Summary

This project aimed to test the flexibility of residential energy injection by optimizing solar power systems and battery storage in alignment with dynamic pricing signals. The study focused on two strategies: 1. blocking energy injection during negative pricing periods, and 2. shifting injection to peak price times using battery storage. These methods effectively illustrate the benefits of using a price signal to adjust the electricity injection by prosumers.

However, we also highlight the risk of a widespread adoption of such systems that could lead to grid congestion and imbalances if Distribution System Operators (DSOs) are not integrated into the process.

The challenge

As the EU market progresses in the energy transition, the importance of energy efficiency as a structural solution to addressing and improving the demands of sustainable energy becomes increasingly evident. By improving the flexibility of residential energy consumption to preventing grid congestion and imbalances, consumers can actively contribute to stablizing the energy system, reducing peak demand and potentially saving costs . This small R&D project aimed to explore this by developing a device capable of controlling and optimizing the operation of residential solar production and battery storage, in alignment with dynamic pricing.

The core focus of this research was to test the flexibility of energy injection optimized for ENTSO dynamic pricing signals. While this optimization approach primarily considers price signals and hence does not account for DSO congestion constraints, it provides valuable insights into the technical feasibility and potential (positive and negative) impact of such a system.

Our study explored two key optimization strategies for energy injection:

1. Blocking Injection During Negative Price Periods

Negative wholesale electricity prices are increasingly common. For instance, in August 2024, the number of hours with negative prices more than doubled compared to the same period in 2023.

Cumulative hours of negative wholesale electricity prices in Belgium.

Injecting power into the grid during these periods incurs costs rather than generating revenue, thus making it a key scenario to avoid. However, simply disabling the inverter isn’t sufficient either : we still want to align production and house consumption to prevent the need to draw electricity from the grid (at least if the negative price does not compensate the grid fee).

2. Shifting Injection to Peak Price Periods

Another optimization strategy involves the storage of energy in a domestic battery storage to delay energy injection to times of peak electricity prices. While daily price spreads around €80/MWh, this approach can enhance revenue, depending on the battery capacity dedicated to this strategy.

By focusing on these two behaviors, the project demonstrates the potential for optimizing residential solar production and battery usage within the current energy market framework.

Monthly average of the daily spread for the wholesale electricity prices in Belgium

Our approach

Hardware

  • DSO: Fluvius grid (Belgian Flemish region)
  • Energy supplier: Engie Dynamic Pricing (based on ENTSO-E Day Ahead Pricing – Belgian bidding zone).
  • Solar installation: 14.6kVA peak and 2 Huawei inverters 5kVA each.
  • Battery: Huawei LUNA 2000, 10 kWh and 5kW.
  • Micro controller: Raspberry Pi 4
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Raspeberry Pi 4

Raspeberry Pi 4 connected via Ethernet / TCP / MODBUS to the inverters and battery

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Inverters and battery

2 inverters (5kW) & 1 battery (10kWh)

Infrastructure

The Raspberry Pi microcontroller runs a python module with the following characteristics :

Input data:

  • Day ahead prices downloaded from ENTSO-E API
  • Solar irradiance forecast
  • House consumption in real-time

Python module

  • Optimisation model that define the battery strategy for the next day: timing and power for charge and discharge.
  • Operational module that sends commands to the inverters in real time.

Output:

  • Send commands (using MODBUS over TCP) to the inverters to
    • During periods of negative price, adjust the output power to the house consumption
    • Command the battery pack according to the defined strategy.

Architecture diagram

The results

The system is currently deployed to a production environment, running continuously. It successfully blocks energy injection during periods of negative pricing, while allowing the inverter to continue producing energy to meet the household’s immediate consumption needs.

Additionally, the battery is strategically charged during low-price intervals and discharged during peak price periods.

The charts below illustrates this behavior for July 14, 2024.

Conclusion and DSO perspective

This minimal setup shows the potential positive impacts of incentivising injection flexibility towards a more virtuous injection behavior. This strategy can provide great benefits for the final consumers, while also contributing to reducing the congestion at the DSO level if correctly governed.

However, if DSO’s are are excluded from the strategy, optimizing energy injection based solely on price signals (currently controlled by the TSO) can lead to significant challenges for both DSOs and TSOs. If widely adopted, such systems could indeed synchronize injection profiles across numerous households, negatively impacting grid congestion for DSOs and potentially causing imbalances for TSOs. 

As a consequence, DSOs may face the burden of investing in and upgrading grid infrastructure to handle a demand profile over which they have little control. To mitigate these issues, several measures could be explored in future developments:

  1. Support and Incentivization for Battery Installation and DSO-Optimized Energy Management Systems: Encouraging residential consumers to implement energy management systems tailored to the needs of the DSO could help alleviate grid congestion and optimize overall performance.
  2. Dynamic Grid Fees and Grid-Friendly Price Signals: Introducing a dynamic grid fee structure, or « Optimal Grid-Friendly Price Signals, » could better align consumer behavior with the needs of the grid. Although the « capacity tariff » introduced by Fluvius is a step in this direction, it has notable limitations, such as its lack of time-sensitivity and the static nature of the monthly fee, which fails to incentivize a balanced consumption pattern throughout the month.

Addressing these challenges will require a coordinated approach between TSOs, DSOs, and residential consumers, ensuring that grid stability is maintained while enabling the benefits of flexible energy management.