Bulgaria – 6G-VERSUS

AI-driven wide area monitoring and control of Distributed Energy Resourses (DERs)

Sustainability Aspects: Energy grid management for wind farms and DERs

Targeted Vertical: Renewable Energy Systems

Partners:

Entra Energy: Use Case leader
University of Cyprus: Technical co-leader. Developer and Integrator
A1 Bulgaria: Telecom Operator and testbed provider
Software Company: Developers and Integrators

The Bulgarian use case focuses on energy grid management and real-time DER monitoring. The location of the trial site is spread between Sofia where the Central Vertical application is located and Southeast Bulgaria where the Wind turbine and BESS are located and Regional application is deployed.

6G-VERSUS Bulgarian Pilot – AI-data driven monitoring and control of distributed renewable sources

Motivation and challenges:

The transition to a smart grid, aiming for full renewable energy resources (RES) utilization by 2050, poses environmental benefits and technical hurdles due to renewable power’s unpredictability. Distribution grids face complexity from renewable integration and dynamic loads like electric vehicles and challenging traditional grid management during disturbances. 6G technology promises ubiquitous connectivity and ultra-fast communication, facilitating real-time coordination of distributed energy resources (DERs), like RES and energy storage systems (ESS), enhancing grid stability and efficiency. Storage and demand side management (DMS) offer fast, flexible solutions, but effective coordination is essential. 6G technology, with features like massive MIMO and cell-free networks, enables high-capacity, low-latency communication, fostering dynamic network optimization based on real-time information, as illustrated in the figure below:

Key benefits of 6G-fast-DERs integration are: (1) ultra-fast frequency support (UFFS) down to sub-millisecond communication (as theoretically envisioned for 6G), allowing the fast ESSs to respond instantly to frequency deviations; (2) voltage regulation (VR) by means of coordinated voltage control to stabilize the grid operation during load changes or faults (significant disturbances), (3) resilience: 6G’s facilitate grid resilience and robustness against cyber/physical threats by adopting a zero-trust network-design architecture for all critical grid components which require communication, (4) advanced control strategies: ML and AI algorithms optimize DERs dispatch based on predictive models and decentralized decision-making, ensuring adaptability to changing grid dynamics.

Solutions/Trial scenarios to address the challenges

In this context, the Bulgarian pilot will investigate user-centric systems where fast DERs communicate directly with each other, exploring A1 production network infrastructure for flexible and interoperable communication. Moreover, three main challenges of smart grids will be addressed:

(1) enhance reliability and resilience of smart grids using distributed control system (DCS) architectures and 6G communication. DCS allows a decentralized decision-making in smart grids which improves grid resilience and reliability in cases of natural or man-made generated grid disturbances, by allowing the system to quickly adapt and reroute power flow such that to minimize its downtime. For an efficient DSC it is highly important that the 6G communication provides consistent ULL and high reliability communication performance, especially during network congestions or adverse conditions.

(2) improved voltage and frequency control by fine-tuning voltage and frequency levels across the grid (with a focus on high-RES penetration regions of distribution power grids the so-called grid edge). Small DERs integration in remote areas using DCS and 6G communication technology aims to manage variable generation and ultra-fast ESS proactively. This includes AI-based agents’ development to predict and adjust responses to grid disturbances, optimizing DERs and ESS dispatch based on real-time grid conditions, and implementing distributed predictive control strategies to enhance regional coordination of DERs amidst changing grid dynamics.

(3) leverage on edge computing and localization advanced features of 6G networks to support identification of changes in the grid dynamics. Edge computing plays a vital role in enabling real-time processing and decision making in smart grids, prompting the testing of 6G network capabilities to support distributed computing at the network edge. This involves running pre-trained ML models locally on edge network components to minimize data transmission. Additionally, the implementation of smart grid applications necessitates a zero-trust network architecture, requiring default authentication for all devices and users due to the critical nature of data involved.

The main 6G-VERSUS application components (app triplet) are summarized in Table 1.

Table 1: 6G-VERSUS application components for Bulgarian use case

Simple Table

V-apps	Due to technical and legislative limitations, the pilot is executed across two testbeds: A) the real-life Bulgarian pilot testbed involving A1’s production telco infrastructure and Entra Energy’s energy assets in Southeast Bulgaria; and B) Digital Twin pre-pilot setup at UCY. The pilot deploys four interconnected V-Apps as a V-App cluster. These are: • V-App Central WAM (Wide Area Monitoring) • V-App Central WAC (Wide Area Control) • V-App Regional – monitoring DERs, and • V-App Regional Controller – RC that together provide IoT sensor- and PMU-based wide-area monitoring and control, real-time monitoring of distributed energy resources, centralised computation of control actions and regional execution of control requests, collectively enabling the end-to-end monitoring and control chain of the Bulgarian energy use case.
AI-apps	The AI-App will provide predictive analytics for short-term grid frequency evolution and early estimation of frequency nadir, enhancing real-time PMU monitoring with predictive intelligence to support preventive control actions for grid stability and outage prevention in low-inertia conditions.
N-Apps	The N-App of the Bulgarian pilot will provide network performance data and adaptive network control to support reliable sensor-network communication, including dynamic QoS optimisation and transmission efficiency adjustments based on network conditions, while interfacing the 5G Core Network with the V-App Central via OpenCAPIF.

As sustainability is of vital importance in 6G-VERSUS, the main sustainability challenges are summarized together with the expected outcomes of this use case in Table 2.

Table 2: Main sustainability challenges and expected outcomes for Bulgarian use case.

Main Sustainability Challenges
1) Environmental sustainability: a) Avoidance of RES curtailment, together with the efficient integration of renewable energy sources (RES) into the grid, enhances their utilisation and contributes to a reduced environmental footprint. b) reduced land disturbance and habitat disruption through replacing wired communication infrastructure with mobile communication in the grid control centre.
2) Social sustainability: a) Improved grid stability enhances system reliability and reduces the likelihood of blackouts. b) The extension of 6G networks into remote areas facilitates the integration of renewable energy sources (RES) into the power grid, while simultaneously enabling connectivity access for underserved communities. c) Higher annual operational uptime of renewable energy sources (RES) enhances the affordability and stability of energy supply to communities.
3) Economic Sustainability: a) Efficient integration of RES to the grid optimises the revenue management of RES owners.
Expected Outcomes
1) Enhanced grid stability and reliability: The distributed wide area controller enhances grid stability by efficiently managing the variability and intermittency of RES. Through dynamic coordination of RES and ESS units, it effectively mitigates voltage fluctuations, frequency deviations, and other grid instabilities, thereby boosting overall system reliability.
2) Optimized utilization of renewable resources: Through advanced optimization algorithms and predictive analytics, the controller maximizes the utilization of renewable resources by forecasting generation patterns and coordinating the dispatch of RES and ESS units, thereby optimizing clean energy integration while minimizing curtailment and waste.
3) Reduced operational costs and environmental impact: The wide area controller utilizes DERs and energy storage to enable efficient power system operation. By employing intelligent energy scheduling and demand-side management, it helps utilities optimize generation, transmission, and distribution, leading to cost savings and environmental benefits.
4) Improved grid resilience: The distributed wide area controller bolsters the power system's resilience by mitigating threats like extreme weather, equipment failures, and cyber-attacks. Its decentralized control and autonomous decision-making capabilities enable swift response and recovery during emergencies, ensuring minimal impact on critical infrastructure and enhancing overall grid resilience.
5) Facilitation of grid modernization and integration: Distributed wide area controller represents a crucial step towards the modernization and integration of the electric grid. By providing a platform for seamless communication and coordination among diverse grid assets, including RES, ESS, and demand response resources, the controller paves the way for a more flexible, efficient, and sustainable energy system.