The integration of renewables, the decentralization of generation, and the growing number of power electronics devices in the grid are turning power systems into highly dynamic, complex environments. In this new paradigm, ensuring frequency stability after a disturbance is no longer a trivial task.
The job of Transmission System Operators has been to gather many signals, process them, and output the right control actions in real time. However, in a distributed environment, how are you supposed to maintain balance in the grid when there are thousands of intelligent devices that can make decisions on their own?
Now imagine an ideal scenario where every asset in the grid, including storage systems or converter-interfaced renewables with grid-following/grid-forming controls, to name a few, react locally, based on their own capabilities, but in perfect coordination with the rest of the system. No central controller, just collective intelligence.
That is what we are building with COLMENA, a project developed by the Barcelona Supercomputing Center in collaboration with eRoots. In this context, COLMENA introduces a fully distributed control system based on multiple agents that allows the grid to regulate itself in real time, intelligently, autonomously, and robustly.
The core of COLMENA is a network of software agents, each linked to a controllable device. Every agent is capable of executing different roles based on measurements and internal calculation rules rules, making them capable of selecting control actions that benefit both their local asset and the overall grid. Such is the case with the frequency, a magnitude that can be locally measured but is inherently global. This is achieved by applying a distributed Model Predictive Control (MPC).
Distributed MPC enables each agent to:
The method works in a loop:
This architecture requires no central coordinator and is naturally scalable. Even under severe disturbances, such as generator trips, or short-circuit faults, the system can reorganize control decisions on the fly and maintain frequency close to its nominal value.
We have tested COLMENA in large-scale simulations with promising results. Under various contingency scenarios, frequency deviations were quickly suppressed and control efforts were smoothly distributed across all assets.
Ideally, the next step is the transition from simulation to real-world demonstration, perhaps integrating hardware-in-the-loop testing and preparing COLMENA for deployment in microgrids, and eventually, utility-scale systems. Also, the actual MPC we have implemented relies on the DC approximation of the network. As we always preach, including non-linearities is eventually the way to go.
At eRoots, we believe the grid of the future will not be centrally controlled — it will be collectively controlled. With the vision of the Barcelona Supercomputing Center, COLMENA is a step toward making that vision real.
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