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EV Charging/Smart Charging and Load Management
S3 Scale · Smart Charging

Smart Charging and Load Management

We engineer smart charging systems that distribute power intelligently across your chargers. Whether you are working within grid constraints, integrating solar, or optimizing energy costs, we build the algorithms and OCPP profiles that make it work in the real world.

What We Deliver Icon

What We Deliver

Core capabilities

Dynamic Load Balancing

Real-time power distribution across all chargers based on available grid capacity. Our algorithms continuously adjust charging rates as vehicles arrive and depart, ensuring you maximize throughput within your electrical limits.

Real-TimePower DistributionGrid LimitsThroughput

Grid Capacity Management

Transformer-level monitoring with demand response capabilities and peak shaving. We integrate with building energy management systems to ensure EV charging coexists with facility loads gracefully.

TransformerPeak ShavingDemand ResponseBMS

Priority-Based Charging

Vehicle priority rules based on user tiers, departure time targets, state of charge, and fleet scheduling requirements. The system optimizes who gets power first while ensuring every vehicle meets its departure deadline.

Priority RulesDeparture TimeFleetSoC

Solar and Battery Integration

PV self-consumption optimization that routes excess solar production directly to EV charging. Battery buffer management for sites with energy storage, smoothing demand peaks and maximizing renewable utilization.

Solar PVBattery StorageSelf-ConsumptionRenewables

OCPP Smart Charging Profiles

Full implementation of TxProfile, TxDefaultProfile, and ChargePointMaxProfile. We handle profile stacking, period transitions, and the coordination between CSMS-set and locally-managed charging schedules.

TxProfileTxDefaultProfileMaxProfileStacking

Energy Cost Optimization

Time-of-use tariff awareness that shifts charging to off-peak windows automatically. Spot market integration for dynamic pricing, and cost modeling tools that show operators their savings potential.

ToU TariffsSpot MarketOff-PeakCost Modeling
Engineering Flow Icon

Engineering Flow

How we execute

01Site Assessment > Electrical Capacity AuditPlan
02Load Analysis > Demand ProfilingPlan
03Algorithm Design > Optimization ModelDesign
04OCPP Profile ImplementationBuild
05Simulation > Multi-Vehicle ScenariosTest
06Field Testing > Real Load ValidationTest
07Deployment > Site ConfigurationValidate
08Optimization > Continuous TuningOperate
Tech Stack Icon

Tech Stack

Tools & technologies

OCPP Smart Charging

Profile-based power management via OCPP SetChargingProfile messages.

ProfilesPeriodsStacking

Python

Optimization algorithms, data processing, and load balancing engine.

NumPySciPyPandas

Optimization Algorithms

Linear programming, constraint satisfaction, and real-time scheduling.

LPGreedyHeuristic

Energy Meters (Modbus)

Real-time power measurement at transformer and charger level.

RS-485RTUTCP

Solar Inverter APIs

Integration with SMA, Fronius, SolarEdge, and Huawei inverters.

SunSpecModbusREST

Grid Monitoring

CT clamp integration, power quality monitoring, and grid feed-in tracking.

CT ClampsPower QualityFeed-In

Time-Series Databases

InfluxDB and TimescaleDB for energy data storage and trend analysis.

InfluxDBTimescaleDBGrafana

MQTT / Event Streaming

Real-time data pipeline for meter readings and charger telemetry.

MQTTKafkaRedis Streams

Simulation Framework

Custom simulation tools for validating algorithms before field deployment.

PythonMonte CarloScenarios

Ready to optimize your charging infrastructure?

We build load management systems that maximize charger utilization within your grid constraints. Let us discuss your site.