Smart charging for Utilities
The first-ever vendor-neutral EV charging software that reduces costs and makes charging clean again
Available also as white-label
Increase customer satisfaction
Our prediction technology helps to use your and your customer's data to deliver clean and affordable energy to electric vehicles
Sell more additional services
Our technology helps you to deliver on-top-services to your customers to generate additional revenue while acting economically friendly.
Improve the charging experience
Your customer, their's employees, and clients engage better when using the charging station managed with your Charging Management Solution
Help to commit on clean energy and to oversee costs for electric vehicles
Companies have more and more charging stations on their site. Either as their own fleet or a new offering to employees or customers. Electric vehicles have an enormous positive impact on our environment but may also cause unforeseeable costs for the company.
As a utility, you can now help your commercial customers to make a positive impact on their environment while reducing energy costs. With ChargingLedger, you help to control their charging cycles. Like this, you can ensure that a car charges at the right time with the right rate.
Our algorithms are analyzing your customer's and your energy data to calculate the most environmentally friendly and cost-efficient load profile for each charging cycle. You may also combine this with our optimization method to reduce congestion on substation and grid lines.
How does it work?
ChargingLedger's Charging Management solution gives utilities one centralized, customizable platform to extend utilities' service beyond energy distribution. With ChargingLedger you can offer your Charging Management Solution to your most important customers. With our optional white-label product, the Charging Management Solution feels like your own service to your customers.
Schools and Universities
Cost efficient charging
Hands-on dashboard to see costs
Standard and customizable reports
Show current metering
Enable Managed Charging for Customers
Control your customers EVSE with ChargingLedger's communication platform using OCPP
Increase your and your customer's impact on the environment and let them set their KPI
Integrate your customer's solar panel to increase his self-supply
Combine With Our Grid Optimization
Combine the energy optimization with ChargingLedger's grid optimization methods
Prevent high utilization rates and possible constraints on substation or grid lines
Avoid street constructions or long grid projects in your service area
Optimize you customers' Energy Mix
Match green energy with EV charging using ChargingLedger's analytic platform
Schedule charging cycles when you deliver renewable energy to your customers
Increase your overall consumed renewable energy to achieve the utility's targets
See how you can give the best experience to your customers
Optimize your grid for residential charging
Electric vehicles in residential areas behave differently from other energy assets. The strong impact of the consumer's behavior requires special treatment. Especially, as the average charging time occurs between 5-9 PM, they become cost drivers for the energy distribution as well as become strategic assets for optimizing your energy supply (costs and renewables).
ChargingLedger provides vendor-neutral optimization software specified for residential energy assets such as electric vehicles. This includes the integration, visualization, and optimization for utility's energy supply and grid operation.
With residential charging equipment (EVSE)
On substations, transformers or grid lines
By reacting on changing weather situation and pricing
Tool sets for individual optimization of subnetworks or specific asset groups
Application of mathematical methods, heuristics and Machine Learning
Optimization based on historical data in combination with real-time internal and external data
Regular reports and KPI tracking personalized for users and the organization
USE CASE: Aggregation of EVs
Most charging cycles happen during the peak-time (4 - 9 pm)
80% of all charging cycles are highly shiftable (11 hrs)
Low-voltage networks in urban areas are more likely to be affected by these changes in consumption habits. When assuming an average urban residential area with about 250 households, we have for example a 250kVA transformer and a peak consumption of 180kVA between 4 pm and 9 pm.
If we add to these consumption habits the charging of 40-60 electric vehicles, we will see a consumption peak twice as large, with a demand on the grid of about 360kVA during the same period. In practice, this would imply the need to quadruple the installed capacity of the substation in order to ensure seamless electricity delivery.
ChargingLedger provides a software infrastructure for load shifting and Demand Response (DR) for utilities. We integrate EVSE (electric vehicle supply equipment) of residential consumers or of fleets and match the data to your current grid management systems or grid preferences. Consumers benefit from affordable and reliable charging with very little interaction to our system. The utility profits through reduced investment costs, lower expenses for financial incentives (as in time-of-use rates), better visualization and better use of renewable energy.
New trends are not only difficult to identify. They also behave differently regarding the geographical and technical environment. To estimate the impact of new energy assets such as electric vehicles, utilities have to assess their individual subnetworks and overall network with its very own circumstances.
Simulation helps to identify potential cost drivers and constraints in your energy grid or energy supply. Like this, the next steps can be evaluated from an economic and technical perspective. ChargingLedger offers dedicated solutions to measure the impact of electric vehicles and energy storages in order to help utilities in making their decision.
Economic and technical analysis of future market changes in your network and energy supply
Testing of grid or energy optimization for electric vehicles and energy storages
Applying load shifting, demand response, and frequency containment reserve
Individual preferences, visualization, reporting and network structure