Current Approaches of Load Management for OCPP 1.6
The more complex topics are addressed in a particular niche, the easier it is to build a business. This applies to eMobility as well. This article explores the newest methods for load management as outlined in the OCPP 1.6 protocol. By examining these approaches, we aim to offer insights into their practical applications and implications for optimising charging infrastructure in the face of dynamic energy demands and grid integration.
Brief Overview of Load Management and OCPP 1.6
Load management (LM) optimises energy use and regulates electrical load in real-time, enhancing the efficiency of EV charging. It adjusts charging power based on the following factors:
- Demand.
- Grid capacity.
- Renewable energy availability.
The mentioned points prevent bottlenecks and ensure smooth operations. LM systems adapt the charging rate based on real-time conditions, supporting the efficient use of infrastructure and contributing to grid stability and sustainability.
OCPP 1.6 enhances support for LM in EV charging environments. The protocol facilitates the integration of load management systems, addressing challenges such as interoperability and real-time responsiveness for successful implementation.
We aim to provide a detailed examination of how the advancements in OCPP 1.6 can be leveraged to optimise LM practices. And as we transition from discussing load management, it’s essential to recognise how these strategies set the stage for the next evolution in EV technology. Moving forward, we’ll delve into the topic of smart charging, exploring how it builds on these principles to offer even greater efficiency and flexibility in managing EV charging.
Smart Charging
Smart charging allows a central system to manage the charging power or current for individual EVs or across multiple Charge Points. This management can be based on factors like:
- Grid connection.
- Energy availability.
- Building wiring.
Сontrol overcharging is governed by energy transfer limits, defined in a Charging Profile.
Charging Profile Types
Let’s investigate this further, as the information, although known, is quite intricate. Here are three types of charging profiles, as they are mentioned in OCPP (and small examples of them):
1.ChargePointMaxProfile: Used for load balancing, this profile limits the power or is currently shared among all connectors at a Charge Point. It is configured with the ChargingProfilePurpose set to “ChargePointMaxProfile” and applies only to ConnectorId 0.
Example: It means that when there is a single static limit (let’s say, 70 kW) on the total power for a charging station, and we’re not concerned with how the load is balanced among the connectors, the kind of profile mentioned is ideal. It ensures that the total power consumption never exceeds the set 70 kW limit regardless of the number of connectors in use.
2. TxDefaultProfile: This profile provides default charging policies for new transactions, such as restricting charging during certain times. If set to ConnectorId 0, it applies to all connectors; if set to a specific ConnectorId > 0, it applies only to that connector. A TxDefaultProfile for ConnectorId 0 can be overridden by a new profile for a particular connector.
Example: When you need a strategy for individually controlling each connector — whether in a residential complex or a parking facility — TxDefaultProfile is a useful tool. It allows each connector to be assigned a specific power limit, with the flexibility to adapt dynamically. For example, during the first 30 seconds of a charging session, while the dynamic power limit is being adjusted, the connector will already know its allocated limit. This helps ensure the connector operates within the defined parameters, preventing any disruption to the overall load management system.
3.TxProfile: This profile overrides the TxDefaultProfile for the duration of the transaction. Once the transaction ends, the profile should be deleted. If no transaction is active, the Charge Point will discard the TxProfile and reject the SetChargingProfile command.
For instance, the profile comes into play for load balancing when an instruction for a specific limit is received. As soon as the command is issued, this limit can be adjusted with minimal delays, ensuring that the power distribution is responsive and accurately managed throughout the transaction.
Stacking Charging Profiles
Stacking allows multiple charging profiles with the same purpose to be combined, creating intricate schedules. For instance, a TxDefaultProfile can be set for a week-long period, permitting complete power charging on weekdays from 11 PM to 6 AM and all day on weekends while allowing reduced power at other times. Additional profiles can be added to specify exceptions, such as holiday schedules.
The primary use case for stacking charging profiles is effectively managing load balancing. For instance, if a business unit needs to adjust power distribution over 48 hours, stacking profiles allows for nuanced control of power limits. This ensures that changes in power usage are well-regulated and can adapt to real-time needs, making stacked profiles essential for complex scheduling and efficient load management in practical applications.
Consider the following points:
- When a profile update with a future date is sent, it replaces the current profile, and default behaviour will apply until the new profile’s effective date. Providing a start time in the past helps avoid gaps.
- If stacking is used without a duration at the highest stack level, the Charge Point will not revert to lower stack levels.
Combining Charging Profile Purposes
In EV charging systems, a Composite Schedule is created by integrating different charging profiles based on their specific purposes. This process ensures that the charging power or current adheres to the most stringent limits defined by the relevant profiles.
How сomposite schedules work:
- Merging Profiles: The Composite Schedule combines multiple Charging Profiles, such as ChargePointMaxProfile and TxDefaultProfile (or TxProfile). The schedule takes the minimum available power or current value from the merged profiles for each time interval.
- Interval Variability: The time intervals used in the Composite Schedule can vary in length and do not need to be uniform across all profiles. This allows a flexible and adaptive charging strategy to handle different scheduling needs.
Key Points
- Power Constraints: At any given time, the power available as defined in the Composite Schedule must not exceed the lowest value from any merged profiles. This ensures that the most restrictive limits are respected, maintaining safety and efficiency.
- Multi-Connector Systems: For Charge Points with multiple connectors, the ChargePointMaxProfile applies to the combined energy flow across all connectors. The total power consumption across all connectors must remain within the limits set by this profile.
OCPP 1.6 Integration with Load Management
OCPP 1.6 introduces several critical enhancements significantly impacting LM for EV charging infrastructure. These enhancements are designed to address the growing demands for more flexible, scalable, and efficient charging solutions:
- Enhanced Communication Protocols: OCPP 1.6 provides communication between charge points and management systems through updated and more robust protocols. These updates include advanced methods for real-time data exchange, enabling more accurate monitoring and control of charging operations. For example, the protocol now supports higher-resolution data packets and more frequent updates, allowing LM systems to respond more effectively to fluctuating energy demands and grid conditions.
- Flexible Load Control Options: The protocol allows for finer adjustments in charging power, enabling advanced load balancing strategies based on real-time and predictive data. OCPP 1.6 prevents the overloading of local grids and optimises energy distribution across the network.
- Improved Demand Response Mechanisms: This includes better support for dynamic pricing models and grid signals, which can incentivise or control charging behaviour in alignment with broader grid management objectives.
Technical Aspects and Implementation
The technical architecture of LM systems integrated with OCPP 1.6 optimizes the interaction between charge points, management systems, and the grid. This architecture typically involves several key components and design principles. Here they are:
Network Design
The network design for LM systems using OCPP 1.6 involves a hierarchical structure. The central management system (CMS) oversees multiple charge points and handles load management algorithms. Charge points communicate with the CMS through OCPP 1.6/2.0.1.
Data Flows
This architecture’s data flows encompass various types of information, including real-time charging data, grid status updates, and user preferences.
This approach ensures efficient and dynamic power usage management, contributing to optimised energy distribution and enhanced performance of EV charging networks.
Control Mechanisms
The control mechanisms in a LM system involve the application of various algorithms and rules to manage the load dynamically. These mechanisms include:
- Load Balancing: Distributing the charging load across available charge points to prevent local grid overloads.
- Peak Shaving: Reducing the charging power during peak demand periods to lower overall energy costs.
- Demand Response: Adjusting charging schedules in response to signals from grid operators or energy market conditions.
Decision-Making Algorithms
We hope the information provided above has boosted your understanding of this topic. Just to remind you, Electriqua strictly adheres to all the principles discussed. As a result, our clients consistently achieve their desired business outcomes. Electriqua’s decision-making algorithms process real-time data to make informed choices about load management. These algorithms consider factors such as current grid conditions, energy prices, and charging priorities to:
- Adjust Power Levels: Modify the charging power at individual charge points to maintain balance and avoid overloading.
- Optimise Scheduling: Schedule charging sessions to minimise energy costs and align with grid conditions.
- Respond to Demand Signals: Adapt charging patterns based on signals from grid operators or energy market changes.
To Sum Up
OCPP 1.6 allows us to respond to real-time grid conditions and energy demands, supporting a smoother and more reliable charging experience. These advancements, whether through precise load balancing, centralised control, or local management, ensure that we maximize our energy resources while maintaining grid stability. With these tools at our disposal, we are better equipped to meet the challenges of modern energy demands and drive forward the sustainable adoption of electric vehicles.
Of course, OCPP 1.6 is the current standard that everyone is using. However, there’s a lot of anticipation surrounding OCPP 2.0.1, which promises even more advanced features and improvements. This upcoming version is set to elevate the standard further, bringing us closer to a more sophisticated and seamless charging experience. We’re excited about the future and will keep you updated on all the latest developments.