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Smart Charging Scheduling Platforms (Grid-friendly Load Balancing)

Build smart EV charging scheduling platforms with AI-driven load balancing. PySquad helps operators optimise charging demand, reduce peak load, and protect grid stability.

See How We Build for Complex Businesses

As EV adoption accelerates, uncontrolled charging can overwhelm grids, increase peak loads, and raise operational costs for charging networks. Smart charging systems are essential for avoiding overloads, optimising energy usage, and coordinating charging sessions across residential, commercial, and fleet environments.

PySquad builds intelligent charging scheduling platforms powered by AI models, demand forecasting, and real-time load management. Our solutions enable charging operators, utilities, and fleets to manage charging intelligently while improving user experience and grid compatibility.


Problem Businesses Face

  • Peak load spikes due to simultaneous charging.

  • No control over when and how EVs are charged.

  • Difficulty forecasting energy demand across chargers.

  • High risk of transformer or feeder overload.

  • Limited tools for implementing grid-friendly load distribution.

  • Poor coordination across fleets and public stations.


Our Solution

PySquad develops smart charging scheduling systems that coordinate EV charging in real time using AI-driven logic.

Our solution includes:

  • Demand forecasting using historical + real-time data.

  • Priority-based scheduling (vehicle type, battery level, urgency).

  • Dynamic load balancing across chargers and sites.

  • Time-of-day and tariff-based optimisation.

  • APIs for utilities and charging station operators.

  • User-facing controls for scheduling preferences.


Key Features

  • AI-based demand prediction and scheduling.

  • Real-time load control across multiple chargers.

  • OCPP integration for command execution.

  • Priority charging for fleets or emergency vehicles.

  • Tariff-aware charging (off-peak incentives).

  • Grid-aware algorithms to avoid feeder overload.

  • Dashboards for monitoring load, demand, and schedule queues.


Benefits

  • Lower peak loads and reduced grid stress.

  • Lower charging costs through off-peak optimisation.

  • Increased operational efficiency for station operators.

  • Better user satisfaction with predictable charging slots.

  • Scalable solution suitable for fleets, apartments, and smart cities.


Why Choose PySquad

  • Deep expertise in EV software, OCPP, AI, and load balancing.

  • Proven experience with utility-grade optimisation systems.

  • Human-first dashboards and user-friendly scheduling tools.

  • Scalable, secure backend designed for multi-site operations.

  • Support from MVP creation to production rollout.


Call to Action

  • Want smarter charging without grid overloads?

  • Need AI-based scheduling for fleet or public charging?

  • Looking to integrate charging control with utilities?

Partner with PySquad to build smart charging scheduling platforms that keep grids stable and EV charging efficient.


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Frequently asked questions

Yes. We integrate via OCPP and custom APIs.

Yes. The system scales from small complexes to large CPO networks.

Yes. User preferences are factored into scheduling.

Yes. Utilities can send signals for load control or tariff changes.

Absolutely — fleet-first scheduling and prioritisation are built in.

About PySquad

PySquad works with businesses that have outgrown simple tools. We design and build digital operations systems for marketplace, marina, logistics, aviation, ERP-driven, and regulated environments where clarity, control, and long-term stability matter.
Our focus is simple: make complex operations easier to manage, more reliable to run, and strong enough to scale.

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happy clients50+
Projects Delivered20+
Client Satisfaction98%