/corrently-charge

Tariff builder for ChargePointOperators in the area of employee, tradefairs, hotels or areal parking.

Primary LanguageHTMLMIT LicenseMIT

corrently-charge

Corrently Charge is a full automated tariff evaluation process. It automatically chooses different tariffs to the client depending on final state of charge, available time and energy mix. Selected tariff requirements are fulfilled via a scheduler connection to CPO's backend (via OCPP protocol). The solution Corrently Charge acts as an intermediate between a given energy management system and the charge point.

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Challenge

Todays BEV charging lacks communication between driver/customer and charge point operator (CPO).

If we would know the goals the driver has by time of connecting to our charging point, we could optimize the charging session, for the driver, for us and for the environment.

Goals

  • integrate local generation (eq. photovoltaics) into tariffs
  • reduce scope2 greenhouse gas emissions for customers
  • ensure regulatory compliance
  • consult clients using data driving transparency
  • expedite adoption of eMobility by providing state of the art CX

Problem definition

The flexibility of BEV charging for demand-side-management could not be used in public or semi-public charging points. Local energy generation in conjunction with eMobility do not develop synergy effects making investments into energy management less attractive and limiting customer experience in an upcoming competitive market.

Proposed solution

Automated tariff evaluation as soon as charging session starts. Tariffs take local generation and green power index into account giving different tariffs to the client as options of required energy (final state of charge), available time, energymix.

Selected tariff requirements are automatically fulfilled via a scheduler connection to CPO's backend (via OCPP protocol). The sollution corrently-charge acts as an intermediate between a given energy management system and the charge point.

Core of the solution is encapsulated into an Open-Source Node Module NPM allowing to quickly adopts new tariff models or limit number of available models based on requirements at a certain location.

Sample Plugin UX

Business Model Canvas

Business Model Canvas

Or browse GIT

This prototype takes a real charging station located in the village Mauer (Germany) and uses the prediction of a PV power plant at the same grid connection point as local energy generation.

Configured prices

Price per kWh Source
0.75€ Mains / public grid
0.30€ PV / local generation

Architecture / Integration Points

Architecture Schema Charging

Download draw.io xml

Installation

npm install --save corrently-charge

Configuration

Either as .env or during instanciation

Setting Description
SOLAR_PREDICTION URL to the solar prediction API to use
GSI_PREDICTION URL to the Green Power Index API to use
localPrice Price per kwh for local energy (eq. solar)
gridPrice Price per kwh for energy from grid

Limitations

  • Does not respect none-linear maxpower
  • Does not respect reactive power in low power charging conditions

Maintainer / Imprint

STROMDAO GmbH
Gerhard Weiser Ring 29
69256 Mauer
Germany

+49 6226 968 009 0

kontakt@stromdao.com

Handelsregister: HRB 728691 (Amtsgericht Mannheim)

LICENSE

MIT