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Applications

Computing for Grid Integration and Dispatch

Modeling how a fusion plant would connect to and behave within a power grid that must balance supply and demand every second.

The grid's constraint

An electrical grid must match generation to load continuously; a persistent imbalance changes frequency and can trigger protective disconnections. Any new generator must integrate into this balancing act: respond appropriately to frequency, provide or absorb reactive power, and behave predictably during disturbances. Dispatch is the decision of how much each generator produces at each moment to meet load reliably.

What is modeled

Kronos motion — power balance

Baseload versus flexibility

A fusion plant is naturally suited to steady, high-availability output. But grids increasingly value flexibility, the ability to change output as variable renewables rise and fall. Integration studies model both roles and the trade-offs between running steadily and following load, since the two impose different demands on the plant.

python
def frequency_response(f, f_nominal, droop, p_now, p_max):
    # simple droop control: adjust power toward restoring frequency
    dp = -(f - f_nominal)/f_nominal / droop
    return min(max(p_now + dp*p_max, 0), p_max)

Why simulate before connecting

Grid operators require studies showing a new plant will not destabilize the network under normal and fault conditions. These are computational studies of power flow, stability, and dynamics performed long before interconnection. The burner housings Aegis (fixed defense installations) and MetroVolt (data centers) target specific connection contexts, each with its own integration profile.

Honest scope

This is systems modeling that deliberately excludes economics. It answers whether and how a plant can connect and behave well, not what dispatch would be worth.