using secondary data or expert feedback, refine outputs. Deliverable: Validation report and presentation, reviewed by panel (faculty + industry).
6. Final Report & Presentation
15 marks 21d
Prepare final report, business impact summary, and present to academic and industry panel. Deliverable: Comprehensive report and stakeholder-ready presentation.
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Skills you'll learn
Energy & UtilitiesOperationsGeospatial analytics and mappingData cleaning and integrationPredictive modelling and demand forecastingBusiness case developmentData visualisation and storytellingDomain knowledge of EV infrastructureStakeholder communication
Tools used
Python (PandasGeopandasScikit-learn)QGIS or ArcGIS for geospatial analysisGovernment open datasets (e.g.NITI Aayog EV DataRTO vehicle registrationsCEA grid maps)Power BI or Tableau for dashboardsGoogle Maps API or OpenStreetMapExcel for data pre-processing and scenario analysis
Prerequisites
Basic statistics and probabilityIntroduction to data analysis or data scienceFundamentals of operations research or supply chainIntroductory course in energy systems or transport management
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You'll earn — Certificate (PDF)

AICTE-aligned Project Completion Certificate

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